innovation – Technology Liberation Front https://techliberation.com Keeping politicians' hands off the Net & everything else related to technology Thu, 03 Apr 2025 23:20:10 +0000 en-US hourly 1 6772528 Podcast: Should We Regulate AI? https://techliberation.com/2023/05/08/podcast-should-we-regulate-ai/ https://techliberation.com/2023/05/08/podcast-should-we-regulate-ai/#comments Mon, 08 May 2023 12:15:12 +0000 https://techliberation.com/?p=77120

It was my pleasure to recently join Matthew Lesh, Director of Public Policy and Communications for the London-based Institute of Economic Affairs (IEA), for the IEA podcast discussion, “Should We Regulate AI?” In our wide-ranging 30-minute conversation, we discuss how artificial intelligence policy is playing out across nations and I explained why I feel the UK has positioned itself smartly relative to the US & EU on AI policy. I argued that the UK approach encourages a better ‘innovation culture’ than the new US model being formulated by the Biden Administration.

We also went through some of the many concerns driving calls to regulate AI today, including: fears about job dislocations, privacy and security issues, national security and existential risks, and much more.

Additional reading:

]]> https://techliberation.com/2023/05/08/podcast-should-we-regulate-ai/feed/ 6 77120 My Latest Study on AI Governance https://techliberation.com/2023/04/20/my-latest-study-on-ai-governance/ https://techliberation.com/2023/04/20/my-latest-study-on-ai-governance/#comments Thu, 20 Apr 2023 18:25:29 +0000 https://techliberation.com/?p=77114

The R Street Institute has just released my latest study on AI governance and how to address “alignment” concerns in a bottom-up fashion. The 40-page report is entitled, “Flexible, Pro-Innovation Governance Strategies for Artificial Intelligence.”

My report asks, is it possible to address AI alignment without starting with the Precautionary Principle as the governance baseline default? I explain how that is indeed possible. While some critics claim that no one is seriously trying to deal with AI alignment today, my report explains how no technology in history has been more heavily scrutinized this early in its life-cycle as AI, machine learning and robotics. The number of ethical frameworks out there already is astonishing. We don’t have too few alignment frameworks; we probably have too many!

We need to get serious about bringing some consistency to these efforts and figure out more concrete ways to a culture of safety by embedding ethics-by-design. But there is an equally compelling interest in ensuring that algorithmic innovations are developed and made widely available to society.

Although some safeguards will be needed to minimize certain AI risks, a more agile and iterative governance approach can address these concerns without creating overbearing, top-down mandates, which would hinder algorithmic innovations – especially at a time when America is looking to stay ahead of China and other nations in the global AI race.

My report explores the many ethical frameworks that professional associations have already formulated as well as the various other “soft law” frameworks that have been devised. I also consider how AI auditing and algorithmic impact assessments can be used to help formalize the twin objectives of “ethics-by-design” and keeping “humans in the loop,” which are the two principles that drive most AI governance frameworks. But it is absolutely essential that audits and impact assessments are done right to ensure it does not become an overbearing, compliance-heavy, and politicized nightmare that would undermine algorithmic entrepreneurialism and computational innovation.

Finally, my report reviews the extensive array of existing government agencies and policies that ALREADY govern artificial intelligence and robotics as well as the wide variety of court-based common law solutions that cover algorithmic innovations. The notion that America has no law or regulation covering artificial intelligence today is massively wrong, as my report explains in detail.

I hope you’ll take the time to check out my new report. This and my previous report on “Getting AI Innovation Culture Right” serve as the foundation of everything we have coming on AI and robotics from the R Street Institute. Next up will be a massive study on global AI “existential risks” and national security issues. Stay tuned. Much more to come!

In the meantime, you can find all my recent work here on my “Running List of My Research on AI, ML & Robotics Policy.”

Additional Reading:

]]> https://techliberation.com/2023/04/20/my-latest-study-on-ai-governance/feed/ 4 77114 What Policy Vision for Artificial Intelligence? https://techliberation.com/2023/04/02/what-policy-vision-for-artificial-intelligence/ https://techliberation.com/2023/04/02/what-policy-vision-for-artificial-intelligence/#comments Sun, 02 Apr 2023 21:32:49 +0000 https://techliberation.com/?p=77103

In my latest R Street Institute report, I discuss the importance of “Getting AI Innovation Culture Right.” This is the first of a trilogy of major reports on what sort of policy vision and set of governance principles should guide the development of  artificial intelligence (AI), algorithmic systems, machine learning (ML), robotics, and computational science and engineering more generally. More specifically, these reports seek to answer the question, Can we achieve AI safety without innovation-crushing top-down mandates and massive new regulatory bureaucracies? 

These questions are particular pertinent as we just made it through a week in which we’ve seen a major open letter issued that calls for a 6-month freeze on the deployment of AI technologies, while a prominent AI ethicist argued that governments should go further and consider airstrikes data processing centers even if the exchange of nuclear weapons needed to be considered! On top of that, Italy became the first major nation to ban ChatGPT, the popular AI-enabled chatbot created by U.S.-based OpenAI.

My report begins from a different presumption: AI, ML and algorithmic technologies present society with enormously benefits and, while real risks are there, we can find better ways of addressing them. As I summarize:

The danger exists that policy for algorithmic systems could be formulated in such a way that innovations are treated as guilty until proven innocent—i.e., a precautionary principle approach to policy—resulting in many important AI applications never getting off the drawing board. If regulatory impediments block or slow the creation of life-enriching, and even life-saving, AI innovations, that would leave society less well-off and give rise to different types of societal risks.

I argue that it is essential we not trap AI in an “innovation cage” by establishing the wrong policy default for algorithmic governance but instead work through challenges as they come at us. The right policy default for the internet and for AI continues to be “innovation allowed.” But AI risks do require serious governance steps. Luckily, many tools exist and others are being created. While my next major report (due out April 20th) offers far more detail, this paper sketches out some of those mechanisms. 

The goal of algorithmic policy should be for policymakers and innovators to work together to find flexible, iterative, agile, bottom-up governance solutions over time. We can promote a culture of responsibility among leading AI innovators and balance safety and innovation for complex, rapidly evolving computational and computing technologies like AI. This approach is buttressed by existing laws and regulations, as well as common law and the courts.

The new Biden Admin “AI Bill of Rights” unfortunately represents a fear-based model of technology policymaking that breaks from the superior Clinton framework for the internet & digital technology. Our nation’s policy toward AI, robotics & algorithmic innovation should instead embrace a dynamic future and the enormous possibilities that await us.

Please check out my new paper for more details. Much more to come. And you can also check out my running list of research on AI, ML robotics policy.

]]> https://techliberation.com/2023/04/02/what-policy-vision-for-artificial-intelligence/feed/ 3 77103 US Chamber AI Commission Launches https://techliberation.com/2023/03/11/us-chamber-ai-commission-launches/ https://techliberation.com/2023/03/11/us-chamber-ai-commission-launches/#respond Sat, 11 Mar 2023 13:54:14 +0000 https://techliberation.com/?p=77094

This week, the U.S. Chamber of Commerce Commission on Artificial Intelligence Competitiveness, Inclusion, and Innovation (AI Commission) released a major report on the policy considerations surrounding AI, machine learning (ML) and algorithmic systems. The 120-page report concluded that “AI technology offers great hope for increasing economic opportunity, boosting incomes, speeding life science research at reduced costs, and simplifying the lives of consumers.” It was my honor to serve as one of the commissioners on the AI Commission and contribute to the report.

Over at the R Street Institute blog, I offer a quick summary of the major findings and recommendations from the report and argue that, along with the National Institute of Standards and Technology (NIST)’s recently released AI Risk Management Framework, the AI Commission report offers, “a constructive, consensus-driven framework for algorithmic governance rooted in flexibility, collaboration and iterative policymaking. This represents the uniquely American approach to AI policy that avoids the more heavy-handed regulatory approaches seen in other countries and it can help the United States again be a global leader in an important new technological field,” I conclude. Check out the blog post and the full AI Commission report if you are following debates of algorithmic policy issues. There’s lot of important material in there.

For more info on AI policy developments, check out my running list of research on AI, ML robotics policy.

]]> https://techliberation.com/2023/03/11/us-chamber-ai-commission-launches/feed/ 0 77094 Studies Document Growing Cost of EU Privacy Regulations https://techliberation.com/2023/02/09/studies-document-growing-cost-of-eu-privacy-regulations/ https://techliberation.com/2023/02/09/studies-document-growing-cost-of-eu-privacy-regulations/#comments Thu, 09 Feb 2023 16:22:47 +0000 https://techliberation.com/?p=77086

[Originally published on Medium on 2/5/2022]

In an earlier essay, I explored “Why the Future of AI Will Not Be Invented in Europe” and argued that, “there is no doubt that European competitiveness is suffering today and that excessive regulation plays a fairly significant role in causing it.” This essay summarizes some of the major academic literature that leads to that conclusion.

Since the mid-1990s, the European Union has been layering on highly restrictive policies governing online data collection and use. The most significant of the E.U.’s recent mandates is the 2018 General Data Protection Regulation (GDPR). This regulation established even more stringent rules related to the protection of personal data, the movement thereof, and limits what organizations can do with data. Data minimization is the major priority of this system, but there are many different types of restrictions and reporting requirements involved in the regulatory scheme. This policy framework also has ramifications for the future of next-generation technologies, especially artificial intelligence and machine learning systems, which rely on high-quality data sets to improve their efficacy.

Whether or not the E.U.’s complicated regulatory regime has actually resulted in truly meaningful privacy protections for European citizens relative to people in other countries remains open to debate. It is very difficult to measure and compare highly subjective values like privacy across countries and cultures. This makes benefit-cost analysis for privacy regulation extremely challenging — especially on the benefits side of the equation.

What is no longer up for debate, however, is the cost side of the equation and the question of what sort of consequences the GDPR has had on business formation, competition, investment, and so on. On these matters, standardized metrics exist and the economic evidence is abundantly clear: the GDPR has been a disaster for Europe.

Summary of Major Studies on Impact of EU Data Regulation

Consider the impact of E.U. data controls on business startups and market structure. GDPR and other regulations greatly limit the flow of data to innovative upstarts who need it most to compete, leaving only the largest companies who can afford to comply to control most of the market. Benjamin Mueller of ITIF notes that it is already the case that just “two of the world’s 30 largest technology firms by market capitalization are from the EU,” and only “5 of the 100 most promising AI startups are based in Europe,” while private funding of AI startups in Europe for 2020 ($4 billion) was dwarfed by US ($36 billion) and China ($25 billion). These issues are even more pressing as the E.U. looks to advance a new AI Act, which would layer on still more regulatory restrictions.

In concrete terms, this has meant that the E.U. came away from the digital revolution with “the complete absence of superstar companies,” argue competition policy experts Nicolas Petit and David Teece. There are no European versions of Microsoft, Google, or Apple, even though Europeans clearly demand the sort of products and services those US-based companies provide. Entrepreneurialism scholar Zoltan Acs asks: “What has been the outcome of E.U. policy in limiting entrepreneurial activity over recent decades?” His conclusion:

It is immediately clear… that the United States and China dominate the platform landscape. Based on the market value of top companies, the United States alone represents 66% of the world’s platform economy with 41 of the top 100 companies. European platform-based companies play a marginal role, with only 3% of market value.

Several recent studies have documented the costs associated with the GDPR and the E.U.’s heavy-handed approach to data flows more generally. Here is a rundown of some of the academic evidence and a summary of the major findings from these studies.

“There is a growing body of economic literature and commentary showing that the costs of implementing the GDPR benefit large online platforms, and that consent-based data collection gives a competitive advantage to firms offering a range of consumer-facing products compared to smaller market actors. This in turn increases concentration in a number of digital markets where access to data is important, by creating barriers to entry or encouraging market exit.” (p. 2–3)

“this paper examines how privacy regulation shaped firm performance in a large sample of companies across 61 countries and 34 industries. Controlling for firm and country-industry-year unobserved characteristics, we compare the outcomes of firms at different levels of exposure to EU markets, before and after the enforcement of the GDPR in 2018. We find that enhanced data protection had the unintended consequence of reducing the financial performance of companies targeting European consumers. Across our full sample, firms exposed to the regulation experienced a 8% decline in profits, and a 2% reduction in sales. An exception is large technology companies, which were relatively unaffected by the regulation on both performance measures. Meanwhile, we find the negative impact on profits among small technology companies to be almost double the average effect across our full sample. Following several robustness tests and placebo regressions, we conclude that the GDPR has had significant negative impacts on firm performance in general, and on small companies in particular.” (p. 1)

“We show that websites’ vendor use falls after the European Union’s General Data Protection Regulation (GDPR), but that market concentration also increases among technology vendors that provide support services to websites. We collect panel data on the web technology vendors selected by more than 27,000 top websites internationally. The week after the GDPR’s enforcement, website use of web technology vendors falls by 15% for EU residents. Websites are more likely to drop smaller vendors, which increases the relative concentration of the vendor market by 17%. Increased concentration predominantly arises among vendors that use personal data such as cookies, and from the increased relative shares of Facebook and Google-owned vendors, but not from website consent requests. Though the aggregate changes in vendor use and vendor concentration dissipate by the end of 2018, we find that the GDPR impact persists in the advertising vendor category most scrutinized by regulators. Our findings shed light on potential explanations for the sudden drop and subsequent rebound in vendor usage.” (p. 1)

“GDPR creates inherent tradeoffs between data protection and other dimensions of welfare, including competition and innovation. While some of these effects were acknowledged when constructing the legal data regime, many were disregarded. Furthermore, the magnitude and breadth of such effects may well constitute an unintended and unheeded welfare-reducing consequence. As this article shows, the GDPR limits competition and increases concentration in data and data-related markets, and potentially strengthens large data controllers. It also further reinforces the already existing barriers to data sharing in the EU, thereby potentially reducing data synergies that might result from combining different datasets controlled by separate entities.” (pp. 3–4)

“Using data on 4.1 million apps at the Google Play Store from 2016 to 2019, we document that GDPR induced the exit of about a third of available apps; and in the quarters following implementation, entry of new apps fell by half. We estimate a structural model of demand and entry in the app market. Comparing long-run equilibria with and without GDPR, we find that GDPR reduces consumer surplus and aggregate app usage by about a third. Whatever the privacy benefits of GDPR, they come at substantial costs in foregone innovation.”

“this paper empirically quantifies the effects of the enforcement of the EU’s General Data Protection Regulation (GDPR) on online user behavior over time, analyzing data from 6,286 websites spanning 24 industries during the 10 months before and 18 months after the GDPR’s enforcement in 2018. A panel differences estimator, with a synthetic control group approach, isolates the short- and long-term effects of the GDPR on user behavior. The results show that, on average, the GDPR’s effects on user quantity and usage intensity are negative; e.g., the numbers of total visits to a website decrease by 4.9% and 10% due to GDPR in respectively the short- and long-term. These effects could translate into average revenue losses of $7 million for e-commerce websites and almost $2.5 million for ad-based websites 18 months after GDPR. The GDPR’s effects vary across websites, with some industries even benefiting from it; moreover, more-popular websites suffer less, suggesting that the GDPR increased market concentration.”

“This paper investigates the impact of the General Data Protection Regulation (GDPR for short) on consumers’ online browsing and search behavior using consumer panels from four countries, United Kingdom, Spain, United States, and Brazil. We find that after GDPR, a panelist exposed to GDPR submits 21.6% more search terms to access information and browses 16.3% more pages to access consumer goods and services compared to a non-exposed panelist, indicating higher friction in online search. The implications of increased friction are heterogeneous across firms: Bigger e-commerce firms see an increase in consumer traffic and more online transactions. The increase in the number of transactions at large websites is about 6 times the increase experienced by smaller firms. Overall, the post-GDPR online environment may be less competitive for online retailers and may be more difficult for EU consumers to navigate through.”

“Privacy regulations should increase trust because they provide laws that increase transparency and allow for punishment in cases in which the trustee violates trust. […] We collected survey panel data in Germany around the implementation date and ran a survey experiment with a GDPR information treatment. Our observational and experimental evidence does not support the hypothesis that the GDPR has positively affected trust. This finding and our discussion of the underlying reasons are relevant for the wider research field of trust, privacy, and big data.”

“We follow more than 110,000 websites and their third-party HTTP requests for 12 months before and 6 months after the GDPR became effective and show that websites substantially reduced their interactions with web technology providers. Importantly, this also holds for websites not legally bound by the GDPR. These changes are especially pronounced among less popular websites and regarding the collection of personal data. We document an increase in market concentration in web technology services after the introduction of the GDPR: Although all firms suffer losses, the largest vendor — Google — loses relatively less and significantly increases market share in important markets such as advertising and analytics. Our findings contribute to the discussion on how regulating privacy, artificial intelligence and other areas of data governance relate to data minimization, regulatory competition, and market structure.”

William Rinehart of the Center for Growth and Opportunity has compiled and summarized many additional studies that document the costs associated with restrictions on data, including many state privacy laws imposed in the United States.

“The Biggest Loser”: Innovation Culture Gone Wrong

Taken together, this evidence makes it clear that, “Well-meaning privacy laws can have the unintended consequence of penalizing smaller companies within technology markets.” It can also have broader geopolitical ramifications for continental competitive advantage and engagement between countries. Some have argued that the United Kingdom’s so-called “Brexit” from the EU can be viewed as not only an effort to reclaim its sovereignty but more specifically “to escape its crippling regulatory structure.” The E.U.’s approach to emerging technology regulation likely had some bearing on this. Acs argues that Britain’s move was logical, “because E.U. regulations were holding back the U.K.’s strong DPE (digital platform economy).” “If the United Kingdom was to realize its economic potential,” he says, “it had to extricate itself from the European Union,” due to the growing “dysfunctional E.U. bureaucracy.”

Can Europe turn things around? Most market watchers do not believe that the E.U. will be willing to change its regulatory course in such a way that the continent would suddenly become more open to data-driven innovation. As part of a Spring 2022 journal symposium, The International Economy asked 11 experts from Europe and the U.S. to consider where the European Union currently stood in “the global tech race.” The responses were nearly unanimous and bluntly summarized in the symposium’s title: “The Biggest Loser.” Several respondents observed how “Europe is considered to be lagging behind in the global tech race,” and “is unlikely to become a global hub of innovation.” “The future will not be invented in Europe,” another respondent concluded. Europe’s risk-averse culture and preference for meticulously detailed and highly precautionary regulatory regimes were repeatedly cited as factors.

Europe has become the biggest loser on the digital technology front not because of their people but because of their policy. Europe is filled with some of the most important advanced education and engineering programs in the world, and countless brilliant minds there could be leading world-leading digital technology companies that could rival the U.S., China, and the rest of the world. But Europe’s current “innovation culture” simply will not allow it.

Innovation culture refers to “the various social and political attitudes and pronouncements towards innovation, technology, and entrepreneurial activities that, taken together, influence the innovative capacity of a culture or nation.” A positive innovation culture depends upon a dynamic, open economy that encourages new entry, entrepreneurialism, continuous investment, and the free movement of goods, ideas, and talent.

At this point in time, it is clear that — at least for data-driven sectors — the E.U. has created the equivalent of an anti-innovation culture, and the GDPR has clearly played a major rule in that outcome. This regulatory regime has also had devastating consequences for venture capital formation and investment more generally in Europe. “Public policy and attitudes explain the relative technological decline and lack of economic dynamism,” Petit and Teece argue, and it has resulted in, “weak venture capital markets, fragmented research capabilities, low worker mobility and frustrated entrepreneurs.”

Industrial Policy Won’t Save Europe

While the E.U. is aggressively regulating data-driven sectors, it is simultaneously trying to use industrial policy programs to advance new technological capabilities and innovations. European policymakers would obviously like to avoid a repeat of the past quarter century and the lack of digital technology competition and innovation they witnessed.

But past European industrial policy efforts on the digital technology front have largely failed, as Connor Haaland and I documented earlier. Zoltan Acs notes that, despite many state efforts to promote digital innovation across the continent in recent decades, the E.U.’s regulatory policies have resulted in the opposite. “The European Union protected traditional industries and hoped that existing firms would introduce new technologies. This was a policy designed to fail,” he argues. A major recent book, Questioning the Entrepreneurial State: Status-quo, Pitfalls, and the Need for Credible Innovation Policy (Springer, 2022), offers additional evidence of the failure of European industrial policy efforts. No amount of industrial policy planning and spending is going to be able to overcome a negative innovation culture that suffocates entrepreneurialism and investment out of the gates.

These findings have lessons for policymakers in the United States, too, especially with President Biden and even many Republicans now calling for heavy-handed top-down regulation of digital technology companies. Basically, “President Biden Wants America to Become Europe on Tech Regulation,” I argued in a recent R Street Institute blog post. In a letter to the Wall Street Journal, I responded to recent opeds by both President Biden and former Trump Administration Attorney General William Barr in which they both advocated regulations that would take us down the disastrous path that the European Union has already charted.

“The only thing Europe exports now on the digital-technology front is regulation,” I noted in my response, and that makes it all the more mind-boggling that Biden and Barr want to go down that same path. “Overregulation by EU bureaucrats led Europe’s best entrepreneurs and investors to flee to the U.S. or elsewhere in search of the freedom to innovate.” This is the wrong innovation culture for the United States if we hope to be a leader in the Computational Revolution that is unfolding — and match expanding efforts by the Chinese to top us at it.

In closing, policymakers should never lose sight of the most fundamental lesson of innovation policy, which can be stated quite simply: You only get as much innovation as you allow to begin with. If the public policy defaults are all set to be maximally restrictive and limit entrepreneurialism and experimentation by design, then it should be no surprise when the country or continent fails to generate meaningful innovation, investment, new companies, and global competitive advantage. The European model is no model for America.

Additional reading:

]]> https://techliberation.com/2023/02/09/studies-document-growing-cost-of-eu-privacy-regulations/feed/ 2 77086 Quick Thoughts on Biden’s Tech-Bashing in the State of the Union https://techliberation.com/2023/02/07/quick-thoughts-on-bidens-tech-bashing-in-the-state-of-the-union/ https://techliberation.com/2023/02/07/quick-thoughts-on-bidens-tech-bashing-in-the-state-of-the-union/#respond Wed, 08 Feb 2023 03:43:49 +0000 https://techliberation.com/?p=77080

  • President Biden began his 2023 State of the Union remarks by saying America is defined by possibilities. Correct! Unfortunately, his tech-bashing will undermine those possibilities by discouraging technological innovation & online freedom in the United States.
  • America became THE global leader on digital tech because we rejected heavy-handed controls on innovators & speech. We shouldn’t return to the broken model of the past by layering on red tape, economic controls & speech restrictions.
  • What has the tech economy done for us lately? Here is a look at the value added to the U.S. economy by the digital sector from 2005-2021. That’s $2.4 TRILLION (with a T) added in 2021. These are astonishing numbers.
  • FACT: According to the BEA, in 2021, “the U.S. digital economy accounted for $3.70 trillion of gross output, $2.41 trillion of value added (translating to 10.3 % of U.S. GDP), $1.24 trillion of compensation + 8.0 million jobs.”

In 2021…

  • $3.70 trillion of gross output
  • $2.41 trillion of value added (=10.3% percent GDP)
  • $1.24 trillion of compensation
  • 8.0 million jobs

FACT: globally, 49 of the top 100 digital tech firms with most employees are US companies. Here they are. Smart public policy made this list possible.

  • FACT: 18 of the world’s Top 25 tech companies by Market Cap are US-based firms.
  • It’d be a huge mistake to adopt Europe’s approach to tech regulation. As I noted recently in the Wall Street Journal, “The only thing Europe exports now on the digital-technology front is regulation.”  Yet, Biden would have us import the EU model to our shores.
  • My R Street colleague Josh Withrow has also noted how, “the EU’s approach appears to be, in sum, ‘If you can’t innovate, regulate.’” America should not be following the disastrous regulatory path of the European Union on digital technology policy.
  • On antitrust regulation, here is a study by my R Street colleague Wayne Brough on the dangerous approach that the Biden administration wants, which would swing a wrecking ball through the tech economy. We have to avoid this.
  • It is particularly important that the US not follow the EU’s lead on artificial intelligence regulation at a time when we are in heated competition w China on the AI front as I noted here.
  • American tech innovators flourished thanks to a positive innovation culture rooted in permissionless innovation & policies like Section 230, which allowed American firms to become global powerhouses. And we’ve moved from a world of information scarcity to one of information abundance. Let’s keep it that way.
]]> https://techliberation.com/2023/02/07/quick-thoughts-on-bidens-tech-bashing-in-the-state-of-the-union/feed/ 0 77080 AI Policy Research: My Year in Review https://techliberation.com/2022/12/26/ai-policy-research-my-year-in-review/ https://techliberation.com/2022/12/26/ai-policy-research-my-year-in-review/#comments Mon, 26 Dec 2022 20:07:40 +0000 https://techliberation.com/?p=77073

I spent much of 2022 writing about the growing policy debate over artificial intelligence, machine learning, robotics, and the Computational Revolution more generally. Here are some of the major highlights of my work on this front.

All these essays + dozens more can be found on my: “Running List of My Research on AI, ML & Robotics Policy.” I have several lengthy studies and many shorter essays coming in the first half of 2023.

Finally, here is a Federalist Society podcast discussion about AI policy hosted by Jennifer Huddleston in which Hodan Omaar of ITIF and I offer a big picture overview of where things are headed next.

]]> https://techliberation.com/2022/12/26/ai-policy-research-my-year-in-review/feed/ 2 77073 Gonzalez v Google, Section 230 & the Future of Permissionless Innovation https://techliberation.com/2022/12/09/gonzalez-v-google-section-230-the-future-of-permissionless-innovation/ https://techliberation.com/2022/12/09/gonzalez-v-google-section-230-the-future-of-permissionless-innovation/#comments Fri, 09 Dec 2022 13:15:15 +0000 https://techliberation.com/?p=77066

Over at Discourse magazine this week, my R Street colleague Jonathan Cannon and I have posted a new essay on how it has been “Quite a Fall for Digital Tech.” We mean that both in the sense that the last few months have witnessed serious market turmoil for some of America’s leading tech companies, but also that the political situation for digital tech more generally has become perilous. Plenty of people on the Left and the Right now want a pound of flesh from the info-tech sector, and the starting cut at the body involves Section 230, the 1996 law that shields digital platforms from liability for content posted by third parties.

With the Supreme Court recently announcing it will hear Gonzalez v. Google, a case that could significantly narrow the scope of Section 230, the stakes have grown higher. It was already the case that federal and state lawmakers were looking to chip away at Sec. 230’s protections through an endless variety of regulatory measures. But if the Court guts Sec. 230 in Gonzalez, then it will really be open season on tech companies, as lawsuits will fly at every juncture whenever someone does not like a particular content moderation decision. Cannon and I note in our new essay that,

if the court moves to weaken liability protections for digital platforms, the ramifications will be profoundly negative. While many critics today complain that the law’s liability protections have been too generous, the reality is that Section 230 has been the legal linchpin supporting the permissionless innovation model that fueled America’s commanding lead in the digital information revolution. Thanks to the law, digital entrepreneurs have been free to launch bold new ideas without fear of punishing lawsuits or regulatory shenanigans. This has boosted economic growth and dramatically broadened consumer information and communications options.

Many critics of Sec. 230 claim that reforms are needed to “rein in Big Tech.” But, ironically, gutting Sec. 230 would probably only make big tech companies even bigger because the smaller players in the market would struggle to deal with the mountains of regulations and lawsuits that would come about in its absence. Cannon and I continue on to explore what it means for the next generation of online innovators if these court cases go badly and Section 230 is scaled back or gutted:

Section 230 has been a legal cornerstone of the entire ecosystem. All the large-scale platforms we depend on for our online experience would never have gotten off the ground without its protection. […] More importantly, these platforms have relied on being able to host third-party content without fear of opening a Pandora’s box of private litigation and endless challenges from governments. By removing these protections, platforms will be forced to significantly increase their moderation practices to reduce risk of suits from zealous litigants. Besides the chilling effect this will have on speech, it also will put up a cost-prohibitive barrier for smaller entrants who lack the resources to have an army of content moderators to find and eliminate undesirable content.

The broader effect on market dynamism and the nation’s technological competitiveness will be profound as permissionless innovation is replaced by mountains of top-down permission slips. “If America’s digital sector gets kneecapped by the Supreme Court, or if new regulations or legislative proposals scale back Section 230 protections, it will be significantly more difficult for U.S. firms to continue to lead in the development and commercialization of new technologies,” we conclude.

Jump over to Discourse to read the entire piece.

]]> https://techliberation.com/2022/12/09/gonzalez-v-google-section-230-the-future-of-permissionless-innovation/feed/ 2 77066 Tech Regulation Will Increasingly Be Driven Through the Prism of “Algorithmic Fairness” https://techliberation.com/2022/11/06/tech-regulation-will-increasingly-be-driven-through-the-prism-of-algorithmic-fairness/ https://techliberation.com/2022/11/06/tech-regulation-will-increasingly-be-driven-through-the-prism-of-algorithmic-fairness/#comments Sun, 06 Nov 2022 18:51:21 +0000 https://techliberation.com/?p=77056

We are entering a new era for technology policy in which many pundits and policymakers will use “algorithmic fairness” as a universal Get Out of Jail Free card when they push for new regulations on digital speech and innovation. Proposals to regulate things like “online safety,” “hate speech,” “disinformation,” and “bias” among other things often raise thorny definitional questions because of their highly subjective nature. In the United States, efforts by government to control these things will often trigger judicial scrutiny, too, because restraints on speech violate the First Amendment. Proponents of prior restraint or even ex post punishments understand this reality and want to get around it. Thus, in an effort to avoid constitutional scrutiny and lengthy court battles, they are engaged in a rebranding effort and seeking to push their regulatory agendas through a techno-panicky prism of “algorithmic fairness” or “algorithmic justice.”

Hey, who could possibly be against FAIRNESS and JUSTICE? Of course, the devil is always in the details as Neil Chilson and I discuss in our new paper for the The Federalist Society and Regulatory Transparency Project on, “The Coming Onslaught of ‘Algorithmic Fairness’ Regulations.” We document how federal and state policymakers from both parties are currently considering a variety of new mandates for artificial intelligence (AI), machine learning, and automated systems that, if imposed, “would thunder through our economy with one of the most significant expansions of economic and social regulation – and the power of the administrative state – in recent history.”

We note how, at the federal level, bills are being floated with titles like the “Algorithmic Justice and Online Platform Transparency Act” and the “Protecting Americans from Dangerous Algorithms Act,” which would introduce far-reaching regulations requiring AI innovators to reveal more about how their algorithms work or even hold them liable if their algorithms are thought to be amplifying hateful or extremist content. Other proposed measures like the “Platform Accountability and Consumer Transparency Act” and the “Online Consumer Protection Act” would demand greater algorithmic transparency as it relates to social media content moderation policies and procedures. Finally, measures like the “Kids Online Safety Act” would require audits of algorithmic recommendation systems that supposed targeted or harmed children. Algorithmic regulation is also creeping into proposed privacy regulations, such as the “American Data Protection and Privacy Act of 2022.”

And then there are all the state laws–many of which have been pushed by conservatives–that would mandate “algorithmic transparency” for social media content moderation in the name of countering supposed viewpoint bias. Bills in Florida and Texas take this approach. Meanwhile, conservatives in Congress Senator Josh Hawley’s (R-MO) push for bills like the “Ending Support for Internet Censorship Act” that requires large tech companies undergo external audits proving that their algorithms and content-moderation techniques are politically unbiased. It’s an open invitation to regulators and trial lawyers to massively regulate technology and speech under the guise of “algorithmic fairness.” Countless left-leaning law professors and European officials have already proposed a comprehensive algorithmic audit apparatus to regulate innovators in every sector.

It’s the rise of the Code Cops. If we continue down this path, it ends with a complete rejection of the permissionless innovation ethos that made America’s information technology sector a global powerhouse. Instead, we’ll be stuck with the very worst type of “Mother, May I” precautionary principle-based regulatory regime that will be imposing the equivalent of occupational licensing requirements for coders.

If code is speech, algorithms are as well. Defenders of innovation freedom need to step up and prepare for the fight to come. [See my earlier essay, “AI Eats the World: Preparing for the Computational Revolution and the Policy Debates Ahead.”] Chilson and I outline the broad contours of the battle for freedom of speech and the freedom to innovation that is brewing. It will be the most important technology policy issue of the next ten years. I hope you take the time to read our new essay and understand why. And below you will find a few dozen more essay on the same topic if you’d like to dig even deeper.

Additional Reading :

 

]]> https://techliberation.com/2022/11/06/tech-regulation-will-increasingly-be-driven-through-the-prism-of-algorithmic-fairness/feed/ 4 77056 Dispatch from JMI’s “Tech & Innovation Summit” Panel on Progress Studies https://techliberation.com/2022/09/16/dispatch-from-jmis-tech-innovation-summit-panel-on-progress-studies/ https://techliberation.com/2022/09/16/dispatch-from-jmis-tech-innovation-summit-panel-on-progress-studies/#comments Fri, 16 Sep 2022 13:59:12 +0000 https://techliberation.com/?p=77044

It was my pleasure this week to participate in a panel discussion about the future of innovation policy at the James Madison Institute’s 2022 Tech and Innovation Summit in Coral Gables, FL. Our conversation focused on the future of Progress Studies, which is one of my favorite topics. We were asked to discuss five major questions and below I have summarized some of my answers to them, plus some other thoughts I had about what I heard at the conference from others.

  1. What is progress studies and why is it so needed today?

In a sense, Progress Studies is nothing new. Progress studies goes back at least to the days of Adam Smith and plenty of important scholars have been thinking about it ever since. Those scholars and policy advocates have long been engaged in trying to figure out what’s the secret sauce that powers economic growth and human prosperity. It’s just that we didn’t call that Progress Studies in the old days.

The reason Progress Studies is important is because technological innovation has been shown to be the fundamental driver in improvements in human well-being over time.  When we can move the needle on progress, it helps individuals extend and improve their lives, incomes, and happiness. By extension, progress helps us live lives of our choosing. As Hans Rosling brilliantly argued, the goal of expanding innovation opportunities and raising incomes “is not just bigger piles of money” or more leisure time. “The ultimate goal is to have the freedom to do what we want.”

  1. What don’t policymakers get about progress?

Policymakers often fail to appreciate the connection between innovation policy defaults and actual real-world innovation outcomes. Here is the biggest no-duh statement ever uttered: If you discourage innovation by default, you’ll get a lot less of it. In other words, incentives matters if you hope to create a positive innovation culture. Innovation culture refers to the various social and political attitudes, policies and entrepreneurial activities that, taken together, influence the innovative capacity of a particular region.

Thus, when policymakers make the Precautionary Principle the legal default for innovative activities, it means that government has put a red light in front of entrepreneurs and treated them and their innovations as guilty until proven innocent.  That’s a sure-fire recipe for stagnation.

The better approach is to make Permissionless Innovation our policy default and treat entrepreneurs and innovations as innocent until proven guilty. When our policy defaults offer entrepreneurs more green lights instead of red ones, it encourages more experimentation with new and better ways of doing things. In turn, this spurs business formation, job creation, new industries and products, and broad-based economic growth.

But policymakers consistently ignore this fundamental reality about the connection between policy and progress.

  1. Can you think of any states or governments that are doing a good job of putting the insights of progress studies into practice?

This summer, I co-authored an essay about, “How Arizona Is Getting Innovation Culture Right,” and highlighted the many important reforms undertaken over the past eight years by Gov. Doug Ducey and the Arizona Legislature. Arizona has advanced several reforms that have helped the state get its innovation culture right both broadly and narrowly. Broadly speaking, the state took steps to minimize red tape burdens and streamline permitting process and occupational licensing mandates. They also promoted “right to earn a living” and “right to try” initiatives to broaden worker and patient opportunities.

In terms of more targeted reforms, Arizona took steps to clear the way for greater broadband rollout and encouraged experimentation with commercial drones and driverless cars. The state also helped pioneer the use of “regulatory sandboxes,” which grant innovators a temporary safe space free of excessive regulatory burdens so they can experiment with new products and services.

And then there’s the city of Miami. At the JMI event, Miami Mayor Francis Suarez delivered a keynote address and he identified 3 keys to attracting talent and building opportunity: (1) Keep taxes low, (2) keep people safe, and (3) focus on innovation. He’s following that script and making Miami a hotbed of entrepreneurial opportunity.

Mayor Suarez spoke of how he is embracing emerging technologies like blockchain to compete with the traditional geographic Goliaths of tech, like San Francisco and New York. There’s been a massive inflow of companies and investors as a result. The city has become #1 in tech job growth and the inflow of tech entrepreneurs. “It turns out that if you welcome people… they come,” he said. “They want to migrate to places that are on the cutting edge of technology” and find “pathways to prosperity.”

Miami and Arizona offer great models that other cities and states could follow if they hope to improve their own innovation culture.

  1. What is the difference between progress studies and industrial organization, or industrial policy, or “government planning, but for innovation”?

Many policymakers foolishly believe there exists a precise technocratic cocktail that can immediately unlock innovation through highly targeted interventions and spending initiatives. In reality, achieving consistent growth and prosperity requires more than Big Government gimmicks. It’s a long game.

Many politicians and pundits are often fond of using machine-like metaphors and insisting that they have the ability to “fine-tune” innovative outcomes or “dial-in” economic development according to a precise formula. This is how we end up trillions in debt without much to show for it. Most recently, we’ve witnessed an “orgy of spending” on industrial policy schemes at the federal level.

The better metaphor for thinking about a nation’s innovation culture might be a plant or garden. Two of the great Progress Studies thinkers are F. A. Hayek and Joel Mokyr. Hayek once suggested that policymakers should aim to “cultivate a growth by providing the appropriate environment, in the manner in which the gardener does this for his plants.”  And Mokyr has argued that technological innovation and economic progress must be viewed as “a fragile and vulnerable plant, whose flourishing is not only dependent on the appropriate surroundings and climate, but whose life is almost always short. It is highly sensitive to the social and economic environment and can easily be arrested by relatively small external changes.”

Thus, the technocratic industrial policy mindset is always looking for “sexy” initiatives that capture a lot of short-term media attention, but typically fail to produce meaningful innovations or lasting growth. What’s more important to long-term prosperity is that policymakers get the “boring” stuff right.

The building blocks of the “boring” general approach economic development is a mix of broadly applicable tax, spending, regulatory and legal rules that help create a stable innovation ecosystem. Again, it’s like Mayor Suarez’s 3-prong approach of low taxes, safe communities, and a welcoming embrace of entrepreneurialism. That’s the secret sauce that fuels long-term progress and a sustainable prosperity.

  1. Is there a disconnect between the theories of progress and the practice – in other words, is it a problem of governance forms?

Indeed, I already mentioned the difference between the Precautionary Principle and Permissionless Innovation and it’s always interesting to me how my scholars ignore the importance of these governance forms when thinking about how to advance progress. There exists an unfortunate tendency among many to either ignore or repeat the mistakes of the past. Having made significant economic and societal gains thanks to past technological progress, many pundits and policymakers come to take much of it for granted. Thus, Progress Studies requires a process of constant re-education to remind each new generation of what helped raise our living standards so dramatically over the past two centuries.

The dramatic growth in incomes, life expectancy, and human welfare were not the product of sheer luck but of important policy choices. The freedom to think, to innovate, and to trade are the three freedoms that gave us our modern riches. If our governance forms limit those foundational freedoms, our current welfare and future prosperity will suffer. This is the great lesson of Progress Studies.

Additional Reading from Adam Thierer on Progress Studies

 

]]> https://techliberation.com/2022/09/16/dispatch-from-jmis-tech-innovation-summit-panel-on-progress-studies/feed/ 3 77044 AI Eats the World: Preparing for the Computational Revolution and the Policy Debates Ahead https://techliberation.com/2022/09/12/ai-eats-the-world-preparing-for-the-computational-revolution-and-the-policy-debates-ahead/ https://techliberation.com/2022/09/12/ai-eats-the-world-preparing-for-the-computational-revolution-and-the-policy-debates-ahead/#comments Mon, 12 Sep 2022 23:52:26 +0000 https://techliberation.com/?p=77039

[Cross-posted from Medium.]

The Coming Computational Revolution

Thomas Edison once spoke of how electricity was a “field of fields.” This is even more true of AI, which is ready to bring about a sweeping technological revolution. In Carlota Perez’s influential 2009 paper on “Technological Revolutions and Techno-economic Paradigms,” she defined a technological revolution “as a set of interrelated radical breakthroughs, forming a major constellation of interdependent technologies; a cluster of clusters or a system of systems.” To be considered a legitimate technological revolution, Perez argued, the technology or technological process must be “opening a vast innovation opportunity space and providing a new set of associated generic technologies, infrastructures and organisational principles that can significantly increase the efficiency and effectiveness of all industries and activities.” In other words, she concluded, the technology must have “the power to bring about a transformation across the board.”

Expanding Our Skillset

Thus, AI (and AI policy) is multi-dimensional, amorphous, and ever-changing. It has many layers and complexities. This will require public policy analysts and institutions to reorient their focus and develop new capabilities.

Mapping the AI Policy Terrain: Broad vs. Narrow

Beyond talent development, the other major challenge is issue coverage. How can we cover all the AI policy bases? There are two general categories of AI concerns, and supporters of free markets need to be prepared to engage on both battlefields.

Confronting the Formidable Resistance to Change

Finally, free-market analysts and organizations must prepare to defend the general concept of progress through technological change as AI becomes a central social, economic, and legal battleground — both domestically and globally. Every technological revolution involves major social and economic disruptions and gives rise to intense efforts to defend the status quo and block progress. As Perez concludes, “the profound and wide-ranging changes made possible by each technological revolution and its techno-economic paradigm are not easily assimilated; they give rise to intense resistance.”

]]> https://techliberation.com/2022/09/12/ai-eats-the-world-preparing-for-the-computational-revolution-and-the-policy-debates-ahead/feed/ 3 77039 Why the Endless Techno-Apocalyptica in Modern Sci-Fi? https://techliberation.com/2022/09/02/why-the-endless-techno-apocalyptica-in-modern-sci-fi/ https://techliberation.com/2022/09/02/why-the-endless-techno-apocalyptica-in-modern-sci-fi/#comments Fri, 02 Sep 2022 15:06:06 +0000 https://techliberation.com/?p=77033

James Pethokousis of AEI interviews me about the current miserable state of modern science fiction, which is just dripping with dystopian dread in every movie, show, and book plot. How does all the techno-apocalyptica affect societal and political attitudes about innovation broadly and emerging technologies in particular. Our discussion builds on my recent a recent Discourse article, “How Science Fiction Dystopianism Shapes the Debate over AI & Robotics.” [Pasted down below.] Swing on over to Jim’s “Faster, Please” newsletter and hear what Jim and I have to say. And, for a bonus question, Jim asked me is we doing a good job of inspiring kids to have a sense of wonder and to take risks. I have some serious concerns that we are falling short on that front.

How Science Fiction Dystopianism Shapes the Debate over AI & Robotics

[Originally ran on Discourse on July 26, 2022.]

George Jetson will be born this year. We don’t know the exact date of this fictional cartoon character’s birth, but thanks to some skillful Hanna-Barbera hermeneutics the consensus seems to be sometime in 2022.

In the same episode that we learn George’s approximate age, we’re also told the good news that his life expectancy in the future is 150 years old. It was one of the many ways The Jestons, though a cartoon for children, depicted a better future for humanity thanks to exciting innovations. Another was a helpful robot named Rosie, along with a host of other automated technologies—including a flying car—that made George and his family’s life easier.

 

Most fictional portrayals of technology today are not as optimistic as  The Jetsons, however. Indeed, public and political conceptions about artificial intelligence (AI) and robotics in particular are being strongly shaped by the relentless dystopianism of modern science fiction novels, movies and television shows. And we are worse off for it.

AI, machine learning, robotics and the power of computational science hold the potential to drive explosive economic growth and profoundly transform a diverse array of sectors, while providing humanity with countless technological improvements in medicine and healthcare, financial services, transportation, retail, agriculture, entertainment, energy, aviation, the automotive industry and many others. Indeed, these technologies are already deeply embedded in these and other industries and making a huge difference.

But that progress could be slowed and in many cases even halted if public policy is shaped by a precautionary-principle-based mindset that imposes heavy-handed regulation based on hypothetical worst-case scenarios. Unfortunately, the persistent dystopianism found in science fiction portrayals of AI and robotics conditions the ground for public policy debates, while also directing attention away from some of the more real and immediate issues surrounding these technologies.

Incessant Dystopianism Untethered from Reality

In his recent book Robots, Penn State business professor John Jordan observes how over the last century “science fiction set the boundaries of the conceptual playing field before the engineers did.” Pointing to the plethora of literature and film that depicts robots, he notes: “No technology has ever been so widely described and explored before its commercial introduction.” Not the internet, cell phones, atomic energy or any others.

Indeed, public conceptions of these technologies, and even the very vocabulary of the field, has been shaped heavily by sci-fi plots beginning a hundred years ago with the 1920 play  R.U.R. (Rossum’s Universal Robots), which gave us the term “robot,” and Fritz Lang’s 1927 silent film Metropolis, with its memorable Maschinenmensch, or “machine-human.” There has been a deep and rich imagination surrounding AI and robotics since then, but it has tended to be mostly negative and has grown more hostile over time.

The result has been a public and policy dialogue about AI and robotics that is focused on an endless parade of horribles about these technologies. Not surprisingly, popular culture also affects journalistic framings of AI and robotics. Headlines breathlessly scream of how “Robots May Shatter the Global Economic Order Within a Decade,” but only if we’re not dead already because… “If Robots Kill Us, It’s Because It’s Their Job.”

Dark depictions of AI and robotics are ever-present in popular modern sci-fi movies and television shows. A short list includes:  2001: A Space Odyssey, Avengers: Age of Ultron, Battlestar Galactica (both the 1978 original and the 2004 reboot), Black Mirror, Blade Runner, Ex Machina, Her, The Matrix, Robocop, The Stepford Wives, Terminator, Transcendence, Tron, WALL-E, Wargames and Westworld, among countless others. The least nefarious plots among these films and television shows rest on the idea that AI and robotics are going to drive us to a life of distraction, addiction or sloth. In more extreme cases, we’re warned about a future in which we are either going to be enslaved or destroyed by our new robotic or algorithmic overlords.

Don’t get me wrong; the movies and shows on the above list are some of my favorites.  2001 and Blade Runner are both in my top 5 all-time flicks, and the reboot of Battlestar is one of my favorite TV shows. The plots of all these movies and shows are terrifically entertaining and raise many interesting issues that make for fun discussions.

But they are not representative of reality. In fact, the vast majority of computer scientists and academic experts on AI and robotics agree that claims about machine “superintelligence” are wildly overplayed and that there is no possibility of machines gaining human-equivalent knowledge any time soon—or perhaps ever. “In any ranking of near-term worries about AI, superintelligence should be far down the list,” argues Melanie Mitchell, author of Artificial Intelligence: A Guide for Thinking Humans.

Contra the  Terminator-esque nightmares envisioned in so many sci-fi plots, MIT roboticist Rodney Brooks says that “fears of runaway AI systems either conquering humans or making them irrelevant aren’t even remotely well grounded.” John Jordan agrees, noting: “The fear and uncertainty generated by fictional representations far exceed human reactions to real robots, which are often reported to be ‘underwhelming.’”

The same is true for AI more generally. “A close inspection of AI reveals an embarrassing gap between actual progress by computer scientists working on AI and the futuristic visions they and others like to describe,” says Erik Larson, author of, The Myth of Artificial Intelligence: Why Computers Can’t Think the Way We Do. Larson refers to this extreme thinking about superintelligent AI as “technological kitsch,” or exaggerated sentimentality and melodrama that is untethered from reality. Yet, the public imagination remains captivated by tales of impending doom.

Seeding the Ground with Misery and Misguided Policy

But isn’t it all just harmless fun? After all, it’s just make believe. Moreover, can’t science fiction—no matter how full of techno-misery—help us think through morally weighty issues and potential ethical conundrums involving AI and robotics?

Yes and no. Titillating fiction has always had a cathartic element to it and helped us cope with the unknown and mysterious. Most historians believe it was Aristotle in his Poetics who first used the term katharsis when discussing how Greek tragedies helped the audience “through pity and fear effecting the proper purgation of these emotions.”

But are modern science fiction depictions of AI and robotics helping us cope with technological change, or instead just stoking a constant fear of it? Modern sci-fi isn’t so much purging negative emotion about the topic at hand as it is endlessly adding to the sense of dread surrounding these technologies. What are the societal and political ramifications of a cultural frame of reference that suggests an entire new class of computational technologies will undermine rather than enrich our human experiences and, possibly, our very existence?

The New Yorker’s Jill Lepore says we live in “A Golden Age for Dystopian Fiction,” but she worries that this body of work “cannot imagine a better future, and it doesn’t ask anyone to bother to make one.” She argues this “fiction of helplessness and hopelessness” instead “nurses grievances and indulges resentments” and that “[i]ts only admonition is: Despair more.” Lapore goes so far as to claim that, because “the radical pessimism of an unremitting dystopianism” has appeal to many on both the left and right, it “has itself contributed to the unravelling of the liberal state and the weakening of a commitment to political pluralism.”

I’m not sure dystopian fiction is driving the unravelling of pluralism, but Lapore is on to something when she notes how a fiction rooted in misery about the future will likely have political consequences at some point.

Techno-panic Thinking Shapes Policy Discussions

The ultimate question is whether public policy toward new AI and robotic technologies will be shaped by this hyperpessimistic thinking in the form of precautionary principle regulation, which essentially treats innovations as “guilty until proven innocent” and seeks to intentionally slow or retard their development.

If the extreme fears surrounding AI and robotics  do inspire precautionary controls—as they already have in the European Union—then we need to ask how the preservation of the technological status quo could undermine human well-being by denying society important new life-enriching and life-saving goods and services. Technological stasis does not provide a safer or healthier society, but instead holds back our collective ability to innovate, prosper and better our lives in meaningful ways.

Louis Anslow, curator of  Pessimists Archive calls this “the Black Mirror fallacy,” referencing the British television show that has enjoyed great success peddling tales of impending techno-disasters. Anslow defines the fallacy as follows: “When new technologies are treated as much more threatening and risky than old technologies with proven risks/harms. When technological progress is seen as a bigger threat than technological stagnation.”

Anslow’s Pessimists Archive collects real-world case studies of how moral panic and techno-panics have accompanied the introduction of new inventions throughout history. He notes, “Science fiction has conditioned us to be hypervigilant about avoiding dystopias born of technological acceleration and totally indifferent to avoiding dystopias born of technological stagnation.”

Techno-panics can have real-world consequences when they come to influence policymaking. Robert Atkinson, president of the Information Technology & Innovation Foundation (ITIF), has documented the many ways that “the social and political commentary [about AI] has been hype, bordering on urban myth, and even apocalyptic.” The more these attitudes and arguments come to shape policy considerations, the more likely it is precautionary principle-based recommendations will drive AI and robotics policy, preemptively limiting their potential. ITIF has published a report documenting “Ten Ways the Precautionary Principle Undermines Progress in Artificial Intelligence,” identifying how it will slow algorithmic advances in key sectors.

Similarly, in his important recent book Where Is My Flying Car ?, scientist J. Storrs Hall documents how “regulation clobbered the learning curve” for many important technologies in the U.S. over the last half century, especially nuclear, nanotech and advanced aviation. Society lost out on many important innovations due to endless bureaucratic delays, often thanks to opposition from special interests, anti-innovation activists, overzealous trial lawyers and a hostile media. Hall explained how this also sent a powerful signal to talented young people who might have been considering careers in those sectors. Why go into a field demonized by so many and where your creative abilities will be hamstrung by precautionary constraints?

Disincentivizing Talent

Hall argues that in those crucial sectors, this sort of mass talent migration “took our best and brightest away from improving our lives,” and he warns that those who still hope to make a career in such fields should be prepared to be “misconstrued and misrepresented by activists, demonized by ignorant journalists, and strangled by regulation.”

Is this what the future holds for AI and robotics? Hopefully not, and America continues to generate world-class talent on this front today in a diverse array of businesses and university programs. But if the waves of negativism about AI and robotics persist, we shouldn’t be surprised if it results in a talent shift away from building these technologies and toward fields that instead look to restrict them.

For example, Hall documents how, following the sudden shift in public attitudes surrounding nuclear power 50 years ago, “interests, and career prospects, in nuclear physics imploded” and “major discoveries stopped coming.” Meanwhile, enrollment in law schools and other soft sciences typically critical of technological innovation enjoyed greater success. Nobody writes any sci-fi stories about what a disaster that development has been for innovation in the energy sphere, even though it is now abundantly clear how precautionary principle policies have undermined environment goals and human welfare, with major geopolitical consequences for many nations.

If America loses the talent race on the AI front, it has ramifications for global competitive advantage going forward, especially as China races to catch up. In a world of global innovation arbitrage, talent and venture capital will flow to wherever it is treated most hospitably. Demonizing AI and robotics won’t help recruit or retain the next generation of talent and investors America needs to remain on top.

Flipping the Script

Some folks have had enough of the relentless pessimism surrounding technology and progress in modern science fiction and are trying to do something to reverse it. In a 2011  Wired essay decrying the dangers of “Innovation Starvation,” the acclaimed novelist Neal Stephenson decried the fact that “the techno-optimism of the Golden Age of [science fiction] has given way to fiction written in a generally darker, more skeptical and ambiguous tone.” While good science fiction, “supplies a plausible, fully thought-out picture of an alternate reality in which some sort of compelling innovation has taken place,” Stephenson said modern sci-fi was almost entirely focused on its potential downsides.

To help reverse this trend, Stephenson worked with the Center for Science and the Imagination at Arizona State University to launch Project Hieroglyph, an effort to support authors willing to take a more optimistic view of the future. It yielded a 2014 book, Hieroglyph: Stories and Visions for a Better Future that included almost 20 contributors. Later, in 2018, The Verge launched the “Better Worlds” project to support 10 writers of “stories that inspire hope” about innovation and the future. “Contemporary science fiction often feels fixated on a sort of pessimism that peers into the world of tomorrow and sees the apocalypse looming more often than not,” said Verge culture editor Laura Hudson when announcing the project.

Unfortunately, these efforts have not captured much public attention and that’s hardly surprising. “Pessimism has always been big box office,” says science writer Matt Ridley, primary because it really is more entertaining. Even though many of great sci-fi writers of the past, including Isaac Asimov, Arthur C. Clarke, and Robert Heinlein, wrote positively about technology, they ultimately had more success selling stories with darker themes. It’s just the nature of things more generally, from the best of Greek tragedy to Shakespeare and on down the line. There’s a reason they’re still rebooting Beowulf all these years later, after all.

So, There’s Star Trek and What Else?

While technological innovation will never enjoy the respect it deserves for being the driving force behind human progress, one can at least hope that more pop culture treatments of it might give it a fair shake. When I ask crowds of people to name a popular movie or television show that includes mostly positive depictions of technology, Star Trek is usually the first (and sometimes the only) thing people mention. It’s true that, on balance, technology was treated as a positive force in the original series, although “V’Ger”—a defunct space probe that attains a level of consciousness—was the prime antagonist in Star Trek: The Motion Picture. Later, Star Trek: The Next Generation gave us the always helpful android Data, but also created the lasting mental image of the Borg, a terrifying race of cyborgs hell-bent on assimilating everyone into their hive mind.

The Borg provided some of The Next Generation’s most thrilling moments, but also created a new cultural meme, with tech critics often worrying about how today’s humans are being assimilated into the hive mind of modern information systems. Philosopher Michael Sacasas even coined the term “the Borg Complex,” to refer to a supposed tendency “exhibited by writers and pundits who explicitly assert or implicitly assume that resistance to technology is futile.” After years of a friendly back-and-forth with Sacasas, I felt compelled to even wrap up my book Permissionless Innovation with a warning to other techno-optimists not to fall prey to this deterministic trap when defending technological change. Regardless of where one falls on that issue, the fact that Sacasas and I were having a serious philosophical discussion premised on a famous TV plotline serves as another indication of how much science fiction shapes public and intellectual debate over progress and innovation.

And, truth be told, some movies know how to excite the senses without resorting to dystopianism.  Interstellar and The Martian are two recent examples that come to mind. Interestingly, space exploration technologies themselves usually get a fair shake in many sci-fi plots, often only to be undermined by onboard Ais or androids, as occurred not only in 2001 with the eerie HAL 9000, but also Alien.

There are some positive (and sometimes humorous) depictions of robots as in  Robot & Frank, or touching ones as in Bicentennial Man. Beyond The Jetsons, other cartoons like Iron Giant and Big Hero 6 offer more kindly visions of robots. KITT, a super-intelligent robot car, was Michael Knight’s dependable ally in NBC’s Knight Rider. And R2-D2 is always a friendly helper throughout the Star Wars franchise. But generally speaking, modern sci-fi continues to churn out far more negativism about AI and robotics.

What If We Took It All Seriously?

So long as the public and political imagination is spellbound by machine machinations that dystopian sci-fi produces, we’ll be at risk of being stuck with absurd debates that have no meaningful solution other than “Stop the clock!” or “Ban it all!” Are we really being assimilated into the Borg hive mind, or just buying time until a coming robopocalypse grinds us into dust (or dinner)?

If there was a kernel of truth to any of this, then we should adopt some of the extreme solutions, Nick Bostrom of Oxford suggests in his writing on these issues. Those radical steps include worldwide surveillance and enforcement mechanisms for scientists and researchers developing algorithmic and robotic systems, as well as some sort of global censorship of information about these capabilities to ensure the technology is not used by bad actors.

To Bostrom’s great credit, he is at least willing to tell us how far he’d go. Most of today’s tech critics prefer to just spread a gospel of gloom and doom and suggest  something must be done, without getting into the ugly details about what a global control regime for computational science and robotic engineering looks like. We should reject such extremist hypothesizing and understand that silly sci-fi plots, bombastic headlines and kooky academic writing should not be our baseline for serious discussions about the governance of artificial intelligence and robotics.

At the same time, we absolutely should consider what downsides any technology poses for individuals and society. And, yes, some precautions will be needed of a regulatory nature. But most of the problems envisioned by sci-fi writers are not what we should be concerned with. There are far more specific and nuanced problems AI and robotics confronts us with today that deserve more serious consideration and governance steps. How to program safer drones and driverless cars, improve the accuracy of algorithmic medical and financial technologies, and ensure better transparency for government uses of AI are all more mundane but very important issues that require reasoned discussion and balanced solutions today. Dystopian thinking gives us no roadmap to get there other than extreme solutions.

Imagining a Better Future

The way forward here is neither to indulge in apocalyptic fantasies nor pollyannaish techno-optimism, but to approach these technologies with reasoned risk analysis, sensible industry best practices, educational efforts and other agile governance steps. In a forthcoming book on flexible governance strategies for AI and robotics, I outline how these and other strategies are already being formulated to address real-world challenges in fields as diverse as driverless cars, drones, machine learning in medicine and much more.

A wide variety of ethical frameworks, offered by professional associations, academic groups and others, already exists to “bake in” best practices and align AI design with widely shared goals and values while also “keeping humans in the loop” at critical stages of the design process to ensure that they can continue to guide and occasionally realign those values and best practices as needed.

When things do go wrong, many existing remedies are available, including a wide variety of common law solutions (torts, class actions, contract law, etc.), recall authority possessed by many regulatory agencies, and various consumer protection policies and other existing laws. Moreover, the most effective solution to technological problems usually lies in more innovation, not less. It is only through constant trial and error that humanity discovers better  and safer ways of satisfying important wants and needs.

These are complicated and nuanced issues that demand tailored and iterative governance responses. But this should not be done using inflexible, innovation-limiting mandates. Concerns about AI dangers deserve serious consideration and appropriate governance steps to ensure that these systems are beneficial to society. However, there is an equally compelling public interest in ensuring that AI innovations are developed and made widely available to help improve human well-being across many dimensions.

So, enjoy your next dopamine hit of sci-fi hysteria—I know I will, too. But don’t let that be your guide to the world that awaits us. Even if most sci-fi writers can’t imagine a better future, the rest of us can.

]]> https://techliberation.com/2022/09/02/why-the-endless-techno-apocalyptica-in-modern-sci-fi/feed/ 2 77033 AI Governance “on the Ground” vs “on the Books” https://techliberation.com/2022/08/24/ai-governance-on-the-ground-vs-on-the-books/ https://techliberation.com/2022/08/24/ai-governance-on-the-ground-vs-on-the-books/#respond Wed, 24 Aug 2022 15:14:56 +0000 https://techliberation.com/?p=77028

[Cross-posted from Medium]

There are two general types of technological governance that can be used to address challenges associated with artificial intelligence (AI) and computational sciences more generally. We can think of these as “on the ground” (bottom-up, informal “soft law”) governance mechanisms versus “on the books” (top-down, formal “hard law”) governance mechanisms.

Unfortunately, heated debates about the latter type of governance often divert attention from the many ways in which the former can (or already does) help us address many of the challenges associated with emerging technologies like AI, machine learning, and robotics. It is important that we think harder about how to optimize these decentralized soft law governance mechanisms today, especially as traditional hard law methods are increasingly strained by the relentless pace of technological change and ongoing dysfunctionalism in the legislative and regulatory arenas.

On the Grounds vs. On the Books Governance

Let’s unpack these “on the ground” and “on the books” notions a bit more. I am borrowing these descriptors from an important 2011 law review article by Kenneth A. Bamberger and Deirdre K. Mulligan, which explored the distinction between what they referred to as “Privacy on the Books and on the Ground.” They identified how privacy best practices were emerging in a decentralized fashion thanks to the activities of corporate privacy officers and privacy associations who helped formulate best practices for data collection and use.

The growth of privacy professional bodies and non­profit organizations — especially the International Association of Privacy Profession­als (IAPP) — helped better formalize privacy best practices by establishing and certifying internal champions to uphold key data-handling principles with organizations. By 2019, the IAPP had over 50,000 trained members globally, and its numbers keep swelling. Today, it is quite common to find Chief Privacy Officers throughout the corporate, governmental, and non-profit world.

These privacy professionals work together and in conjunction with a wide diversity of other players to “bake-in” widely-accepted information collection/ use practices within all these organizations. With the help of IAPP and other privacy advocates and academics, these professionals also look to constantly refine and improve their standards to account for changing circumstances and challenges in our fast-paced data economy. They also look to ensure that organizations live up to commitments they have made to the public or even governments to abide by various data-handling best practices.

Soft Law vs. Hard Law

These “on the ground” efforts have helped usher in a variety of corporate social responsibility best practices and provide a flexible governance model that can be a compliment to, or sometimes even a substitute for, formal “on the books” efforts. We can also think of this as the difference between soft law and hard law.

Soft law refers to agile, adaptable governance schemes for emerging technology that create substantive expectations and best practices for innovators without regulatory mandates. Soft law can take many forms, including guidelines, best practices, agency consultations & workshops, multistakeholder initiatives, and other experimental types of decentralized, non-binding commitments and efforts.

Soft law has become a bit of a gap-filler in the U.S. as hard law efforts fail for various reasons. The most obvious explanations for why the role of hard law governance has shrunk is that it’s just very hard for law to keep up with fast-moving technological developments today. This is known as the pacing problem. Many scholars have identified how the pacing problem gives rise to a “governance gap” or “competency trap” for policymakers because, just as quickly as they are coming to grips with new technological developments, other technologies are emerging quickly on their heels.

Think of modern technologies — especially informational and computational technologies — like a series of waves that come flowing in to shore faster and faster. As soon as one wave crests and then crashes down, another one comes right after it and soaks you again before you’ve had time to recover from the daze of the previous ones hitting you. In a world of combinatorial innovation, in which technologies build on top of one another in a symbiotic fashion, this process becomes self-reinforcing and relentless. For policymakers, this means that just when they’ve worked their way up one technological learning curve, the next wave hits and forces them to try to quickly learn about and prepare for the next one that has arrived. Lawmakers are often overwhelmed by this flood of technological change, making it harder and harder for policies to get put in place in a timely fashion — and equally hard to ensure that any new or even existing policies stay relevant as all this rapid-fire innovation continues.

Legislative dysfunctionalism doesn’t help. Congress has a hard time advancing bills on many issues, and technical matters often get pushed to the bottom of the priorities list. The end result is that Congress has increasingly become a non-actor on tech policy in the U.S. Most of the action lies elsewhere.

What’s Your Backup Plan?

This means there is a powerful pragmatic case for embracing soft law efforts that can at least provide us with some “on the ground” governance efforts and practices. Increasingly, soft law is filling the governance gap because hard law is failing for a variety of reasons already identified. Practically speaking, even if you are dead set on imposing a rigid, top-down, technocratic regulatory regime on any given sector or technology, you should at least have a backup plan in mind if you can’t accomplish that.

This is why privacy governance in the United States continues to depend heavily on such soft law efforts to fill the governance vacuum after years of failed attempts to enact a formal federal privacy law. While many academics and others continue to push for such an over-arching data handling law, bottom-up soft law efforts have played an important role in balancing privacy and innovation.

In a similar way, “on the ground” governance efforts are already flourishing for artificial intelligence and machine learning as policymakers continue to very slowly consider whether new hard law initiatives are wise or even possible. For example, congressional lawmakers have been considering a federal regulatory framework for driverless cars for the past several sessions of Congress. Many people in Congress and in academic circles agree that a federal framework is needed, if for no other reason than to preempt the much-dreaded specter of a patchwork of inconsistent state and local regulatory policies. With so much bipartisan agreement out there on driverless car legislation, it would seem like a federal bill would be a slam dunk. For that reason, year in and year out, people always predict: this is the year we’ll get driverless car legislation! And yet, it never happens due to a combination of special interest opposition from unions and trial lawyers, in addition to the pacing problem issue and Congress focusing its limited attention on other issues.

This is also already true for algorithmic regulation. We hear lots of calls to do something, but it remains unclear what that something is or whether it will get done any time soon. If we could not get a privacy bill through Congress after at least a dozen years of major efforts, chances are that broad-based AI regulation is going to be equally challenging.

Soft Law for AI is Exploding

Thus, soft law will likely fill the governance gap for AI. It already is. I’m working on a new book that documents the astonishing array of soft law mechanisms already in place or being developed to address various algorithmic concerns. I can’t seem to finish the book because there is just so much going on related to soft law governance efforts for algorithmic systems. As Mark Coeckelbergh noted in his recent book on AI Ethics, there’s been an “avalanche of​ initiatives and policy documents” around AI ethics and best practices in recent years. It is a bit overwhelming, but the good news is that there is a lot of consistency in these governance efforts.

To illustrate, a 2019 survey by a group of researchers based in Switzerland analyzed 84 AI ethical frameworks and found “a global convergence emerging around five ethical principles (transparency, justice and fairness, non-maleficence, responsibility and privacy).” A more recent 2021 meta-survey by a team of Arizona State University (ASU) legal scholars reviewed an astonishing 634 soft law AI programs that were formulated between 2016–2019. 36 percent of these efforts were initiated by governments, with the others being led by non-profits or private sector bodies. Echoing the findings from the Swiss researchers, the ASU report found widespread consensus among these soft law frameworks on values such as transparency and explainability, ethics/rights, security, and bias. This makes it clear that there is considerable consistency among ethical soft law frameworks in that most of them focus on a core set of values to embed within AI design. The UK-based Alan Turing Institute boils their list down to four “FAST Track Principles”: Fairness, Accountability, Sustainability, and Transparency.

The ASU scholars noted how ethical best practices for product design already influence developers today by creating powerful norms and expectations about responsible product design. “Once a soft law program is created, organizations may seek to enforce it by altering how their employees or representatives perform their duties through the creation and implementation of internal procedures,” they note. “Publicly committing to a course of action is a signal to society that generates expectations about an organization’s future actions.”

This is important because many major trade associations and individual companies have been formulating governance frameworks and ethical guidelines for AI development and use. For example, among large trade associations, the U.S. Chamber of Commerce, the Business Roundtable, the BSA | The Software Alliance, and ACT (The App Association) have all recently released major AI best practice guidelines. Notable corporate efforts to adopt guidelines for ethical AI practices include statements or frameworks by IBM, Intel, Google, Microsoft, Salesforce, SAP, and Sony, to just name a few. They are also creating internal champions to push AI ethics though either the appointment of Chief Ethical Officers, the creation of official departments, or both plus additional staff to guide the process of baking-in AI ethics by design.

Once again, there is remarkable consistency among these corporate statements in terms of the best practices and ethical guidelines they endorse. Each trade association or corporate set of guidelines align closely with the core values identified in the hundreds of other soft law frameworks that ASU scholars surveyed. These efforts go a long way toward helping to promote a culture of responsibility among leading AI innovators. We can think of this as the professionalization of AI best practices.

What Soft Law Critics Forget

Some will claim that “on the ground” soft law efforts are not enough, but they typically make two mistakes when saying so.

Their first mistake is thinking that hard law is practical or even optimal for fast-paced, highly mercurial AI and ML technologies. It’s not just that the pacing problem necessitates new thinking about governance. Critics fail to understand how hard law would likely significantly undermine algorithmic innovation because algorithmic systems can change by the minute and require a more agile and adaptive system of governance by their very nature.

This is a major focus of my book and I previously published a draft chapter from my book on “The Proper Governance Default for AI,” and another essay on “Why the Future of AI Will Not Be Invented in Europe.” These essays explain why a Precautionary Principle-oriented regulatory regime for algorithmic systems would stifle technological development, undermine entrepreneurialism, diminish competition and global competitive advantage, and even have a deleterious impact on our national security goals.

Traditional regulatory systems can be overly rigid, bureaucratic, inflexible, and slow to adapt to new realities. They focus on preemptive remedies that aim to predict the future, and future hypothetical problems that may not ever come about. Worse yet, administrative regulation generally preempts or prohibits the beneficial experiments that yield new and better ways of doing things. When innovators must seek special permission before they offer a new product or service, it raises the cost of starting a new venture and discourages activities that benefit society. We need to avoid that approach if we hope maximize the potential of AI-based technologies.

The second mistake that soft law critics make is that they fail to understand how many hard law mechanisms actually play a role in supporting soft law governance. AI applications already are regulated by a whole host of existing legal policies. If someone does something stupid or dangerous with AI systems, the Federal Trade Commission (FTC) has the power to address “unfair and deceptive practices” of any sort. And state Attorneys General and state consumer protection agencies also routinely address unfair practices and continue to advance their own privacy and data security policies, some of which are often more stringent than federal law.

Meanwhile, several existing regulatory agencies in the U.S. possess investigatory and recall authority that allows them to remove products from the market when certain unforeseen problems manifest themselves. For example, the National Highway Traffic Safety Administration (NHTSA), the Food & Drug Administration (FDA), and Consumer Product Safety Commission (CPSC) all possess broad recall authority that could be used to address risks that develop for many algorithmic or robotic systems. For example, NHTSA is currently using its investigative authority to evaluate Tesla’s claims about “full self-driving” technology and the agency has the power to take action against the company under existing regulations. Likewise, the FDA used its broad authority to crack down on genetic testing company 23andme many years ago. And CPSC and the FTC have broad authority to investigate claims made by innovators, and they’ve already used it. It’s not like our expansive regulatory state lacks considerable existing power to police new technology. If anything, the power of the administrative state is too broad and amorphous and it can be abused in certain instances.

Perhaps most importantly, our common law system can address other deficiencies with AI-based systems and applications using product defects law, torts, contract law, property law, and class action lawsuits. This is a better way of addressing risks compared to preemptive regulation of general-purpose AI technology because it at least allows the technologies to first develop and then see what actual problems manifest themselves. Better to treat innovators as innocent until proven guilty than the other way around.

There are other thorny issues that deserve serious policy consideration and perhaps even some new rules. But how risks are addressed matters deeply. Before we resort to heavy-handed, legalistic solutions for possible problems, we should exhaust all other potential remedies first.

In other words, “on the ground” soft law government mechanisms and ex post legal solutions should generally trump “ex ante (preemptive, precautionary) regulatory constraints. But we should look for ways to refine and improve soft law governance tools, perhaps through better voluntary certification and auditing regimes to hold developers to a high standard as it pertains to the important AI ethical practices we want them to uphold. This is the path forward to achieve responsible AI innovation without the heavy-handed baggage associated with more formalistic, inflexible, regulatory approaches that are ill-suited for complicated, rapidly-evolving computational and computing technologies.

___________________

Related Reading on AI & Robotics

]]> https://techliberation.com/2022/08/24/ai-governance-on-the-ground-vs-on-the-books/feed/ 0 77028 Running List of My Research on AI, ML & Robotics Policy https://techliberation.com/2022/07/29/running-list-of-my-research-on-ai-ml-robotics-policy/ https://techliberation.com/2022/07/29/running-list-of-my-research-on-ai-ml-robotics-policy/#respond Fri, 29 Jul 2022 12:51:54 +0000 https://techliberation.com/?p=77020

[last updated 4/3/2025 – Check my Medium page for latest posts]

This a running list of all the essays and reports I’ve already rolled out on the governance of artificial intelligence (AI), machine learning (ML), and robotics. Why have I decided to spend so much time on this issue? Because this will become the most important technological revolution of our lifetimes. Every segment of the economy will be touched in some fashion by AI, ML, robotics, and the power of computational science. It should be equally clear that public policy will be radically transformed along the way.

Eventually, all policy will involve AI policy and computational considerations. As AI “eats the world,” it eats the world of public policy along with it. The stakes here are profound for individuals, economies, and nations. As a result, AI policy will be the most important technology policy fight of the next decade, and perhaps next quarter century. Those who are passionate about the freedom to innovate need to prepare to meet the challenge as proposals to regulate AI proliferate.

There are many socio-technical concerns surrounding algorithmic systems that deserve serious consideration and appropriate governance steps to ensure that these systems are beneficial to society. However, there is an equally compelling public interest in ensuring that AI innovations are developed and made widely available to help improve human well-being across many dimensions. And that’s the case that I’ll be dedicating my life to making in coming years.

Here’s the list of what I’ve done so far. I will continue to update this as new material is released:

2025

2024

2023

2022

2021 (and earlier)

]]> https://techliberation.com/2022/07/29/running-list-of-my-research-on-ai-ml-robotics-policy/feed/ 0 77020 My Forthcoming Book on Artificial Intelligence & Robotics Policy https://techliberation.com/2022/07/22/my-forthcoming-book-on-artificial-intelligence-robotics-policy/ Fri, 22 Jul 2022 18:13:14 +0000 https://techliberation.com/?p=77014

I’m finishing up my next book, which is tentatively titled, “A Flexible Governance Framework for Artificial Intelligence.” I thought I’d offer a brief preview here in the hope of connecting with others who care about innovation in this space and are also interested in helping to address these policy issues going forward.

The goal of my book is to highlight the ways in which artificial intelligence (AI) machine learning (ML), robotics, and the power of computational science are set to transform the world—and the world of public policy—in profound ways. As with all my previous books and research products, my goal in this book includes both empirical and normative components. The first objective is to highlight the tensions between emerging technologies and the public policies that govern them. The second is to offer a defense of a specific governance stance toward emerging technologies intended to ensure we can enjoy the fruits of algorithmic innovation.

AI is a transformational technology that is general-purpose and dual-use. AI and ML also build on top of other important technologies—computing, microprocessors, the internet, high-speed broadband networks, and data storage/processing systems—and they will become the building blocks for a great many other innovations going forward. This means that, eventually, all policy will involve AI policy and computational considerations at some level. It will become the most important technology policy issue here and abroad going forward.

The global race for AI supremacy has important implications for competitive advantage and other geopolitical issues. This is why nations are focusing increasing attention on what they need to do to ensure they are prepared for this next major technological revolution. Public policy attitudes and defaults toward innovative activities will have an important influence on these outcomes.

In my book, I argue that, if the United States hopes to maintain a global leadership position in AI, ML, and robotics, public policy should be guided by two objectives:

  1. Maximize the potential for innovation, entrepreneurialism, investment, and worker opportunities by seeking to ensure that firms and other organizations are prepared to compete at a global scale for talent and capital and that the domestic workforce is properly prepared to meet the same global challenges.
  2. Develop a flexible governance framework to address various ethical concerns about AI development or use to ensure these technologies benefit humanity, but work to accomplish this goal without undermining the goals set forth in the first objective.

The book primarily addresses the second of these priorities because getting the governance framework for AI right significantly improves the chances of successfully accomplishing the first goal of ensuring that the United States remains a leading global AI innovator.

I do a deep dive into the many different governance challenges and policy proposals that are floating out there today—both domestically and internationally. The most contentious of these issues involved the so-called “socio-algorithmic” concerns that are driving calls for comprehensive regulation today. Those include the safety, security, privacy, and discrimination risks that AI/ML technologies could pose for individuals and society.

These concerns deserve serious consideration and appropriate governance steps to ensure that these systems are beneficial to society. However, there is an equally compelling public interest in ensuring that AI innovations are developed and made widely available to help improve human well-being across many dimensions.

Getting the balance right requires agile governance strategies and decentralized, polycentric approaches. There are many different values and complex trade-offs in play in these debates, all of which demand tailored responses. But this should not be done in an overly rigid way through complicated, inflexible, time-consuming regulatory mandates that preemptively curtail or completely constrain innovation opportunities. There’s no need to worry about the future if we can’t even build it first. AI innovation must not be treated as guilty until proven innocent.

The more agile and adaptive governance approach I outline in my book builds on the core principles typically recommended by those favoring precautionary principle-based regulation. That is, it is similarly focused on (1) “baking in” best practices and aligning AI design with widely-shared goals and values; and, (2) keeping humans “in the loop” at critical stages of this process to ensure that they can continue to guide and occasionally realign those values and best practices as needed. However, a decentralized governance approach to AI focuses on accomplishing these objectives in a more flexible, evolutionary fashion without the costly baggage associated with precautionary principle-based regulatory regimes.

The key to the decentralized approach is a diverse toolkit of so-called soft law governance solutions. Soft law refers to agile, adaptable governance schemes for emerging technology that create substantive expectations and best practices for innovators without regulatory mandates. Precautionary regulatory restraints will be necessary in some limited circumstances—particular for certain types of very serious existential risk—but most AI innovations should be treated as innocent until proven guilty.

When things do go wrong, many existing remedies are available, including a wide variety of common law solutions (torts, class actions, contract law, etc), recall authority possessed by many regulatory agencies, and various consumer protection policies and other existing laws. Moreover, the most effective solution to technological problems usually lies in more innovation, not less of it. It is only through constant trial and error that humanity discovers better and safer ways of satisfying important wants and needs.

The book has six chapters currently, although I am toying with adding back in two other chapters (on labor market issues and industrial policy proposals) that I finished but then cut to keep the theme of the book more tightly focused on social and ethical considerations surrounding AI and robotics.

Here are the summaries of the current six chapters in the manuscript:

  • Chapter 1: Understanding AI & Its Potential Benefits – Defining the nature and scope of artificial intelligence and its many components and related subsectors is complicated and this fact creates many governance challenges. But getting AI governance right is vital because these technologies offer individuals and society meaningful improvements in living standards across multiple dimensions.
  • Chapter 2: The Importance of Policy Defaults for Innovation Culture – Every technology policy debate involves a choice between two general defaults: the precautionary principle and the proactionary principle or “permissionless innovation.” Setting the initial legal default for AI technologies closer to the green light of permissionless innovation will enable greater entrepreneurialism, investment, and global competitiveness.
  • Chapter 3: Decentralized Governance for AI: A Framework – The process of embedding ethics in AI design is an ongoing, iterative process influenced by many forces and factors. There will be much trial and error when devising ethical guidelines for AI and hammering out better ways of keeping these systems aligned with human values. A top-down, one-size-fits-all regulatory framework for AI is unwise. A more decentralized, polycentric governance approach is needed—nationally and globally. [This chapter is the meat of the book and several derivative articles will be spun out of it beginning with a report on algorithmic auditing and AI impact assessments.]
  • Chapter 4: The US Governance Model for AI So Far – U.S. digital technology and ecommerce sectors have enjoyed a generally “permissionless” policy environment since the early days of the Internet, and this has greatly benefited our innovation and global competitiveness. While AI has thus far been governed by a similar “light-touch” approach, many academics and policymakers are now calling for aggressive regulation of AI rooted in a precautionary principle-oriented mindset, which threatens to derail a great deal of AI innovation.
  • Chapter 5: The European Regulatory Model & the Costs of Precaution by Default – Over the past quarter century, the European Union has taken a more aggressive approach to digital technology and data regulation, and is now advancing several new comprehensive regulatory frameworks, including an AI Act. The E.U.’s heavy-handed regulatory regime, which is rooted in the precautionary principle, discouraged innovation and investment across the continent in the past and will continue to do so as it grows to encompass AI technologies. The U.S. should reject this model and welcome European innovators looking to escape it.
  • Chapter 6: Existential Risks & Global Governance Issues around AI & Robotics – AI and robotics could give rise to certain global risks that warrant greater attention and action. But policymakers must be careful to define existential risk properly and understand how it is often the case that the most important solution to such risks is more technological innovation to overcome those problems. The greatest existential risk of all would be to block further technological innovation and scientific progress. Proposals to impose global bans or regulatory agencies are both unwise and unworkable. Other approaches, including soft law efforts, will continue to play a role in addressing global AI risks and concerns.

This book, which I hope to have out some time later this year, grows out of a large body of research I’ve done over the past decade. [Some of that work is listed down below.] AI, ML, robotics, and algorithmic policy issues will dominate my research focus and outputs over the next few years.

I look forward to doing my small part to help ensure that America builds on the track record of success it has enjoyed with the Internet, ecommerce, and digital technologies. Again, that stunning success story was built on wise policy choices that promoted a culture of creativity and innovation and rejected calls to hold on to past technological, economic, or legal status quos.

Will America rise to the challenge once again by adopting wise policies to facilitate the next great technological revolution? I’m ready for that fight. I hope you are, too, because it will be the most important technology policy battle of our lifetimes.

___________

Recent Essays & Papers on AI & Robotics Policy

]]> 77014 Event Video on Algorithmic Auditing and AI Impact Assessments https://techliberation.com/2022/07/13/event-video-on-algorithmic-auditing-and-ai-impact-assessments/ https://techliberation.com/2022/07/13/event-video-on-algorithmic-auditing-and-ai-impact-assessments/#comments Wed, 13 Jul 2022 18:10:03 +0000 https://techliberation.com/?p=77008

Upsides:

  • Audits and impact assessments can help ensure organizations live up their promises as it pertains to “baking in” ethical best practices (on issues like safety, security, privacy, and non-discrimination).
  • Audits and impact assessments are already utilized in other fields to address safety practices, financial accountability, labor practices and human rights issues, supply chain practices, and various environmental concerns.
  • Internal auditing / Institute of Internal Auditors (IIA) efforts could expand to include AI risks
  • Eventually, more and more organizations will expand their internal auditing efforts to incorporate AI risks because it makes good business sense to stay on top of these issues and avoid liability, negative publicity, or other customer backlash.
  • the International Association of Privacy Professionals (IAPP) trains and certifies privacy professionals through formal credentialing programs, supplemented by regular meetings, annual awards, and a variety of outreach and educational initiatives.
  • We should use similar model for AI and start by supplementing Chief Privacy Officers with Chief Ethical Officers.
  • This is how we formalize the ethical frameworks and best practices that have been formulated by various professional associations such as IEEE, ISO, ACM and others.
  • OECD — Framework for the Classification of AI Systems with the twin goals of helping “to develop a common framework for reporting about AI incidents that facilitates global consistency and interoperability in incident reporting,” and advancing “related work on mitigation, compliance and enforcement along the AI system lifecycle, including as it pertains to corporate governance.”
  • NIST — AI Risk Management Framework “to better manage risks to individuals, organizations, and society associated with artificial intelligence.”
  • These frameworks being developed through a consensus-driven, open, transparent, and collaborative process. Not through top-down regulation.
  • Many AI developers and business groups have endorsed the use of such audits and assessments. BSA|The Software Alliance has said that, “By establishing a process for personnel to document key design choices and their underlying rationale, impact assessments enable organizations that develop or deploy high-risk AI to identify and mitigate risks that can emerge throughout a system’s lifecycle.”
  • Developers can still be held accountable for violations of certain ethical norms and bast practices both through private and potentially even through formal sanctions by consumer protection agencies (Federal Trade Commission / comparable state offices / by state AGs).
  • EqualAI / WEF — “Badge Program for Responsible AI Governance”
  • field of algorithmic consulting continues to expand (ex: O’Neil Risk Consulting)

Downsides:

  • constitutes a harm or impact in any given context will often be a contentious matter.
  • Auditing algorithms is nothing like auditing an accounting ledger, where the numbers either add up or they don’t.
  • With algorithms there are no binary metrics that can quantify the correct amount of privacy, safety, or security in any given system.
  • E.U. AI act will be a disaster for AI innovation and investment
  • Proposed U.S. Algorithmic Accountability Act of 2022 would require that developers perform impact assessments and file them with the Federal Trade Commission. A new Bureau of Technology would be created inside the agency to oversee the process.
  • If enforced through a rigid regulatory regime and another federal bureaucracy, compliance with algorithmic auditing mandates would likely become a convoluted, time-consuming bureaucratic process. That would likely slow the pace of AI development significantly.
  • Academic literature on AI auditing / impact assessment ignores potential costs; Mandatory auditing and assessments are treated as a sort of frictionless nirvana when we already know that such a process would entire significant costs.
  • Some AI scholars suggest that NEPA should be model for AI impact assessments / audits.
  • NEPA assessments were initially quite short (sometimes less than 10 pages), but today the average length of these statements is more than 600 pages and include appendices that average over 1,000 pages on top of that.
  • NEPA assessments take an average of 4.5 years to complete and that, between 2010 and 2017, there were four assessments that took at least 17 years to complete.
  • Many important public projects never get done or take far too long to complete at considerably higher expenditure than originally predicted.
  • would create a number of veto points that opponents of AI could use to stop much progress in the field. This is the “vetocracy” problem.
  • We cannot wait years or even months for bureaucracies to eventually getting around to formally signing off on audits or assessments, many of which would be obsolete before they were even done.
  • “global innovation arbitrage” problem would kick in: Innovators and investors increasingly relocate to the jurisdictions where they are treated most hospitably.
  • Both parties already accuse digital technology companies of manipulating their algorithms to censor their views.
  • Whichever party is in power at any given time could use the process to politicize terms like “safety,” “security,” and “non-discrimination” to nudge or even force private AI developers to alter their algorithms to satisfy the desires of partisan politicians or bureaucrats.
  • FCC abused its ambiguous authority to regulate “in the public interest” and indirectly censor broadcasters through intimidation via jawboning tactics and other “agency threats.” or “regulation by raised eyebrow”
  • There are potentially profound First Amendment issues in play with the regulation of algorithms that have not been explored here but which could become a major part of AI regulatory efforts going forward.

Summary:

  • Auditing and impact assessments can be a part of a more decentralized, polycentric governance framework.
  • Even in the absence of any sort of hard law mandates, algorithmic auditing and impact reviews represent an important way to encourage responsible AI development.
  • But we should be careful about mandating such things due to the many unanticipated cost and consequences of converting this into a top-down, bureaucratic regulatory regime.
  • The process should evolve gradually and organically, as it has in many other fields and sectors.
]]> https://techliberation.com/2022/07/13/event-video-on-algorithmic-auditing-and-ai-impact-assessments/feed/ 3 77008 3 Questions about Progress: The Profectus Progress Roundtable https://techliberation.com/2022/06/15/3-questions-about-the-progress-the-profectus-progress-roundtable/ https://techliberation.com/2022/06/15/3-questions-about-the-progress-the-profectus-progress-roundtable/#respond Wed, 15 Jun 2022 17:10:56 +0000 https://techliberation.com/?p=77002

Profectus is an excellent new online magazine featuring essays and interviews on the intersection of academic literature, public policy, civilizational progress, and human flourishing. The Spring 2022 edition of the magazine features a “Progress Roundtable” in which six different scholars were asked to contribute their thoughts on three general questions:
  1. What is progress?
  2. What are the most significant barriers holding back further progress?
  3. If those challenges can be overcome, what does the world look like in 50 years?

I was honored to be asked by Clay Routledge to contribute answers to those questions alongside others, including: Steven Pinker (Harvard University), Jason Crawford (Roots of Progress), Matt Clancy (Institute for Progress), Marian Tupy (Human​Progress​.org), James Pethokoukis (AEI). I encourage you to jump over the roundtable and read all their excellent responses. I’ve included my answers down below:

What is progress?

Progress is the advancement of human health, happiness, and general well-being. Measures of well-being can be challenging, however, so we should consider a broad range of metrics, including: life expectancy, infant mortality, poverty measures, energy production/consumption, GDP, productivity, agricultural yields/nourishment, and access to various important goods, services, and conveniences. While each of these metrics may have limitations, taken together, they stand for something meaningful that represents a rough proxy for progress.

But we should always remember what progress means at a deeper level for every individual. Innovation and economic growth are important because they allow us to live lives of our own choosing and enjoy the fruits of a prosperous, pluralistic society.  Progress “is not just bigger piles of money,” as Hans Rosling once noted. “The ultimate goal is to have the freedom to do what we want.”  Accordingly, we should aim to broaden the range of opportunities available to all people to help them flourish.

What are the most significant barriers holding back further progress?

The most significant threat to continued progress is the risk of stagnation accompanying efforts to protect the status quo. As Virginia Postrel taught us in her wonderful book The Future & Its Enemies, we should reject stasis-minded thinking and instead shoot for a world of dynamism, which cherishes and protects the freedom to think and act differently.

Progress hinges upon the growth of knowledge. Knowledge comes from experience, and the most important experiences involve trial-and-error learning. Public attitudes and policies that restrict people and ideas from intermingling freely are a recipe for intellectual, social, and economic stagnation. Accordingly, when we consider public policies toward progress, we should first seek to identify and remove legal and regulatory impediments that limit risk-taking, entrepreneurialism, and technological innovation. As science writer Matt Ridley provocatively puts it, to unlock more growth and prosperity, we must first remove obstacles to “ideas having sex.”

The free movement of people and capital is essential to this process. Openness to immigration is the easiest way for a nation to expand its potential for innovation and growth. But domestic labor skills and mobility are equally important. For entrepreneurs and workers, we need to reframe the battle for progress as “the freedom to innovate” and “the right to earn a living.”

Unfortunately, many barriers exist to advancing those goals, like occupational licensing rules and permitting processes, cronyist industrial protectionist schemes, inefficient tax schemes, and many other layers of regulatory red tape. Reforming or eliminating such rules is crucial for broadening opportunities.

Finally, we need to address cultural barriers to progress. Technology and entrepreneurs often get a bad rap in the media and popular culture. Fear and pessimism dominate their narratives. We must do a better job communicating the benefits of openness to change and give people more reasons to be optimistic about a dynamic future.

If those challenges can be overcome, what does the world look like in 50 years?

I agree with Yogi Berra that “It’s tough to make predictions, especially about the future.” Nonetheless, history shows we can achieve remarkable things when we get the prerequisites for progress right and let people tap into their inherent inquisitiveness and inventiveness. Moving the needle on innovation and growth even just a little will yield compounding returns to future generations. But we should dare to dream bigger and think what progress means for each person today and in the future.

A pro-progress agenda will help us lead longer lives and significantly expand our capabilities because that is what people have always desired most. Accordingly, I believe the most significant advance of the next 50 years will be a radical increase in life expectancy and dramatic improvements in our physical and mental capabilities while we are alive.

Today’s tech critics often claim that technological innovation somehow undermines our humanity. They couldn’t be more wrong. There are few things more human than acts of invention. When we take steps to address practical human needs and wants, we enrich our lives and the lives of countless others. The future will be wonderful, so long as we are free to make it so.

]]> https://techliberation.com/2022/06/15/3-questions-about-the-progress-the-profectus-progress-roundtable/feed/ 0 77002 The Proper Governance Default for AI https://techliberation.com/2022/05/26/the-proper-governance-default-for-ai/ https://techliberation.com/2022/05/26/the-proper-governance-default-for-ai/#comments Thu, 26 May 2022 20:15:21 +0000 https://techliberation.com/?p=76994

[This is a draft of a section of a forthcoming study on “A Flexible Governance Framework for Artificial Intelligence,” which I hope to complete shortly. I welcome feedback. I have also cross-posted this essay at Medium.]

Debates about how to embed ethics and best practices into AI product design is where the question of public policy defaults becomes important. To the extent AI design becomes the subject of legal or regulatory decision-making, a choice must be made between two general approaches: the precautionary principle or the proactionary principle.[1] While there are many hybrid governance approaches in between these two poles, the crucial issue is whether the initial legal default for AI technologies will be set closer to the red light of the precautionary principle (i.e., permissioned innovation) or to the green light of the proactionary principle (i.e., (permissionless innovation). Each governance default will be discussed.

The Problem with the Precautionary Principle as the Policy Default for AI

The precautionary principle holds that innovations are to be curtailed or potentially even disallowed until the creators of those new technologies can prove that they will not cause any theoretical harms. The classic formulation of the precautionary principle can be found in the “Wingspan Statement,” which was formulated at an academic conference that took place at the Wingspread Conference Center in Wisconsin in 1998. It read: “Where an activity raises threats of harm to the environment or human health, precautionary measures should be taken even if some cause and effect relationships are not fully established scientifically.”[2] There have been many reformulations of the precautionary principle over time but, as legal scholar Cass Sunstein has noted, “in all of them, the animating idea is that regulators should take steps to protect against potential harms, even if causal chains are unclear and even if we do not know that those harms will come to fruition.”[3] Put simply, under almost all varieties of the precautionary principle, innovation is treated as “guilty until proven innocent.”[4] We can also think of this as permissioned innovation.

The logic animating the precautionary principle reflects a well-intentioned desire to play it safe in the face of uncertainty. The problem lies in the way this instinct gets translated into law and regulation. Making the precautionary principle the public policy default for any given technology or sector has a strong bearing on how much innovation we can expect to flow from it. When trial-and-error experimentation is preemptively forbidden or discouraged by law, it can limit many of the positive outcomes that typically accompany efforts by people to be creative and entrepreneurial. This can, in turn, give rise to different risks for society in terms of forgone innovation, growth, and corresponding opportunities to improve human welfare in meaningful ways.

St. Thomas Aquinas once observed that if the sole goal of a captain were to preserve their ship, the captain would keep it in port forever. But that clearly is not the captain’s highest goal. Aquinas was making a simple but powerful point: There can be no reward without some effort and even some risk-taking. Ship captains brave the high seas because they are in search of a greater good, such as recognition, adventure, or income. Keeping ships in port forever would preserve their vessels, but at what cost?

Similarly, consider the wise words of Wilbur Wright, who pioneered human flight. Few people better understood the profound risks associated with entrepreneurial activities. After all, Wilbur and his brother were trying to figure out how to literally lift humans off the Earth. The dangers were real, but worth taking. “If you are looking for perfect safety,” Wright said, “you would do well to sit on a fence and watch the birds.” Humans would have never taken to the skies if the Wright brothers had not gotten off the fence and taken the risks they did. Risk-taking drives innovation and, over the long-haul, improves our well-being.[5] Nothing ventured, nothing gained.

These lessons can be applied to public policy by considering what would happen if, in the name of safety, public officials told captains to never leave port or told aspiring pilots to never leave the ground. The opportunity cost of inaction can be hard to quantify, but it should be clear that if we organized our entire society around a rigid application of the precautionary principle, progress and prosperity would suffer.

Heavy-handed preemptive restraints on creative acts can have deleterious effects because they raise barriers to entry, increase compliance costs, and create more risk and uncertainty for entrepreneurs and investors. Thus, it is the unseen costs—primarily in the form of forgone innovation opportunities—that makes the precautionary principle so problematic as a policy default. This is why scientist Martin Rees speaks of “the hidden cost of saying no” that is associated with the precautionary principle.[6]

The precise way the precautionary principle leads to this result is that it derails the so-called learning curve by limiting opportunities to learn from trial-and-error experimentation with new and better ways of doing things.[7] The learning curve refers to the way that individuals, organizations, or industries are able to learn from their mistakes, improve their designs, enhance productivity, lower costs, and then offer superior products based on the resulting knowledge.[8] In his recent book, Where Is My Flying Car?, J. Storrs Hall documents how, over the last half century, “regulation clobbered the learning curve” for many important technologies in the U.S., especially nuclear, nanotech, and advanced aviation.[9] Hall shows how society was denied many important innovations due to endless foot-dragging or outright opposition to change from special interests, anti-innovation activists, and over-zealous bureaucrats.

In many cases, innovators don’t even know what they are up against because, as many scholars have noted, “the precautionary principle, in all of its forms, is fraught with vagueness and ambiguity.”[10] It creates confusion and fear about the wisdom of taking action in the face of uncertainty. Worst case thinking paralyzes regulators who aim to “play it safe” at all costs. The result is an endless snafu of red tape as layer upon layer of mandates build up and block progress. The result is what many scholars now decry as a culture of “vetocracy,” which describes the many veto points within modern political systems that hold back innovation, development and economic opportunity.[11] This endless accumulation of potential veto points in the policy process in the form of mandates and restrictions can greatly curtail innovation opportunities. “Like sediment in a harbor, law has steadily accumulated, mainly since the 1960s, until most productive activity requires slogging through a legal swamp,” says Philip K. Howard, chair of Common Good.[12] “Too much law,” he argues, “can have similar effects as too little law,” because:

People slow down, they become defensive, they don’t initiate projects because they are surrounded by legal risks and bureaucratic hurdles. They tiptoe through the day looking over their shoulders rather than driving forward on the power of their instincts. Instead of trial and error, they focus on avoiding error.[13]

This is exactly why it is important that policymakers not get too caught up in attempts to preemptively resolve every potential hypothetical worst case scenarios associated with AI technologies. The problem with that approach was succinctly summarized by the political scientist Aaron Wildavsky when he noted, “If you can do nothing without knowing first how it will turn out, you cannot do anything at all.”[14] Or, as I have stated in a book on this topic, “living in constant fear of worst-case scenarios—and premising public policy on them—means that best-case scenarios will never come about.”[15]

This does not mean society should dismiss all concerns about the risks surrounding AI. Some technological risks do necessitate a degree of precautionary policy, but proportionality is crucial, notes Gabrielle Bauer, a Toronto-based medical writer. “Used too liberally,” she argues, “the precautionary principle can keep us stuck in a state of extreme risk-aversion, leading to cumbersome policies that weigh down our lives. To get to the good parts of life, we need to accept some risk.”[16] It is not enough to simply hypothesize that certain AI innovations might entail some risk. The critics need to prove it using risk analysis techniques that properly weigh both the potential costs and benefits.[17] Moreover, when conducting such analyses, the full range of trade-offs associated with preemptive regulation must be evaluated. Again, where precautionary constraints might deny society life-enriching devices or services, those costs must be acknowledged.

Generally speaking, the most extreme precautionary controls should only be imposed when the potential harms in question are highly probable, tangible, immediate, irreversible, catastrophic, or directly threatening to life and limb in some fashion.[18] In the context of AI and ML systems, it may be the case that such a test is satisfied already for law enforcement use of certain algorithmic profiling techniques. And that test is satisfied for so-called “killer robots,” or autonomous military technology.[19] These are often described as “existential risks.” The precautionary principle is the right default in these cases because it is abundantly clear how unrestricted use would have catastrophic consequences. For similar reasons, governments have long imposed comprehensive restrictions on certain types of weapons.[20] And although nuclear and chemical technologies have many important applications, their use must also be limited to some degree even outside of militaristic applications because they can pose grave danger if misused.

But the vast majority of AI-enabled technologies are not like this. Most innovations should not be treated the same a hand grenade or a ticking time bomb. In reality, most algorithmic failures will be more mundane and difficult to foresee in advance. By their very nature, algorithms are constantly evolving because programs and systems are being endlessly tweaked by designers to improve them. In his books on the evolution of engineering and systems design, Henry Petroski has noted that “the shortcomings of things are what drive their evolution.”[21] The normal state of things is “ubiquitous imperfection,” he notes, and it is precisely that reality that drives efforts to continuously innovate and iterate.[22]

Regulations rooted in the precautionary principle hope to preemptively find and address product imperfections before any harm comes from them. In reality, and as explained more below, it is only through ongoing experimentation that we find both the nature of failures and the knowledge to know how to correct them. As Petroski observes, “the history of engineering in general, may be told in its failures as well as in its triumphs. Success may be grand, but disappointment can often teach us more.”[23] This is particularly true for complex algorithmic systems, where rapid-fire innovation and incessant iteration are the norm.

Importantly, the problem with precautionary regulation for AI is not just that it might be over-inclusive in seeking to regulate hypothetical problems that never develop. Precautionary regulation can also be under-inclusive by missing problematic behavior or harms that no one anticipated before the fact. Only experience and experimentation reveal certain problems.

In sum, we should not presume that there is a clear preemptive regulatory solution to every problem some people raise about AI, nor should we presume we can even accurately identify all such problems that might come about in the future. Moreover, some risks will never be eliminated entirely, meaning that risk mitigation is the wiser approach. This is why a more flexible bottom-up governance strategy focused on responsiveness and resiliency makes more sense than heavy-handed, top-down strategies that would only avoid risks by making future innovations extremely difficult if not impossible.

The “Proactionary Principle” is the Better Default for AI Policy

The previous section made it clear why the precautionary principle should generally not be used as our policy default if we hope to encourage the development of AI applications and services. What we need is a policy approach that:

  • objectively evaluates the concerns raised about AI systems and applications;
  • considers whether more flexible governance approaches might be available to address them; and,
  • does so without resorting to the precautionary principle as a first-order response.

The proactionary principle is the better general policy default for AI because it satisfies these three objectives.[24] Philosopher Max More defines the proactionary principle as the idea that policymakers should, “[p]rotect the freedom to innovate and progress while thinking and planning intelligently for collateral effects.”[25] There are different names for this same concept, including the innovation principle, which Daniel Castro and Michael McLaughlin of the Information Technology and Innovation Foundation say represents the belief that “the vast majority of new innovations are beneficial and pose little risk, so government should encourage them.”[26] Permissionless innovation is another name for the same idea. Permissionless innovation refers to the idea that experimentation with new technologies and business models should generally be permitted by default.[27]

What binds these concepts together is the belief that innovation should generally be treated as innocent until proven guilty. There will be risks and failures, of course, but the permissionless innovation mindset views them as important learning experiences. These experiences are chances for individuals, organizations, and all of society to make constant improvements through incessant experimentation with new and better ways of doing things.[28] As Virginia Postrel argued in her 1998 book, The Future and Its Enemies, progress demands “a decentralized, evolutionary process” and mindset in which mistakes are not viewed as permanent disasters but instead as “the correctable by-products of experimentation.”[29] “No one wants to learn by mistakes,” Petroski once noted, “but we cannot learn enough from successes to go beyond the state of the art.”[30] Instead we must realize, as other scholars have observed, that “[s]uccess is the culmination of many failures”[31] and understand “failure as the natural consequence of risk and complexity.”[32]

This is why the default for public policy for AI innovation should, whenever possible, be more green lights than red ones to allow for the maximum amount of trial-and-error experimentation, which encourages ongoing learning.[33] “Experimentation matters,” observes Stefan H. Thomke of the Harvard Business School, “because it fuels the discovery and creation of knowledge and thereby leads to the development and improvement of products, processes, systems, and organizations.”[34]

Obviously, risks and mistakes are “the very things regulators inherently want to avoid,”[35] but “if innovators fear they will be punished for every mistake,” Daniel Castro and Alan McQuinn argue, “then they will be much less assertive in trying to develop the next new thing.”[36] And for all the reasons already stated, that would represent the end of progress because it would foreclose the learning process that allows society to discover new, better, and safer ways of doing things. Technology author Kevin Kelly puts it this way:

technologies must be evaluated in action, by action. We test them in labs, we try them out in prototypes, we use them in pilot programs, we adapt our expectations, we monitor their alterations, we redefine their aims as they are modified, we retest them given actual behavior, we re-direct them to new jobs when we are not happy with their outcomes.[37]

In other words, the proactionary principle appreciates the benefits that flow from learning by doing. The goal is to continuously assess and prioritize risks from natural and human-made systems alike, and then formulate and reformulate our toolkit of possible responses to those risks using the most practical and effective solutions available. This should make it clear that the proactionary approach is not synonymous with anarchy. Various laws, government bodies, and especially the courts play an important role in protecting rights, health, and order. But policies need to be formulated such that innovators and innovation are given the benefit of the doubt and risks are analyzed and addressed in a more flexible fashion.

Some of the most effective ways to address potential AI risks already exist in the form of “soft law” and decentralized governance solution. These will be discussed at greater length below. But existing legal remedies include various common law solutions (torts, class actions, contract law, etc), recall authority possessed by many regulatory agencies, and various consumer protection policies. Ex post remedies are generally superior to ex ante prior restraints if we hope to maximize innovation opportunities. Ex ante regulatory defaults are too often set closer to the red light of the precautionary principle and then enforced through volumes of convoluted red tape.

This is what the World Economic Forum has referred to as a “regulate-and-forget” system of governance,[38] or what others call a “build-and-freeze model” or regulation.[39] In such technological governance regimes, older rules are almost never revisited, even after new social, economic, and technical realities render them obsolete or ineffective.[40] A 2017 survey of U.S. Code of Regulations by Deloitte consultants revealed that 68 percent of federal regulations have never been updated and that 17 percent have only been updated once.[41] Public policies for complex and fast-moving technologies like AI cannot be set in stone and forgotten like that if America hopes to remain on the cutting edge of this sector.

Advocates of the proactionary principle look to counter this problem not by eliminating all laws or agencies, but by bringing them in line with flexible governance principles rooted in more decentralized approaches to policy concerns.[42] As many regulatory advocates suggest, it is important to embed or “bake in” various ethical best practices into AI systems to ensure that they benefit humanity. But this, too, is a process of ongoing learning and there are many ways to accomplish such goals without derailing important technological advances. What is often referred to as “value alignment” or “ethically-aligned design” is challenged by the fact that humans regularly disagree profoundly about many moral issues.[43] “Before we can put our values into machines, we have to figure out how to make our values clear and consistent,” says Harvard University psychologist Joshua D. Greene.[44]

The “Three Laws of Robotics” famously formulated decades ago by Isaac Asimov in his science fiction stories continue to be widely discussed today as a guide to embedding ethics into machines.[45] They read:

  1. A robot may not injure a human being or, through inaction, allow a human being to come to harm.
  2. A robot must obey orders given it by human beings except where such orders would conflict with the First Law.
  3. A robot must protect its own existence as long as such protection does not conflict with the First or Second Laws.

What is usually forgotten about these principles, as AI expert Melanie Mitchell reminds us, is the way Asimov, “often focused on the unintended consequences of programming ethical rules into robots,” and how he made it clear that, if applied too literally, “such a set of rules would inevitably fail.”[46]

This is why flexibility and humility are essential virtues when thinking about AI policy. The optimal governance regime for AI can be shaped by responsible innovation practices and embed important ethical principles by design without immediately defaulting to a rigid application of the precautionary principle.[47] In other words, an innovation policy regime rooted in the proactionary principle can also be infused with the same values that animate a precautionary principle-based system.[48] The difference is that the proactionary principle-based approach will look to achieve these goals in a more flexible fashion using a variety of experimental governance approaches and ex post legal enforcement options, while also encouraging still more innovation to solve problems past innovations may have caused.

To reiterate, not every AI risk is foreseeable, and many risks and harms are more amorphous or uncertain. In this sense, the wisest governance approach for AI was recently outlined by the National Institute of Standards and Technology (NIST) in its initial draft AI Risk Management Framework, which is a multistakeholder effort “to describe how the risks from AI-based systems differ from other domains and to encourage and equip many different stakeholders in AI to address those risks purposefully.”[49] NIST notes that the goal of the Framework is:

to be responsive to new risks as they emerge rather than enumerating all known risks in advance. This flexibility is particularly important where impacts are not easily foreseeable, and applications are evolving rapidly. While AI benefits and some AI risks are well-known, the AI community is only beginning to understand and classify incidents and scenarios that result in harm.[50]

This is a sensible framework for how to address AI risks because it makes it clear that it will be difficult to preemptively identify and address all potential AI risks. At the same time, there will be a continuing need to advance AI innovation while addressing AI-related harms. The key to striking that balance will be decentralized governance approaches and soft law techniques described below.

[Note: The subsequent sections of the study will detail how decentralized governance approaches and soft law techniques already are helping to address concerns about AI risks.]

Endnotes:

[1]     Adam Thierer, Permissionless Innovation: The Continuing Case for Comprehensive Technological Freedom, 2nd ed. (Arlington, VA: Mercatus Center at George Mason University, 2016): 1-6, 23-38; Adam Thierer, Evasive Entrepreneurs & the Future of Governance (Washington, DC: Cato Institute, 2020): 48-54.

[2]     “Wingspread Statement on the Precautionary Principle,” January 1998, https://www.gdrc.org/u-gov/precaution-3.html.

[3]     Cass R. Sunstein, Laws of Fear: Beyond the Precautionary Principle (Cambridge, UK: Cambridge University Press, 2005). (“The Precautionary Principle takes many forms. But in all of them, the animating idea is that regulators should take steps to protect against potential harms, even if causal chains are unclear and even if we do not know that those harms will come to fruition.”)

[4]     Henk van den Belt, “Debating the Precautionary Principle: ‘Guilty until Proven Innocent’ or ‘Innocent until Proven Guilty’?” Plant Physiology 132 (2003): 1124.

[5]     H.W. Lewis, Technological Risk (New York: WW. Norton & Co., 1990): x. (“The history of the human race would be dreary indeed if none of our forebears had ever been willing to accept risk in return for potential achievement.”)

[6]     Martin Rees, On the Future: Prospects for Humanity (Princeton, NJ: Princeton University Press, 2018): 136.

[7]     Adam Thierer, “Failing Better: What We Learn by Confronting Risk and Uncertainty,” in Sherzod Abdukadirov (ed.), Nudge Theory in Action: Behavioral Design in Policy and Markets (Palgrave Macmillan, 2016): 65-94.

[8]     Adam Thierer, “How to Get the Future We Were Promised,” Discourse, January 18, 2022, https://www.discoursemagazine.com/culture-and-society/2022/01/18/how-to-get-the-future-we-were-promised.

[9]     J. Storrs Hall, Where Is My Flying Car? (San Francisco: Stripe Press, 2021)

[10]    Derek Turner and Lauren Hartzell Nichols, “The Lack of Clarity in the Precautionary Principle,” Environmental Values, Vol 13, No. 4 (2004): 449.

[11]    William Rinehart, “Vetocracy, the Costs of Vetos and Inaction,” Center for Growth & Opportunity at Utah State University, March 24, 2022, https://www.thecgo.org/benchmark/vetocracy-the-costs-of-vetos-and-inaction; Adam Thierer, “Red Tape Reform is the Key to Building Again,” The Hill, April 28, 2022, https://thehill.com/opinion/finance/3470334-red-tape-reform-is-the-key-to-building-again.

[12]    Philip K. Howard, “Radically Simplify Law,” Cato Institute, Cato Online Forum, http://www.cato.org/publications/cato-online-forum/radically-simplify-law.

[13]    Ibid.

[14]    Aaron Wildavsky, Searching for Safety (New Brunswick, NJ: Transaction Publishers, 1989): 38.

[15]    Thierer, Permissionless Innovation, at 2.

[16]    Gabrielle Bauer, “Danger: Caution Ahead,” The New Atlantis, February 4, 2022, https://www.thenewatlantis.com/publications/danger-caution-ahead.

[17]    Richard B. Belzer, “Risk Assessment, Safety Assessment, and the Estimation of Regulatory Benefits” (Mercatus Working Paper, Mercatus Center at George Mason University, Arlington, VA, 2012), 5, http://mercatus.org/publication/risk-assessment-safety-assessment-and-estimation-regulatory-benefits; John D. Graham and Jonathan Baert Wiener, eds. Risk vs. Risk: Tradeoffs in Protecting Health and the Environment, (Cambridge, MA: Harvard University Press, 1995).

[18]    Thierer, Permissionless Innovation, at 33-8.

[19]    Adam Satariano, Nick Cumming-Bruce and Rick Gladstone, “Killer Robots Aren’t Science Fiction. A Push to Ban Them Is Growing,” New York Times, December 17, 2021, https://www.nytimes.com/2021/12/17/world/robot-drone-ban.html.

[20]    Adam Thierer, “Soft Law: The Reconciliation of Permissionless & Responsible Innovation,” in Adam Thierer, Evasive Entrepreneurs & the Future of Governance (Washington, DC: Cato Institute, 2020): 183-240, https://www.mercatus.org/publications/technology-and-innovation/soft-law-reconciliation-permissionless-responsible-innovation.

[21]    Henry Petroski, The Evolution of Useful Things (New York: Vintage Books, 1994): 34.

[22]    Ibid., 27,

[23]    Henry Petroski, To Engineer is Human: The Role of Failure in Successful Design (New York: Vintage, 1992): 9.

[24]    James Lawson, These Are the Droids You’re Looking For: An Optimistic Vision for Artificial Intelligence, Automation and the Future of Work (London: Adam Smith Institute, 2020): 86, https://www.adamsmith.org/research/these-are-the-droids-youre-looking-for.

[25]    Max More, “The Proactionary Principle (March 2008),” Max More’s Strategic Philosophy, March 28, 2008, http://strategicphilosophy.blogspot.com/2008/03/proactionary-principle-march-2008.html.

[26]    Daniel Castro & Michael McLaughlin, “Ten Ways the Precautionary Principle Undermines Progress in Artificial Intelligence,” Information Technology and Innovation Foundation, February 4, 2019, https://itif.org/publications/2019/02/04/ten-ways-precautionary-principle-undermines-progress-artificial-intelligence.

[27]    Thierer, Permissionless Innovation.

[28]    Thierer, “Failing Better.”

[29]    Virginia Postrel, The Future and Its Enemies (New York: The Free Press, 1998): xiv.

[30]    Henry Petroski, To Engineer is Human: The Role of Failure in Successful Design (New York: Vintage, 1992): 62.

[31]    Kevin Ashton, How to Fly a Horse: The Secret History of Creation, Invention, and Discovery (New York: Doubleday, 2015): 67.

[32]    Megan McArdle, The Up Side of Down: Why Failing Well is the Key to Success (New York: Viking, 2014), 214.

[33]    F. A. Hayek, The Constitution of Liberty (London: Routledge, 1960, 1990): 81. (“Humiliating to human pride as it may be, we must recognize that the advance and even preservation of civilization are dependent upon a maximum of opportunity for accidents to happen.”)

[34]    Stefan H. Thomke, Experimentation Matters: Unlocking the Potential of New Technologies for Innovation (Harvard Business Review Press, 2003), 1.

[35]    Daniel Castro and Alan McQuinn, “How and When Regulators Should Intervene,” Information Technology and Innovation Foundation Reports, (February 2015): 2 http://www.itif.org/publications/how-and-when-regulators-should-intervene.

[36]    Ibid.

[37]    Kevin Kelly, “The Pro-Actionary Principle,” The Technium, November 11, 2008, https://kk.org/thetechnium/the-pro-actiona.

[38]    World Economic Forum, Agile Regulation for the Fourth Industrial Revolution (Geneva: Switzerland: 2020): 4, https://www.weforum.org/projects/agile-regulation-for-the-fourth-industrial-revolution.

[39]    Jordan Reimschisel and Adam Thierer, “’Build & Freeze’ Regulation Versus Iterative Innovation,” Plain Text, November 1, 2017, https://readplaintext.com/build-freeze-regulation-versus-iterative-innovation-8d5a8802e5da.

[40]    Adam Thierer, “Spring Cleaning for the Regulatory State,” AIER, May 23, 2019, https://www.aier.org/article/spring-cleaning-for-the-regulatory-state.

[41]    Daniel Byler, Beth Flores & Jason Lewris, “Using Advanced Analytics to Drive Regulatory Reform: Understanding Presidential Orders on Regulation Reform,” Deloitte, 2017, https://www2.deloitte.com/us/en/pages/public-sector/articles/advanced-analytics-federal-regulatory-reform.html.

[42]    Adam Thierer, Governing Emerging Technology in an Age of Policy Fragmentation and Disequilibrium, American Enterprise Institute (April 2022), https://platforms.aei.org/can-the-knowledge-gap-between-regulators-and-innovators-be-narrowed.

[43]    Brian Christian, The Alignment Problem: Machine Learning and Human Values (New York: W.W. Norton & Company, 2020).

[44]    Joshua D. Greene, “Our Driverless Dilemma,” Science (June 2016): 1515.

[45]    Susan Leigh Anderson, “Asimov’s ‘Three Laws of Robotics’ and Machine Metaethics,” AI and Society, Vol. 22, No. 4, (2008): 477-493.

[46]    Melanie Mitchell, Artificial Intelligence: A Guide for Thinking Humans (New York: Farrar, Straus and Giroux, 2019): 126 [Kindle edition.]

[47]    Thomas A. Hemphill, “The Innovation Governance Dilemma: Alternatives to the Precautionary Principle,” Technology in Society, Vol. 63 (2020): 6, https://ideas.repec.org/a/eee/teinso/v63y2020ics0160791x2030751x.html.

[48]    Adam Thierer, “Are ‘Permissionless Innovation’ and ‘Responsible Innovation’ Compatible?” Technology Liberation Front, July 12, 2017, https://techliberation.com/2017/07/12/are-permissionless-innovation-and-responsible-innovation-compatible.

[49]    The National Institute of Standards and Technology, “AI Risk Management Framework: Initial Draft,” (March 17, 2022): 1, https://www.nist.gov/itl/ai-risk-management-framework.

[50]    Ibid., at 5.

]]> https://techliberation.com/2022/05/26/the-proper-governance-default-for-ai/feed/ 4 76994 Event Notice: “2022 Tech and Innovation Summit” https://techliberation.com/2022/05/25/event-notice-2022-tech-and-innovation-summit/ https://techliberation.com/2022/05/25/event-notice-2022-tech-and-innovation-summit/#respond Wed, 25 May 2022 14:10:18 +0000 https://techliberation.com/?p=76991

Just FYI, the James Madison Institute will be hosting its “2022 Tech and Innovation Summit” on Thursday, September 15 and Friday, September 16 in Coral Gables, Florida. I’m honored to be included among the roster of speakers announced so far, which includes:

  • Ajit Pai, Former Chairman of the Federal Communications Commission
  • Adam Thierer, the Mercatus Center at George Mason University
  • Will Duffield, Cato Institute
  • Utah State Representative Cory Maloy
  • Dane Ishihara, Director of Utah’s Office of Regulatory Relief

Registration info is here.

]]> https://techliberation.com/2022/05/25/event-notice-2022-tech-and-innovation-summit/feed/ 0 76991 “Building Again” Must Be More than Just Rhetoric https://techliberation.com/2022/04/29/building-again-must-be-more-than-just-rhetoric/ https://techliberation.com/2022/04/29/building-again-must-be-more-than-just-rhetoric/#comments Fri, 29 Apr 2022 18:22:05 +0000 https://techliberation.com/?p=76978

As I note in my latest regular column for The Hill, it seems like everyone these days is talking about the importance of America “building again.” For example, take a look at this compendium of essays I put together where scholars and pundits have been making the case for “building again” in various ways and contexts. It would seem that the phrase is on everyone’s lips. “These calls include many priorities,” I note, “but what unifies them is the belief that the nation needs to develop new innovations and industries to improve worker opportunities, economic growth and U.S. global competitive standing.”

What I fear, however, is that “building again” has become more of a convenient catch line than anything else. It seems like few people are willing to spell out exactly what it will take to get that started. My new column suggests that the most important place to start is “to cut back the thicket of red tape and stifling bureaucratic procedures that limit the productiveness of the American workforce.” I cite recent reports and data documenting the enormous burden that regulatory accumulation imposes on American innovators and workers. I then discuss how to get reforms started at all levels of government to get the problem under control and help us start building again in earnest. Jump over to The Hill to read the entire essay.

]]> https://techliberation.com/2022/04/29/building-again-must-be-more-than-just-rhetoric/feed/ 4 76978 Book Review: “Questioning the Entrepreneurial State” https://techliberation.com/2022/04/26/book-review-questioning-the-entrepreneurial-state/ https://techliberation.com/2022/04/26/book-review-questioning-the-entrepreneurial-state/#comments Tue, 26 Apr 2022 20:14:03 +0000 https://techliberation.com/?p=76975

An important new book launched this week in Europe on issues related to innovation policy and industrial policy. “Questioning the Entrepreneurial State: Status-quo, Pitfalls, and the Need for Credible Innovation Policy” (Springer, 2022) brings together more than 30 scholars who contribute unique chapters to this impressive volume. It was edited by Karl Wennberg of the Stockholm School of Economics and Christian Sandström of the Jönköping (Sweden) International Business School.

As the title of this book suggests, the authors are generally pushing back against the thesis found in Mariana Mazzucato’s book The Entrepreneurial State (2011). That book, like many other books and essays written recently, lays out a romantic view of industrial policy that sees government as the prime mover of markets and innovation. Mazzucato calls for “a bolder vision for the State’s dynamic role in fostering economic growth” and innovation. She wants the state fully entrenched in technological investments and decision-making throughout the economy because she believes that is the best way to expand the innovative potential of a nation.

The essays in Questioning the Entrepreneurial State offer a different perspective, rooted in the realities on the ground in Europe today. Taken together, the chapters tell a fairly consistent story: Despite the existence of many different industrial policy schemes at the continental and country level, Europe isn’t in very good shape on the tech and innovation front. The heavy-handed policies and volumes of regulations imposed by the European Union and its member states have played a role in that outcome. But these governments have simultaneously been pushing to promote innovation using a variety of technocratic policy levers and industrial policy schemes. Despite all those well-intentioned efforts, the EU has struggled to keep up with the US and China in most important modern tech sectors.

As Wennberg and Sandström note in their introductory chapter:

Grand schemes toward noble outcomes have a disappointing track record in human political and economic history. Conventional wisdom regarding authorities’ inability to selectively pinpoint certain technologies, sectors, or firms as winners, and the fact that large support structures for specific technologies are bound to distort incentives and result in opportunism, seem to have been forgotten.

In summarizing the chapters, they conclude that, “while the idea of aiming high and leveraging large portions of society’s resources to address some fundamental human challenges may sound appealing to many, such ideas have limited scientific credibility.”

Why do governments frequently fail in attempts to be entrepreneurial? Johan P. Larsson gets at the heart of the matter in his chapter when noting how, “[t]he state entrepreneur is not subject to real risk, often faces no market, and cannot be properly evaluated. It pays no price for being wrong and it struggles in assigning responsibility.” Which leads to two questions that are rarely asked, he notes: “[F]irst, how do we ensure that the state pays a price for being wrong? And second, when is that price high enough for us to know it is time to cut our losses?”

The authors of another chapter (Murtinu, Foss & Klein) concur and note how, “even well-intentioned and strongly motivated public actors lack the ability to manage the process of innovation.” “As stewards of resources owned by the public,” they note, “government bureaucrats do not exercise the ultimate responsibility that comes with ownership.” In other words, the state faces problems of misaligned incentives.

Several authors in the book highlight the various public choice problems often associated with large-scale industrial policy initiatives, including rent-seeking and capture. Wennberg and Sandström note how this results in less disruption as established players don’t seek to challenge existing market or technological status quos but instead simply seek to benefit from it. “[S]upport structures, platforms for private-public cooperation, and large volumes of technology-specific money usually end up in the hands of established interest groups,” they note. “Hence, they are not very likely to question these policies but will rather go along with the ride.”

John-Erik Bergkvist and Jerker Moodysson devote an entire chapter to this problem and offer a grim assessment of how past industrial policy schemes have exacerbated it:

Assuming that policies and programs are shaped by the interest groups that are affected by the policies, we highlight the risk that policymaking may end up as support for established interest groups rather than supporting the emergence of those who could act as institutional entrepreneurs or disruptors. Policies and programs may thus be captivated by dominant actors in the established regime, who have superior financial and relational resources. The result would then be that innovation policies sustain the established socio-technical structures of industries rather than contributing to the emergence of new structures.”

Other organizations are incentivized to support the status quo when big money is on the line. One of the most interesting chapters in the book was co-authored by Wennberg and Sandström along with Elias Collin. They examine the conflicts of interest inherent in many evaluations of industrial policy programs by various third parties, including academics and consultants who receive generous state contracts:

the overwhelming majority of evaluations are positive or neutral and that very few evaluations are negative. While this is the case across all categories of evaluators, we note that consulting firms stand out as particularly inclined to provide positive evaluations. The absence of negative or critical reports can be related to the fact that most of the studies do not rely upon methods that make it possible to discuss effects. This discrepancy between so many positive evaluations on the one hand and comparatively weak evaluation methods on the other hand leads us to suspect that evaluators are not sufficiently independent. Consultants and scholars that are funded by a government agency in order to evaluate the agency’s policies and programs are put in a position where it is difficult to maintain objectivity.

This is one reason why industrial policy continues to have such currency in European policy discussions despite a long track record of failure, as documented throughout this new book. The biggest problem for Europe lies in its layers of regulatory bureaucracy and heavy-handed treatment of entrepreneurs.

Later in the book, Zoltan J. Acs offers a grim account of just how bad things have been for Europe on the digital technology front in recent decades, despite the many state-led efforts to promote the sector. “The European Union protected traditional industries and hoped that existing firms would introduce new technologies. This was a policy designed to fail,” Acs argues. “What has been the outcome of E.U. policy in limiting entrepreneurial activity over recent decades?” he asks. Acs concludes that:

It is immediately clear… that the United States and China dominate the platform landscape. Based on the market value of top companies, the United States alone represents 66% of the world’s platform economy with 41 of the top 100 companies. European platform-based companies play a marginal role, with only 3% of market value.

He says that the United Kingdom’s “Brexit” from the European Union was a logical move, “because E.U. regulations were holding back the U.K.’s strong DPE (digital platform economy).” “If the United Kingdom was to realize its economic potential, it had to extricate itself from the European Union,” Acs says, due to the “dysfunctional E.U. bureaucracy.” No amount of industrial policy support is going to allow European firms to overcome those burdens. In fact, many of Europe’s industrial policy programs create the very disincentives that retard innovation and discourage entrepreneurialism in key sectors.

Several of the authors in the collection stress how the better role for the state is usually to set the table for innovation and growth without trying to determine everything that is served on the plate. As Wennberg and Sandström summarize:

the best policies to promote innovation are those that promote productive economic activity more generally: property rights protection, open and contestable markets, a stable monetary system, and legal rules that favor competition and entrepreneurship. Policy should promote an institutional environment in which innovation and entrepreneurship can flourish without trying to anticipate the specific outcomes of those processes—an impossible task in the face of uncertainty, technological change, and a dynamic, knowledge-based economy.

That’s good advice, as is everything found throughout the book. I encourage all those interested in these issues to take a hard look at it because it is particularly relevant even here in the Unites States, as Congress is currently considering a massive new 3,000-page, $350 billion industrial policy bill that I’ve labelled “The Most Corporatist & Wasteful Industrial Policy Ever.” There doesn’t seem to be anything stopping the momentum of this effort with both liberals and conservatives lining up to pass out the pork. I wish I could put a copy of Questioning the Entrepreneurial State in all their hands and ask them to read every word of it before they gamble hundreds of billions on such foolish efforts.

Additional Reading:

]]> https://techliberation.com/2022/04/26/book-review-questioning-the-entrepreneurial-state/feed/ 2 76975 Slide Presentation on “The Future of Innovation Policy” https://techliberation.com/2022/04/18/slide-presentation-on-the-future-of-innovation-policy/ https://techliberation.com/2022/04/18/slide-presentation-on-the-future-of-innovation-policy/#comments Mon, 18 Apr 2022 19:24:10 +0000 https://techliberation.com/?p=76968

Here’s a slide presentation on “The Future of Innovation Policy” that I presented to some student groups recently. It builds on themes discussed in my recent books, Permissionless Innovation: The Continuing Case for Comprehensive Technological Freedom, and Evasive Entrepreneurs and the Future of Governance: How Innovation Improves Economies and Governments. I specifically discuss the tension between permissionless innovation and the precautionary principle as competing policy defaults.

]]> https://techliberation.com/2022/04/18/slide-presentation-on-the-future-of-innovation-policy/feed/ 1 76968 Samuel Florman & the Continuing Battle over Technological Progress https://techliberation.com/2022/04/06/samuel-florman-the-continuing-battle-over-technological-progress/ https://techliberation.com/2022/04/06/samuel-florman-the-continuing-battle-over-technological-progress/#comments Wed, 06 Apr 2022 18:37:45 +0000 https://techliberation.com/?p=76961

Almost every argument against technological innovation and progress that we hear today was identified and debunked by Samuel C. Florman a half century ago. Few others since him have mounted a more powerful case for the importance of innovation to human flourishing than Florman did throughout his lifetime.

Chances are you’ve never heard of him, however. As prolific as he was, Florman did not command as much attention as the endless parade of tech critics whose apocalyptic predictions grabbed all the headlines. An engineer by training, Florman became concerned about the growing criticism of his profession throughout the 1960s and 70s. He pushed back against that impulse in a series of books over the next two decades, including most notably: The Existential Pleasures of Engineering (1976), Blaming Technology: The Irrational Search for Scapegoats (1981), and The Civilized Engineer (1987). He was also a prolific essayist, penning hundreds of articles for a wide variety of journals, magazines, and newspapers beginning in 1959. He was also a regular columnist for MIT Technology Review for sixteen years.

Florman’s primary mission in his books and many of those essays was to defend the engineering profession against attacks emanating from various corners. More broadly, as he noted in a short autobiography on his personal website, Florman was interested in discussing, “the relationship of technology to the general culture.”

Florman could be considered a “rational optimist,” to borrow Matt Ridley’s notable term [1] for those of us who believe, as I have summarized elsewhere, that there is a symbiotic relationship between innovation, economic growth, pluralism, and human betterment.[2] Rational optimists are highly pragmatic and base their optimism on facts and historical analysis, not on dogmatism or blind faith in any particular viewpoint, ideology, or gut feeling. But they are unified in the belief that technological change is a crucial component of moving the needle on progress and prosperity.

Florman’s unique contribution to advancing rational optimism came in the way he itemized the various claims made by tech critics and then powerfully debunked each one of them. He was providing other rational optimists with a blueprint for how defend technological innovation against its many critics and criticisms. As he argued in The Civilized Engineer, we need to “broaden our conception of engineering to include all technological creativity.”[3] And then we need to defend it with vigor.

In 1982, the American Society of Mechanical Engineers appropriately awarded Florman the distinguished Ralph Coats Roe Medal for his “outstanding contribution toward a better public understanding and appreciation of the engineer’s worth to contemporary society.” Carl Sagan had won the award the previous year. Alas, Forman never attained the same degree of notoriety as Sagan. That is a shame because Florman was as much a philosopher and a historian as he was an engineer, and his robust thinking on technology and society deserves far greater attention. More generally, his plain-spoken style and straight-forward defense of technological progress continues to be a model for how to counter today’s techno-pessimists.

This essay highlights some of the most important themes and arguments found in Florman’s writing and explains its continuing relevance to the ongoing battles over technology and progress.

What Motivates The “Antitechnologists”?

Florman was interested in answering questions about what motivates both engineers as well as their critics. He dug deep into psychology and history to figure out what makes these people tick. Who are engineers, and why do they do what they do? That was his primary question, and we will turn to his answers momentarily. But he also wanted to know what drove the technology critics to oppose innovation so vociferously.

Florman’s most important contribution to the history of ideas lies in his 6-part explanation of “the main themes that run through the works of the antitechnologists.”[4] Florman used the term “antitechnologists” to describe the many different critics of engineering and innovation. He recognized that the term wasn’t perfect and that some people he labelled as such would object to it. Nevertheless, because they offer no umbrella label for their movement or way of thinking, Florman noted that opposition to, or general discomfort with, technology was what motivated these critics. Hence, the label “antitechnologists.”

Florman surveyed a wide swath of technological critics from many different disciplines—philosophy, sociology, law, and other fields. He condensed their main criticisms into six general points:

  • Technology is a “thing” or a force that has escaped from human control and is spoiling our lives.
  • Technology forces man to do work that is tedious and degrading.
  • Technology forces man to consume things that he does not really desire.
  • Technology creates an elite class of technocrats, and so disenfranchises the masses.
  • Technology cripples man by cutting him off from the natural world in which he evolved.
  • Technology provides man with technical diversions which destroy his existential sense of his own being.[5]

No one else before this had ever crafted such a taxonomy of complaints from tech critics, and no one has done it better since Florman did so in 1976. In fact, it is astonishing how well Florman’s list continues to identify what motivates modern technology critics. New technologies have come and gone, but these same concerns tend to be brought up again and again. Florman’s books addressed and debunked each of these concerns in powerful fashion.

The Relentless Pessimism & Elitism of the Antitechnologists

Florman identified the way a persistent pessimism unifies antitechnologists. “Our intellectual journals are full of gloomy tracts that depict a society debased by technology,” he noted.[6] What motivated such gloom and doom? “It is fear. They are terrified by the scene unfolding before their eyes.”[7] He elaborated:

“The antitechnologists are frightened; they counsel halt and retreat. They tell the people that Satan (technology) is leading them astray, but the people have heard that story before. They will not stand still for vague promises of a psychic contentment that is to follow in the wake of voluntary temperance.”[8]

The antitechnologist’s worldview isn’t just relentlessly pessimistic but also highly elitist and paternalistic, Florman argued. He referred to it as “Platonic snobbery.”[9] The economist and political scientist Thomas Sowell would later call that snobbish attitude, “the vision of the anointed.”[10] Like Sowell, Florman was angered at the way critics stared down their noses at average folk and disregarded their values and choices:

“The antitechnologists have every right to be gloomy, and have a bounden duty to express their doubts about the direction our lives are taking. But their persistent disregard of the average person’s sentiments is a crucial weakness in their argument—particularly when they then ask us to consider the ‘real’ satisfactions that they claim ordinary people experienced in other cultures of other times.”[11]

Florman noted that critics commonly complain about “too many people wanting too many things,” but he noted that, “[t]his is not caused by technology; it is a consequence of the type of creature that man is.”[12] One can moralize all they want about supposed over-consumption or “conspicuous consumption,” but in the end, most of us strive to better our lives in various ways—including by working to attain things that may be out of our reach or even superfluous in the eyes of others.

For many antitechnologists and other social critics, only the noble search for truth and wisdom will suffice. Basically, everybody should just get back to studying philosophy, sociology, and other soft sciences. Modern tech critics, Forman said, fashion themselves as the intellectual descendants of Greek philosophers who believed that, “[t]he ideal of the new Athenian citizen was to care for his body in the gymnasium, reason his way to Truth in the academy, gossip in the agora, and debate in the senate. Technology was not deemed worthy of a free man’s time.”[13]

“It is not surprising to find philosophers recommending the study of philosophy as a way of life,” Florman noted amusingly.[14] But that does not mean all of us want (or even need) to devote our lives to such things. Nonetheless, critics often sneer at the choices made by the rest of us—especially when they involve the fruits of science and technology. “The most effective weapon in the arsenal of the antitechnologists is self-righteousness,” he noted,[15] and, “[a]s seen by the antitechnologists, engineers and scientists are half-men whose analysis and manipulation of the world deprives them of the emotional experiences that are the essence of the good life.”[16]

Indeed, it is not uncommon (both in the past and today) to see tech critics self-anoint themselves “humanists” and then suggest that anyone who thinks differently from them (namely, those who are pro-innovation) are the equivalent of anti-humanistic. I wrote about this in my 2018 essay, “Is It ‘Techno-Chauvinist’ & ‘Anti-Humanist’ to Believe in the Transformative Potential of Technology?” I argued that, “[p]roperly understood, ‘technology’ and technological innovation are simply extensions of our humanity and represent efforts to continuously improve the human condition. In that sense, humanism and technology are compliments, not opposites.”

But the critics remain fundamentally hostile to that notion and they often suggest that there is something suspicious about those who believe, along with Florman, that there is a symbiotic relationship between innovation, economic growth, pluralism, and human betterment. We rational optimists, the critics suggest, are simply too focused on crass, materialistic measures of happiness and human flourishing.

Florman observed this when noting how much grief he and fellow engineers and scientists got when engaging with critics. “Anyone who has attempted to defend technology against the reproaches of an avowed humanist soon discovers that beneath all the layers of reasoning—political, environmental, aesthetic, or moral—lies a deep-seated disdain for ‘the scientific view.’”[17]

Everywhere you look in the world of Science & Technology Studies (STS) today, you find this attitude at work. In fact, the field is perhaps better labelled Anti-Science & Technology Studies, or at least Science & Technology Skeptical Studies. For most STSers, the burden of proof lies squarely on scientists, engineers, and innovators who must prove to some (often undefined) higher authorities that their ideas and inventions will bring worth to society (however the critics measure worth and value, which is often very unclear). Until then, just go slow, the critics say. Better yet, consult your local philosophy department for a proper course of action!

The critics will retort that they are just looking out for society’s best interests and trying to counter that selfish, materialist side of humanity. Florman countered by noting how, “most people are in search of the good life—not ‘the goods life’ as [Lewis] Mumford puts it, although some goods are entailed—and most human desires are for good things in moderate amounts.”[18] Trying to better our lives through the creation and acquisition of new and better goods and services is just a natural and quite healthy human instinct to help us attain some ever-changing definition of whatever each of us considers “the good life.” “Something other than technology is responsible for people wanting to live in a house on a grassy plot beyond walking distance to job, market, neighbor, and school,” Florman responded.[19] We all want to “get ahead” and improve our lot in life. That’s not because technology forces the urge upon us. Rather, that urge comes quite naturally as part of a desire to improve our lot in life.

The Power of Nostalgia

I have spent a fair amount of time in my own writing documenting the central role that nostalgia plays in motivating technological criticism.[20] Florman’s books repeatedly highlighted this reality. “The antitechnologists romanticize the work of earlier times in an attempt to make it seem more appealing than work in a technological age,” he noted. “But their idyllic descriptions of peasant life do not ring true.”[21]

The funny thing is, it is hard to pin down the critics regarding exactly when the “golden era” or “good ‘ol days” were. But if there is one thing that they all agree on, it’s that those days have long passed us by. In a 2019 essay on “Four Flavors of Doom: A Taxonomy of Contemporary Pessimism,” philosopher Maarten Boudry noted:

“In the good old days, everything was better. Where once the world was whole and beautiful, now everything has gone to ruin. Different nostalgic thinkers locate their favorite Golden Age in different historical periods. Some yearn for a past that they were lucky enough to experience in their youth, while others locate utopia at a point farther back in time…”

Not all nostalgia is bad. Clay Routledge has written eloquently about how “nostalgia serves important psychological functions,” and can sometimes possess a positive character that strengthens individuals and society. But the nostalgia found in the works of tech critics is usually a different thing altogether. It is rooted in misery about the present and dread of the future—all because technology has apparently stolen away or destroyed all that was supposedly great about the past. Florman noted how, “the current pessimism about technology is a renewed manifestation of pastoralism,” that is typically rooted in historical revisionism about bygone eras.[22] Many critics engage in what rhetoricians call “appeals to nature” and wax poetic about the joys of life for Pre-Technological Man, who apparently enjoyed an idyllic life free of the annoying intrusions created by modern contrivances.

Such “good ol days” romanticism is largely untethered from reality. “For most of recorded history humanity lived on the brink of starvation,” Wall Street Journal columnist Greg Ip noted in a column in early 2019. Even a cursory review of history offers voluminous, unambiguous proof that the old days were, in reality, eras of abject misery. Widespread poverty, mass hunger, poor hygiene, disease, short lifespans, and so on were the norm. What lifted humanity up and improved our lot as a species is that we learned how to apply knowledge to tasks in a better way through incessant trial-and-error experimentation. Recent books by Hans Rosling,[23] Steven Pinker,[24] and many others[25] have thoroughly documented these improvements to human well-being over time.

The critics are unmoved by such evidence, preferring to just jump around in time and cherry-pick moments when they feel life was better than it is now. “Fond as they are of tribal and peasant life, the antitechnologists become positively euphoric over the Middle Ages,” Florman quipped.[26] Why? Mostly because the Middle Ages lacked the technological advances of modern times, which the critics loathe. But facts are pesky things, and as Florman insisted, “it is fair to go on to ask whether or not life was ‘better’ in these earlier cultures than it is in our own.”[27] “We all are moved to reverie by talk of an arcadian golden age,” he noted. “But when we awaken from this reverie, we realize that the antitechnologists have diverted us with half-truths and distortions.”[28]

The critics’ reverence for the old days would be humorous if it wasn’t rooted in an arrogant and dangerous belief that society can be somehow reshaped to resemble whatever preferred past the critics desire. “Recognizing that we cannot return to earlier times, the antitechnologists nevertheless would have us attempt to recapture the satisfactions of these vanished cultures,” Florman noted. “In order to do this, what is required is nothing less than a change in the nature of man.”[29] That is, the critics will insist that, “something must be done” (namely be forced from above via some grand design) to remake humans and discourage their inner homo faber desire to be an incessant tool-builder. But this is madness, Florman argued in one of the best passages from his work:

“we are beginning to realize that for mankind there will never be a time to rest at the top of the mountain. There will be no new arcadian age. There will always be new burdens, new problems, new failures, new beginnings. And the glory of man is to respond to his harsh fate with zest and ever-renewed effort.”[30]

If the critics had their way, however, that zest would be dampened and those efforts restrained in the name of recapturing some mythical lost age. This sort of “rosy retrospection bias” is all the more shocking coming, as it does, from learned people who should know a lot more about the actual history of our species and the long struggle to escape utter despair and destitution. Alas, as the great Scottish philosopher David Hume observed in a 1777 essay, “The humour of blaming the present, and admiring the past, is strongly rooted in human nature, and has an influence even on persons endued with the profoundest judgment and most extensive learning.”[31]

Why Invent? Homo Faber is our Nature

While taking on the critics and debunking their misplaced nostalgia about the past, Florman mounted a defense of engineers and innovators by noting that the need to tinker and create is in our blood. He began by noting how “the nature of engineering has been misconceived”[32] because, in a sense, we are all engineers and innovators to some degree.

Florman’s thinking was very much in line with Benjamin Franklin, who once noted, “man is a tool-making animal.” “Both genetically and culturally the engineering instinct has been nurtured within us,” Florman argued, and this instinct “was as old as the human race.”[33] “To be human is to be technological. When we are being technological we are being human—we are expressing the age-old desire of the tribe to survive and prosper.”[34] In fact, he claimed, it was no exaggeration to say that humans, “are driven to technological creativity because of instincts hardly less basic than hunger and sex.”[35] Had our past situation been as rosy as the critics sometimes suggest, perhaps we would have never bothered to fashion tools to escape those eras! It was precisely because humans wanted to improve their lives and the lives of their loved ones that we started crafting more and better tools. Flint and firewood were never going to suffice.

But our engineering instincts do not end with basic needs. “Engineering responds to impulses that go beyond mere survival: a craving for variety and new possibilities, a feeling for proportion—for beauty—that we share with the artist,” Florman argued.[36] In essence, engineering and innovation respond to both basic human needs and higher ones at every stage of “Maslow’s pyramid,” which describes a five-level hierarchy of human needs. This same theme is developed in Arthur Diamond’s recent book, Openness to Creative Destruction: Sustaining Innovative Dynamism. As Diamond argues, one of the most unheralded features of technological innovation is that, “by providing goods that are especially useful in pursuing a life plan full of challenging, worthwhile creative projects,” it allows each of us the pursue different conceptions of what we consider a good life.[37] But we are only able to do so by first satisfying our basic physiological needs, which innovation also handles for us.

Florman was frustrated that critics failed to understand this point and equally concerned that engineers and innovators had been cast as uncaring gadget-worshipers who did not see beauty and truth in higher arts and other more worldly goals and human values. That’s hogwash, he argued:

“What an ironic turn of events! For if ever there was a group dedicated to—obsessed with—morality, conscience, and social responsibility, it has been the engineering profession. Practically every description of the practice of engineering has stressed the concept of service to humanity.[38] [. . .] Even in an age of global affluence, the main existential pleasure of the engineer will always be to contribute to the well-being of his fellow man.”[39]

Engineers and innovators do not always set out with some grandiose design to change the world, although some aspire to do so. Rather, the “existential pleasures of engineering” that Florman described in the title of his most notable book comes about by solving practical day-to-day problems:

“The engineer does not find existential pleasure by seeking it frontally. It comes to him gratuitously, seeping into him unawares. He does not arise in the morning and say, ‘Today I shall find happiness.’ Quite the contrary. He arises and says, ‘Today I will do the work that needs to be done, the work for which I have been trained, the work which I want to do because in doing it I feel challenged and alive.’ Then happiness arrives mysteriously as a byproduct of his effort.”[40]

And this pleasure of getting practical work done is something that engineers and innovators enjoy collectively by coming together and using specialized skills in new and unique combinations. “[T]echnological progress depends upon a variety of skills and knowledge that are far beyond the capacity of any one individual,” he insisted. “High civilization requires a high degree of specialization, and it was toward high civilization that the human journey appears always to have been directed.”[41] Adam Smith could not have said it any better.

“Muddling Through”: Why Trial-and-Error is the Key to Progress

My favorite insights from Florman’s work relate to the way humans have repeatedly faced up to adversity and found ways to “muddle through.” This was the focus of an old essay of mine— “Muddling Through: How We Learn to Cope with Technological Change”—which argued that humans are a remarkably resilient species and that we regularly find creative ways to deal with major changes through constant trial-and-error experimentation and the learning that results from it.[42]

Florman made this same point far more eloquently long ago:

“We have been attempting to muddle along, acknowledging that we are selfish and foolish, and proceeding by means of trial and error. We call ourselves pragmatists. Mistakes are made, of course. Also, tastes change, so that what seemed desirable to one generation appears disagreeable to the next. But our overriding concern has been to make sure that matters of taste do not become matters of dogma, for that is the way toward violent conflict and tyranny. Trial and error, however, is exactly what the antitechnologists cannot abide.[43]

It is the error part of trial-and-error that is so vital to societal learning. “Even the most cautious engineer recognizes that risk is inherent in what he or she does,” Florman noted. “Over the long haul the improbable becomes the inevitable, and accidents will happen. The unanticipated will occur.”[44] But “[s]ometimes the only way to gain knowledge is by experiencing failure,” he correctly observed[45] “To be willing to learn through failure—failure that cannot be hidden—requires tenacity and courage.”[46]

I’ve argued that this represents the central dividing line between innovation supporters and technology critics. The critics are so focused on risk-adverse, precautionary principle-based thinking that they simply cannot tolerate the idea that society can learn more through trial-and-error than through preemptive planning. They imagine it is possible to override that process and predetermine the proper course of action to create a safer, more stable society. In this mindset, failure is to be avoided at all costs through prescriptions and prohibitions. Innovation is to be treated as guilty until proven innocent in the hope of eliminating the error (or risk / failure) associated with trial-and-error experiments. To reiterate, this logic misses the fact that the entire point of trial-and-error is to learn from our mistakes and “fail better” next time, until we’ve solved the problem at hand entirely.[47]

Florman noted that, “sensible people have agreed that there is no free lunch; there are only difficult choices, options, and trade-offs.”[48] In other words, precautionary controls come at a cost. “All we can do is do the best we can, plan where we can, agree where we can, and compromise where we must,” he said.[49] But, again, the antitechnologists absolutely cannot accept this worldview. They are fundamentally hostile to it because they either believe that a precautionary approach will do a better job improving public welfare, or they believe that trial-and-error fails to safeguard any number of other values or institutions that they regard as sacrosanct. This shuts down the learning process from which wisdom is generated. As the old adage goes, “nothing ventured, nothing gained.” There can be no reward without some risk, and there can be no human advances without unless we are free to learn from the error portion of trial-and-error.

The Costs of Precautionary Regulation

Florman did not spend much time in his writing mulling over the finer points of public policy, but he did express skepticism about our collective ability to define and enforce “the public interest” in various contexts. A great many regulatory regimes—and their underlying statutes—rest on the notion of “protecting the public interest.” It is impossible to be against that notion, but it is often equally impossible to define what it even means.[50]

This leads to what Florman called, “the search for virtues that nobody can define”[51] “As engineers we are agreed that the public interest is very important; but it is folly to think that we can agree on what the public interest is. We cannot even agree on the scientific facts!”[52] This is especially true today in debates over what constitutes “responsible innovation” or “ethical innovation.”[53] What Florman noted about such conversations three decades ago is equally true today:

“Whenever engineering ethics is on the agenda, emotions come quickly to a boil. […] “It is oh so easy to mouth clichés, for example to pledge to protect the public interest, as the various codes of engineering ethics do. But such a pledge is only a beginning and hardly that. The real questions remain: What is the public interest, and how is it to be served?”[54]

That reality makes it extremely difficult to formulate consensus regarding public polices for emerging technologies. And it makes it particularly difficult to define and enforce a “precautionary principle” for emerging technologies that will somehow strike the Goldilocks balance of getting things just right. This was the focus of my 2016 book Permissionless Innovation, which argued that the precautionary principle should be the last resort when contemplating innovation policy. Experimentation with new technologies and business models should generally be permitted by default because, “living in constant fear of worst-case scenarios—and premising public policy on them—means that best-case scenarios will never come about,” I argued. The precautionary principle should only be tapped when the harms alleged to be associated with a new technology are highly probable, tangible, immediate, irreversible, catastrophic, or directly threatening to life and limb in some fashion.

For his part, Florman did not want to get his defense of engineering mixed up with politics and regulatory considerations. Engineers and technologists, he noted, come in many flavors and supported many different causes. Generally speaking, they tend to be quite pragmatic and shun strong ideological leanings and political pronouncements.

Of course, at some point, there is no avoiding this fight; one must comment on how to strike the right balance when politics enter the picture and threatens to stifle technological creativity. Florman’s perspectives on regulatory policy were somewhat jumbled, however. On one hand, he expressed concern about excessive and misguided regulations, but he also saw government playing an important role both in supporting various types of engineering projects and regulating certain technological developments:

“The regulatory impulse, running wild, wreaks havoc, first of all by stifling creative and productive forces that are vital to national survival. But it does harm also—and perhaps more ominously—by fomenting a counter-revolution among outraged industrialists, the intensity of which threatens to sweep away many of the very regulations we most need.”[55]

In his 1987 book, The Civilized Engineer, Florman even expressed surprise and regret about growing pushback against regulation during the Reagan years. He also expressed skepticism about “the deceptive allure” of benefit-cost analysis, which was on the rise at the time, saying that the “attempt to apply mathematical consistency to the regulatory process was deplorably simplistic.”[56] I have always been a big believer in the importance of benefit-cost analysis (BCA), so I was surprised to read of Florman’s skepticism of it. But he was writing in the early days of BCA and it was not entirely clear how well it work in practice. Four decades on, BCA has become far more rigorous, academically respected, and well-established throughout government. It has widespread and bipartisan support as a policy evaluation tool.

Florman adamantly opposed any sort of “technocracy”—or administration of government by technically-skilled elites. He thought it was silly that so many tech critics believe that such a thing already existed. “The myth of the technocratic elite is an expression of fear, like a fairy tale about ogres,” he argued. “It springs from an understandable apprehension, but since it has no basis in reality, it has no place in serious discourse.”[57] Nor did he believe that there was any real chance a technocracy would ever take hold. “No matter how complex technology becomes, and no matter how important it turns out to be in human affairs, we are not likely to see authority vested in a class of technocrats.”[58]

Florman hoped for wiser administration of law and regulations that affected engineering endeavors and innovation more generally. Like so many others, he did not necessarily want more law, just better law. One cannot fault that instinct, but Florman was not really interested in fleshing out the finer details of policy about how to accomplish that objective. He preferred instead to use history as a rough guide for policy. From the fall of the Roman Empire to the decline of Britain’s economic might in more recent times, Florman observed the ways in which societal and governmental attitudes toward innovation influenced the relative growth of science, technology, and national economies. In essence, he was explaining how “innovation culture” and “innovation arbitrage” had been realities for far longer than most people realize.[59]

“Where the entrepreneurial spirit cannot be rewarded, and where non-productive workers cannot be discharged, stagnation will set in,” Florman concluded.[60] This is very much in line with the thinking of economic historians like Joel Mokyr[61] and Deirdre McCloskey,[62] who have identified how attitudes toward creativity and entrepreneurialism affect the aggregate innovative capacity of nations, and thus their competitive advantage and relative prosperity in the world.

Debunking Determinism, Anxiety & Alienation Concerns

One of the ironies of modern technological criticism is the way many critics can’t seem to get their story straight when it comes to “technological determinism” versus social determinism. In the extreme view, technological determinism is the idea that technology drives history and almost has a will of its own. It is like an autonomous force that is practically unstoppable. By contrast, social determinism means that society (individuals, institutions, etc.) guide and control the development of technology.

In the field of Science and Technology Studies, technological determinism is a very hot matter. Academic and social critics are fond of painting innovation advocates as rigid tech determinists who are little better than uncaring anti-humanistic gadget-worshipers. The critics have employed a variety of other creative labels to describe tech determinism, including: “techno-fundamentalism,” “technological solutionism,” and even “techno-chauvinism.”

Engineers and other innovators often get hit with such labels and accused of being rigid technological determinists who just want to see tech plow over people and politics. But this was, and remains, a ridiculous argument. Sure, there will always be some wild-eyed futurists and extropian extremists who make preposterous claims about how “there is no stopping technology.” “Even now the salvation-through-technology doctrine has some adherents whose absurdities have helped to inspire the antitechnological movement, Florman said.”[63] But that hardly represents the majority of innovation supporters, who well understand that society and politics play a crucial role in shaping the future course of technological development.

As Florman noted, we can dismiss extreme deterministic perspectives for a rather simple reason: technologies fail all the time! “If promising technologies can suffer fatal blows from unexpected circumstances,” Florman correctly argued, then “[t]his means that we are still—however precariously—in control of our own destiny.”[64] He believed that, “technology is not an independent force, much less a thing, but merely one of the types of activities in which people engage.”[65] The rigid view of tech determinism can be dismissed, he said, because “it can be shown that technology is still very much under society’s control, that it is in fact an expression of our very human desires, fancies, and fears.”[66]

But what is amazing about this debate is that some of the most rigid technological determinists are the technology critics themselves! Recall how Florman began his 6-part taxonomy of common complaints from tech critics. “A primary characteristic of the antitechnologists,” Florman argued, “is the way in which they refer to ‘technology’ as a thing, or at least a force, as if it had an existence of its own” and which “has escaped from human control and is spoiling our lives.”[67]

He noted that many of the leading tech critics of the post-war era often spoke in remarkably deterministic ways. “The idea that a man of the masses has no thoughts of his own, but is something on the order of a programmed machine, owes part of its popularity with the antitechnologists to the influential writings of Herbert Marcuse,” he believed.[68] But then such thinking accelerated and gained greater favor with the popularity of critics like French philosopher Jacques Ellul, American historian Lewis Mumford, and American cultural critic Neil Postman.

Their books painted a dismal portrait of a future in which humans were subjugated to the evils of “technique” (Ellul), “technics” (Mumford), or “technopoly” (Postman).  The narrative of their works read like dystopian science fiction. Essentially, there was no escaping the iron grip that technology had on us. Postman claimed, for example, that technology was destined to destroy “the vital sources of our humanity” and lead to “a culture without a moral foundation” by undermining “certain mental processes and social relations that make human life worth living.”

Which gets us to commonly heard concerns about how technology leads to “anxiety” and “alienation.” “Having established the view of technology as an evil force, the antitechnologists then proceed to depict the average citizen as a helpless slave, driven by this force to perform work he detests,” Florman notes.[69] “Anxiety and alienation are the watchwords of the day, as if material comforts made life worse, rather than better.”[70]

These concerns about anxiety, alienation, and “dehumanization” are omnipresent in the work of modern tech critics, and they are also tied up with traditional worries about “conspicuous consumption.” It’s all part of the “false consciousness” narrative they also peddle, which basically views humans as too ignorant to look out for their own good. In this worldview, people are sheep being led to the slaughter by conniving capitalists and tech innovators, who are just trying to sell them things they don’t really need.

Florman pointed out how preposterous this line of thinking is when he noted how critics seem to always forget that, “a basic human impulse precedes and underlies each technological development”:[71]

“Very often this impulse, or desire, is directly responsible for the new invention. But even when this is not the case, even when the invention is not a response to any particular consumer demand, the impulse is alive and at the ready, sniffing about like a mouse in a maze, seeking its fulfillment. We may regret having some of these impulses. We certainly regret giving expression to some of them. But this hardly gives us the right to blame our misfortunes on a devil external to ourselves.”[72]

Consider the automobile, for example. Industrial era critics often focused on it and lambasted the way they thought industrialists pushed auto culture and technologies on the masses. Did we really need all those cars? All those colors? All those options? Did we really even need cars? The critics wanted us to believe that all these things were just imposed upon us. We were being force-fed options we really didn’t even need or want. “Choice” in this worldview is just a fiction; a front for the nefarious ends of our corporate overlords.

Florman demolished this reasoning throughout his books. “However much we deplore the growth of our automobile culture, clearly it has been created by people making choices, not by a runaway technology,” he argued.[73] Consumer demand and choice is not some fiction fabricated and forced upon us, as the antitechnologists suggest. We make decisions. “Those who would blame all of life’s problems on an amorphous technology, inevitably reject the concept of individual responsibility,” Florman retorted. “This is not humanism. It is a perversion of the humanistic impulse.”[74]

A modern tweak on the conspicuous consumption and false consciousness arguments is found in the work of leading tech critics like Evgeny Morozov, who pens attention-grabbing screeds decrying what he regards as “the folly of technological solutionism.” Morozov bluntly states that “our enemy is the romantic and revolutionary problem solver who resides within” of us, but most specifically within the engineers and technologists.[75]

But would the world really be better place it tinkerers didn’t try to scratch that itch?[76] In 2021, the Wall Street Journal profiled JoeBen Bevirt, an engineer and serial entrepreneur who has been working to bring flying cars from sci-fi to reality. Channeling Florman’s defense of the existential pleasures associated with engineering, Bevirt spoke passionately about the way innovators can help “move our species forward” through their constant tinkering to find solutions to hard problems. “That’s kind of the ethos of who we are,” he said. “We see problems, we’re engineers, we work to try to fix them.”[77]

When tech critics like Morozov decry “solutionism,” they are essentially saying that innovators like Bevirt need to just shut up and sit down. Don’t try to improve the world through tinkering; just settle for the status quo, the critics basically state. That’s the kiss of death for human progress, however, because it is only through incessant experimentation with the new and different approaches to hard problems that we can advance human well-being. “Solutionism” isn’t about just creating some shiny new toy; it’s about expanding the universe of potentially life-enriching and life-saving technologies available to humanity.

Conclusion

This review of Samuel Florman’s work may seem comprehensive, but it only scratches the surface of his wide-ranging writing. Florman was troubled that engineering lacked support or at least understanding. Perhaps that was because, he reasoned, that “[t]here is no single truth that embodies the practice of engineering, no patron saint, no motto or simple credo. There is no unique methodology that has been distilled from millenia of technological effort.”  Or, more simply, it may also be the case that the profession lacked articulate defenders. “The engineer may merely be waiting for his Shakespeare,” he suggested.[78]

Through his life’s work, however, Samuel Florman became that Shakespeare; the great bard of engineering and passionate defender of technological innovation and rational optimism more generally. In looking for a quote or two to close out my latest book, I ended with this one from Florman:

“By turning our backs on technological change, we would be expressing our satisfaction with current world levels of hunger, disease, and privation. Further, we must press ahead in the name of the human adventure. Without experimentation and change our existence would be a dull business.”[79]

Let us resolve to make sure that Florman’s greatest fear does not come to pass. Let us resolve to make sure that the great human adventure never ends. And let us resolve to counter the antitechnologists and their fundamentally anti-humanist worldview, which would most assuredly make our existence the “dull business” that Florman dreaded.

We can do better when we put our minds and hands to work innovating in an attempt to build a better future for humanity. Samuel Florman, the great prophet of progress, showed us the way forward.

 

Additional Reading from Adam Thierer:

 

Endnotes:

[1]    Matt Ridley, The Rational Optimist: How Prosperity Evolves (New York: Harper Collins, 2010).

[2]    Adam Thierer, “Defending Innovation Against Attacks from All Sides,” Discourse, November 9, 2021, https://www.discoursemagazine.com/ideas/2021/11/09/defending-innovation-against-attacks-from-all-sides.

[3]    Samuel C. Forman, The Civilized Engineer (New York: St. Martin’s Griffin, 1987), p. 26.

[4]    Samuel C. Florman, The Existential Pleasures of Engineering (New York, St. Martins Griffin, 2nd Edition, 1994), p. 53-4.

[5]    Existential Pleasures of Engineering, p. 53-4.

[6]    Samuel C. Florman, Blaming Technology: The Irrational Search for Scapegoats (New York: St. Martin’s Press, 1981), p. 186.

[7]    Existential Pleasures of Engineering, p. 76.

[8]    Existential Pleasures of Engineering, p. 77.

[9]    The Civilized Engineer, p. 38.

[10]   Thomas Sowell, The Vision of the Anointed: Self-Congratulation as a Basis for Social Policy (New York: Basic Books, 1995).

[11]   Existential Pleasures of Engineering, p. 72.

[12]   Existential Pleasures of Engineering, p. 76.

[13]   The Civilized Engineer, p. 35.

[14]   Existential Pleasures of Engineering, p. 102.

[15]   Blaming Technology, p. 162.

[16]   Existential Pleasures of Engineering, p. 55.

[17]   Blaming Technology, p. 70.

[18]   Existential Pleasures of Engineering, p. 77.

[19]   Existential Pleasures of Engineering, p. 60.

[20]   Adam Thierer, “Technopanics, Threat Inflation, and the Danger of an Information Technology Precautionary Principle,” Minnesota Journal of Law, Science & Technology 14, no. 1 (2013), p. 312–50, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2012494.

[21]   Existential Pleasures of Engineering, p. 62.

[22]   Blaming Technology, p. 9.

[23]   Hans Rosling, Factfulness: Ten Reasons We’re Wrong about the World—and Why Things Are Better Than You Think (New York: Flatiron Books, 2018).

[24]   Steven Pinker, Enlightenment Now: The Case for Reason, Science, Humanism, and Progress (New York: Viking, 2018).

[25]   Gregg Easterbrook, It’s Better than It Looks: Reasons for Optimism in an Age of Fear (New York: Public Affairs, 2018); Michael A. Cohen & Micah Zenko, Clear and Present Safety: The World Has Never Been Better and Why That Matters to Americans (New Haven, CT: Yale University Press, 2019).

[26]   Existential Pleasures of Engineering, p. 54.

[27]   Existential Pleasures of Engineering, p. 72.

[28]   Existential Pleasures of Engineering, p. 72.

[29]   Existential Pleasures of Engineering, p. 55.

[30]   Existential Pleasures of Engineering, p. 117.

[31]   David Hume, “Of the Populousness of Ancient Nations,” (1777), https://oll.libertyfund.org/titles/hume-essays-moral-political-literary-lf-ed.

[32]   The Civilized Engineer, p. 20.

[33]   Existential Pleasures of Engineering, p. 6.

[34]   The Civilized Engineer, p. 20.

[35]   Existential Pleasures of Engineering, p. 115.

[36]   The Civilized Engineer, p. 20.

[37]   Arthur Diamond, Openness to Creative Destruction: Sustaining Innovative Dynamism (Oxford: Oxford University Press, 2019).

[38]   Existential Pleasures of Engineering, p. 19.

[39]   Existential Pleasures of Engineering, p. 147.

[40]   Existential Pleasures of Engineering, p. 148.

[41]   The Civilized Engineer, p. 30.

[42]   Adam Thierer, “Muddling Through: How We Learn to Cope with Technological Change,” Medium, June 30, 2014, https://medium.com/tech-liberation/muddling-through-how-we-learn-to-cope-with-technological-change-6282d0d342a6.

[43]   Existential Pleasures of Engineering, p. 84.

[44]   The Civilized Engineer, p. 71.

[45]   The Civilized Engineer, p. 72.

[46]   The Civilized Engineer, p. 72.

[47]   Adam Thierer, “Failing Better: What We Learn by Confronting Risk and Uncertainty,” in Sherzod Abdukadirov (ed.), Nudge Theory in Action: Behavioral Design in Policy and Markets (Palgrave Macmillan, 2016): 65-94.

[48]   The Civilized Engineer, p. xi.

[49]   Existential Pleasures of Engineering, p. 85.

[50]   Adam Thierer, “Is the Public Served by the Public Interest Standard?” The Freeman, September 1, 1996,  https://fee.org/articles/is-the-public-served-by-the-public-interest-standard.

[51]   The Civilized Engineer, p. 84.

[52]   The Existential Pleasures of Engineering, p. 22.

[53]   Adam Thierer, “Are ‘Permissionless Innovation’ and ‘Responsible Innovation’ Compatible?” Technology Liberation Front, July 12, 2017, https://techliberation.com/2017/07/12/are-permissionless-innovation-and-responsible-innovation-compatible.

[54]   The Civilized Engineer, p. 79.

[55]   Blaming Technology, p. 106.

[56]   The Civilized Engineer, p. 158.

[57]   Blaming Technology, p. 41.

[58]   Blaming Technology, p. 40-1.

[59]   Adam Thierer, “Embracing a Culture of Permissionless Innovation,” Cato Online Forum, November 17, 2014, https://www.cato.org/publications/cato-online-forum/embracing-culture-permissionless-innovation; Christopher Koopman, “Creating an Environment for Permissionless Innovation,” Testimony before the US Congress Joint Economic Committee, May 22, 2018, https://www.mercatus.org/publications/creating-environment-permissionless-innovation.

[60]   The Civilized Engineer, p. 117.

[61]   Joel Mokyr, Lever of Riches: Technological Creativity and Economic Progress (New York: Oxford University Press, 1990).

[62]   Deirdre N. McCloskey, The Bourgeois Virtues: Ethics for an Age of Commerce (Chicago: The University of Chicago Press, 2006); Deirdre N. McCloskey, Bourgeois Dignity: Why Economics Can’t Explain the Modern World (Chicago: The University of Chicago Press. 2010).

[63]   Existential Pleasures of Engineering, p. 57.

[64]   Blaming Technology, p. 22.

[65]   The Existential Pleasures of Engineering, p. 58.

[66]   Blaming Technology, p. 10.

[67]   The Existential Pleasures of Engineering, p. 48, 53.

[68]   Existential Pleasures of Engineering, p. 70.

[69]   Existential Pleasures of Engineering, p. 49.

[70]   Existential Pleasures of Engineering, p. 16.

[71]   Existential Pleasures of Engineering, p. 61.

[72]   Existential Pleasures of Engineering, p. 61.

[73]   Existential Pleasures of Engineering, p. 60.

[74]   Blaming Technology, p. 104.

[75]   Evgeny Morozov, To Save Everything, Click Here: The Folly of Technological Solutionism (New York: Public Affairs, 2013).

[76]   Adam Thierer, “A Net Skeptic’s Conservative Manifesto,” Reason, April 27, 2013, https://reason.com/2013/04/27/a-net-skeptics-conservative-manifesto-2/.

[77]   Emily Bobrow, “JoeBen Bevirt Is Bringing Flying Taxis from Sci-Fi to Reality,” Wall Street Journal, July 9, 2021, https://www.wsj.com/articles/joeben-bevirt-is-bringing-flying-taxis-from-sci-fi-to-reality-11625848177.

[78]   Existential Pleasures of Engineering, p. 96.

[79]   Blaming Technology, p. 193.

]]> https://techliberation.com/2022/04/06/samuel-florman-the-continuing-battle-over-technological-progress/feed/ 4 76961 Podcast: What’s Wrong with Industrial Policy? https://techliberation.com/2022/02/18/podcast-whats-wrong-with-industrial-policy/ https://techliberation.com/2022/02/18/podcast-whats-wrong-with-industrial-policy/#comments Fri, 18 Feb 2022 15:54:29 +0000 https://techliberation.com/?p=76954

I recently joined Rep. Dan Crenshaw on his Hold These Truths podcast to discuss, “What’s Wrong with Industrial Policy.” We chatted for 25 minutes about a wide range of issues related to the the growing push for grandiose industrial policy schemes in the US, including the massive new 3,000-page, $350 billion “COMPETES Act” legislation that recently passed in the House and which will soon be conferenced with a Senate bill that already passed.

On the same day this podcast was released this week, I also had a new op-ed appear in  The Hill on “The Coming Industrial Policy Hangover.” In both that essay and the podcast with Rep. Crenshaw, I stress that, beyond all the other problems with these new industrial policy measures, no one is talking about the fiscal cost of it all. As I note:

In the rush to pass legislation, we’ve barely heard a peep about the $250-$350 billion price tag. This follows a massive splurge of recent government borrowing, which led to the U.S. national debt hitting another lamentable new record: $30 trillion. China already owns over $1 trillion of that debt, making one wonder if we’re really countering China by adopting a massive, new and unfunded industrial policy that they will end up financing indirectly.

Read my oped for more details and for a deeper dive of what’s wrong with the bills, see my earlier essay here on “Thoughts on the America COMPETES Act: The Most Corporatist & Wasteful Industrial Policy Ever.”

Additional Reading from Adam Thierer on Industrial Policy:

]]> https://techliberation.com/2022/02/18/podcast-whats-wrong-with-industrial-policy/feed/ 1 76954 The Precautionary Principle: A Plea for Proportionality https://techliberation.com/2022/02/07/the-precautionary-principle-a-plea-for-proportionality/ https://techliberation.com/2022/02/07/the-precautionary-principle-a-plea-for-proportionality/#comments Mon, 07 Feb 2022 19:57:03 +0000 https://techliberation.com/?p=76949

Gabrielle Bauer, a Toronto-based medical writer, has just published one of the most concise explanations of what’s wrong with the precautionary principle that I have ever read. The precautionary principle, you will recall, generally refers to public policies that limit or even prohibit trial-and-error experimentation and risk-taking. Innovations are restricted until their creators can prove that they will not cause any harms or disruptions. In an essay for The New Atlantis entitled, “Danger: Caution Ahead,” Bauer uses the world’s recent experiences with COVID lockdowns as the backdrop for how society can sometimes take extreme caution too far, and create more serious dangers in the process. “The phrase ‘abundance of caution’ captures the precautionary principle in a more literary way,” Bauer notes. Indeed, another way to look at it is through the prism of the old saying, “better to be safe than sorry.” The problem, she correctly observes, is that, “extreme caution comes at a cost.” This is exactly right and it points to the profound trade-offs associated with precautionary principle thinking in practice.

In my own writing about the problems associated with the precautionary principle (see list of essays at bottom), I often like to paraphrase an ancient nugget of wisdom from St. Thomas Aquinas, who once noted in his Summa Theologica that, if the highest aim of a captain were merely to preserve their ship, then they would simply keep it in port forever. Of course, that is not the only goal of a captain has. The safety of the vessel and the crew is essential, of course, but captains brave the high seas because there are good reasons to take such risks. Most obviously, it might be how they make their living. But historically, captains have also taken to the seas as pioneering explorers, researchers, or even just thrill-seekers.

This was equally true when humans first decided to take to the air in balloons, blimps, airplanes, and rockets. A strict application of the precautionary principle would have instead told us we should keep our feet on the ground. Better to be safe than sorry! Thankfully, many brave souls ignored that advice and took the heavens in the spirit of exploration and adventure. As Wilbur Wright once famously said, “If you are looking for perfect safety, you would do well to sit on a fence and watch the birds.” Needless to say, humans would have never mastered the skies if the Wright brothers (and many others) had not gotten off the fence and taken the risks they did.

Opportunity Costs Matter

Here we get to the true danger of strict versions of the precautionary principle: It essentially becomes a crime to get off the fence and do anything risky at all. This sets up the potential for stasis and stagnation as societal learning is severely curtailed. Progress becomes harder because there can be no reward without some risk. — both individually or societally. “Caution makes sense except when it doesn’t,” Bauer notes. She continues on to note:

Used too liberally, the precautionary principle can keep us stuck in a state of extreme risk-aversion, leading to cumbersome policies that weigh down our lives. To get to the good parts of life, we need to accept some risk.

As I argued in a book on these issues, the root problem with precautionary principle thinking is that “living in constant fear of worst-case scenarios—and premising public policy on them—means that best-case scenarios will never come about.” If societal attitudes and public policy will not tolerate the idea of any error resulting from experimentation with new and better ways of doing things, then we will obviously not get many new and better things! Scientist Martin Rees refers to this truism about the precautionary principle as “the hidden cost of saying no.”

The opportunity cost of inaction or stasis can be hard to quantify but imagine if we organized our entire society around a rigid application of the precautionary principle. Bauer notes that this is basically what we did during COVID. And the results are in. “It’s far past time we ask ourselves when  abundance really means excess, when our precautionary measures against Covid have gone too far, when we have ignored the costs and lost all sense of proportionality.” Unfortunately, the precautionary mindset–which is always rooted in fear of the unknown–took control. As Bauer notes:

It should have been socially acceptable to debate the merits of these tradeoffs, with nuance and without censure. But that is not what happened. Early in the pandemic, an unspoken rule — thou shalt not question the costs — sprang up and stifled discourse.

“And here’s the worst of it: the costs of excess caution can persist long after the initial danger has passed,” she notes. “It’s no different with Covid: our knee-jerk caution may have downstream effects that persist after the virus has ceased to be a threat.” She cites many compelling examples of the negative effects associated with extreme precautionary thinking during COVID, noting how, “[t]he impact of travel and trade restrictions on food security and childhood vaccination in developing countries will likely reverberate for decades.” Moreover:

The Covid-19 pandemic has laid bare the risks of extreme protection: lost businesses, lost livelihoods, lost graduations, lost loves, lost goodbyes; the loss of personal agency over life’s most intimate and meaningful moments; the loss, quite possibly, of our cherished principles of liberal democracy. A recent report by International IDEA, a democracy advocacy organization, concluded that many countries had become more authoritarian as they took steps to contain the pandemic.

This list of lockdown trade-offs goes on and the aggregate costs will be staggering once economists and others get around to better estimating them. As noted, gauging those costs will be challenging because of the many variables and values that come into play. But it remains vital that society takes risk analysis and trade-offs more seriously so that we don’t make these mistakes again and again.

Proportionality is the Key

Toward that end, Bauer makes “a plea for proportionality.” She wants society to strike a more reasonable balance when it comes to policy measures that might block actions and research that could help us better understand how to deal with risk uncertainties. Accordingly, “we must understand when to apply the precautionary principle and when to move on from it.”

“The precautionary principle doesn’t come with such checks and balances. On the contrary, it tends to perpetuate itself and acquire a life of its own,” she notes. In other words, once set in place initially for a given issue or sector, precautionary principle thinking tends to grow like bad weeds until it has taken over everything in sight. (To see the consequences of that in fields like aviation, space, nanotech, and others, please check out J. Storrs Hall’s amazing new book, Where Is My Flying Car?)

Of course, proportionality cuts both ways, and as I noted in my last two books, there are some instances in which at least a light version of the precautionary principle should be preemptively applied, but they are limited to scenarios where the threat in question is tangible, immediate, irreversible, and catastrophic in nature. In such cases, I argue, society might be better suited thinking about when an “anti-catastrophe principle” is needed, which narrows the scope of the precautionary principle and focuses it more appropriately on the most unambiguously worst-case scenarios that meet those criteria. Generally speaking, however, this test is not satisfied in the vast majority of cases. “Innovation Allowed” should be our default principle. 

Conclusion

The single most important thing that we must always remember when debating precautionary principle-based policies is that, just because someone has good intentions and claims safety as their goal, that does not automatically make the world a safer place. To repeat: Excessive safety-related measure can result in less safety overall. Or again, as Bauer says, “extreme caution comes at a cost.”

No one ever summarized this truism more clearly than the great political scientist Aaron Wildavsky, who devoted much of his life’s work to proving how efforts to create a risk-free society would instead lead to an extremely unsafe society. In his 1988 book, Searching for Safety, Wildavsky warned of the dangers of “trial without error” reasoning, and contrasted it with the trial-and-error method of evaluating risk and seeking wise solutions to it. He argued that wisdom is born of experience and that we can learn how to be wealthier and healthier as individuals and a society only by first being willing to embrace uncertainty and even occasional failure. Here was the crucial takeaway:

The direct implication of trial without error is obvious: If you can do nothing without knowing first how it will turn out, you cannot do anything at all. An indirect implication of trial without error is that if trying new things is made more costly, there will be fewer departures from past practice; this very lack of change may itself be dangerous in forgoing chances to reduce existing hazards. . . . Existing hazards will continue to cause harm if we fail to reduce them by taking advantage of the opportunity to benefit from repeated trials.

Trial and error is the basis of all societal learning, and without it, humanity will be less safe and less prosperous over the long run. Gabrielle Bauer’s new essay captures that insight better than anything I’ve read since Wildavsky was writing about the dangers of the precautionary principle. I beg you to jump over to New Atlantis and read her entire article. It’s absolutely essential.

Additional reading from Adam Thierer on the precautionary principle

]]> https://techliberation.com/2022/02/07/the-precautionary-principle-a-plea-for-proportionality/feed/ 6 76949 Thoughts on the America COMPETES Act: The Most Corporatist & Wasteful Industrial Policy Ever https://techliberation.com/2022/01/26/thoughts-on-the-competes-act-the-most-corporatist-wasteful-industrial-policy-ever/ https://techliberation.com/2022/01/26/thoughts-on-the-competes-act-the-most-corporatist-wasteful-industrial-policy-ever/#comments Wed, 26 Jan 2022 19:37:24 +0000 https://techliberation.com/?p=76942

On Tuesday, Nancy Pelosi, Speaker of the U.S. House of Representatives, posted the text of the “America Creating Opportunities for Manufacturing, Pre-Eminence in Technology and Economic Strength Act of 2022,” or “The America COMPETES Act.” As far as industrial policy measures go, the COMPETES Act is one of the most ambitious and expensive central planning efforts in American history. It represents the triumph of top-down, corporatist, techno-mercantilist thinking over a more sensible innovation policy rooted in bottom-up competition, entrepreneurialism, private investment, and free trade.

Unprecedented Planning & Spending

First, the ugly facts: The full text of the COMPETES Act weighs in at a staggering 2,912 pages. A section-by-section “summary” of the measure takes up 109 pages alone. Even the shorter “fact sheet” for the bill is 20 pages long. It is impossible to believe that anyone in Congress has read every provision of this bill. It will be another case of having “to pass the bill so you can find out what’s in it,” as Speaker Pelosi once famously said about another mega-measure.

Of course, a mega bill presents major opportunities for lawmakers to sneak in endless gobs of pork and unrelated policy measures they can’t find any other way to get through Congress. The Senate already passed a similar 2,600-page companion measure last summer, “The U.S. Innovation and Competition Act.” Lawmakers loaded up that measure with so much pork and favors for special interests that Sen. John N. Kennedy (R-La.) labelled the effort an “orgy of spending porn.” Like that effort, the new COMPETES Act includes $52 billion to boost domestic semiconductor production as well as $45 billion in grants and loans to address supply chain issues.

But there are billions allocated for other initiatives, as well as countless provisions addressing other technologies and sectors. The list is seemingly endless and includes: 5G mobile networks, biometrics, quantum information science, “the development of safe and trustworthy artificial intelligence and data science,” cybersecurity literacy, drone security, microelectronics, electronic waste, genomics, isotope development, and the Large Hadron Collider and high intensity lasers, among many other things. The measure also proposes a broad array of Green New Deal-esque efforts focused on things like: biometrology, climate and Earth modeling, deforestation and overfishing / “driftnet” fishing matters, marine mammal research, solar energy, bioenergy, the creation of a National Engineering Biology Research and Development Initiative and a Regional Clean Energy Innovation Program at the Department of Energy, clean water programs, a national clean energy incubator program, and helium conservation, again among many other things. There are even provisions addressing the trading of shark fins and almost 70 pages of provisions on coral reef conservation.

A Sweeping Macroeconomic Planning Exercise

There are more sweeping macroeconomic provisions and mandates in the bill. For example, the COMPETES Act would create a new “national supply chain database,” as well as a Supply Chain Resiliency and Crisis Response Office in the Department of Commerce, while also requiring the Director of White House Office of Science & Technology Policy to develop and submit to Congress a 4-year comprehensive national S&T strategy. The measure also includes trade adjustment assistance for workers, firms, and farmers and even provisions dealing with currency undervaluation. There are also many provisions addressing drug manufacturing and medical supply chain issues. There are even proposed expansions of federal antitrust power. (Apparently, once America’s grandiose industrial policies magically create global powerhouses in every sector, we’ll need expanding antitrust action to tear them all down and start all over again! Meanwhile, perhaps the greatest irony of the new industrial policy efforts is that, while lawmakers are falling all over themselves to shower corporate America with hundreds of billions of taxpayer dollars, policymakers are simultaneously on a regulatory and antitrust jihad against many successful tech companies with bills that would break them up or destroy their business models.)

Perhaps most radically, the measure includes a 25-page section proposing a sweeping new “National Critical Capabilities Review” process to oversee outbound investments. Covington lawyers noted that, if such a regulatory regime is enacted, “the United States would become the first major Western advanced economy to adopt a broad-gauged outbound investment screening process, raising the prospect of a new era in national security-based reviews and restrictions of international investment flows.”

Finally, the COMPETES Act includes a huge assortment of other national security and foreign policy-related provisions, most of which focus on countering China in some fashion. “There’s a lot of Cold War-style influence mongering happening here,” says Reason’s Elizabeth Nolan Brown, including programs that sound like they could have been concocted by the CIA, such as the bill’s “Countering China’s Educational and Cultural Diplomacy in Latin America” initiative. But there is also a lot of language here addressing other regions or countries, including: Oceania, Africa, the Arctic, the Middle East, Iran, Hong Kong, Taiwan, and others.

The relationship of most of these provisions to U.S. industrial competitiveness is tenuous to say the least. Nonetheless, those provisions take up a huge amount of space in this nearly 3,000-page industrial policy measure and may end up complicating its passage.

A Chicken in Every Pot

The inclusion of “Regional Technology and Innovation Hubs” in the bill deserves special attention. The Act proposes $7 billion over four years to fund 10 different innovation hubs and it includes many provisions about how and where money will be spent. It’s hard to see how spreading $7 billion across 10 hubs is actually going to result in much once every special interest gets their cut of the action, but proposals like these are all the rage these days. It’s the equivalent of policymakers promising a high-tech chicken in every pot, or a Silicon Valley in every state.

In a two-part series for Discourse, I documented the problems associated with the many previous government efforts to create innovation hubs, tech clusters, or science parks. The government’s  track record in this regard is long and lamentable. Instead of following a time-tested approach getting the broad innovation policy environment right through a “generalized” approach to economic growth and development, most policymakers took unwise shortcuts and tried using “targeted” development schemes that were incredibly risky and ended up squandering a huge amount of taxpayer resources.

But all those failed past efforts probably won’t stop this high-tech pork barrel effort from rolling forward in some fashion. The proposed new regional hub effort comes on top of an announcement last July by the Commerce Department that the agency plans to allocate $1 billion in pandemic recovery funds to create or expand “regional industry clusters” as part of the administration’s new “Build Back Better Regional Challenge.” The agency’s list of possible winning funding ideas includes an “artificial intelligence corridor” and a “climate-friendly electric vehicle cluster.” And there are many other federal and state programs throwing money at the idea of hub or “cluster” formation, or even just highly cronyist efforts to attract a single big tech firm. (Anyone remember the Foxconn fiasco in Wisconsin?)

As Matt Mitchell and I have noted, this growing trend represents the collision of federal industrial policy and long-standing state-based economic development efforts. Regardless of how well-intentioned they may be, it is highly unlikely these new tech pork barrel efforts will produce better results than the long string of earlier federal and state failures.

Secondary Effects & Unforeseeable Costs

A bill this big presents many other big opportunities for corporations and other special interests. It’s no wonder that many companies, trade associations, and other special interests are lining up to support this effort. In a recent study co-authored with Connor Haaland (“Does the US Need a More Targeted Industrial Policy for AI & High-Tech”), we outlined “the way rent-seeking and cronyism often become chronic problems for highly targeted, big-budget industrial policy efforts.” Those problems will grow exponentially if the COMPETES Act passes. Everyone expects a cut of the action when Washington starts showering sectors with money.

But there’s a bigger problem associated with the everything-and-the-kitchen-sink approach to such a massive industrial policy bill.  All the ambiguities associated with a monster measure like this means that agency bureaucrats will be left to fill in all the details for many years to come. It is folly of the highest order to believe that all these agencies will work together in a tightly coordinated and consistent way to advance industrial policy efforts or address “strategic objectives.” Anyone currently following the fight between the FAA and FCC over the rollout of 5G wireless networks will know what I am talking about. Moreover, delegating broad authority and big money to all these agencies just further reinforces the rent-seeking instincts of special interests, who will rush to their respective regulatory masters with hat in hand. This presents agencies with an added policy lever to blackmail companies into doing what they want without any new regulations even being issued.

And then there is the final consideration: where will all the money come from for this grand exercise in technocratic central planning? The Senate bill costs an estimated $250 billion. To be clear, that’s A QUARTER TRILLION DOLLARS. We’re talking big money, and chances are that the final price tag for the House’s COMPETES Act will be even higher. Does the money to fund all this profligate spending just fall like manna from industrial policy heaven? No, it will come out the pockets of the American taxpayer and American companies (who will just pass the bill along to consumers). This will have dynamic effects on growth and innovation that are almost never discussed in industrial policy debates. Here’s how Connor Haaland and I put it in our big study:

“First, a dollar spent pursuing one objective is a dollar that could have been invested differently, and potential better. Second, the very act of imposing taxes to cover these state gambits results in costs and distortions that must be accounted for. Some of these costs are deadweight losses associated with taxes and tax collection more generally. But this points to a third lesson: The true potential costs associated with industrial policy programs also need to account for the negative secondary effects of rent-seeking, bureaucracy, and the many other downsides of the political system, included cost overruns and corruption.”

As the old saying goes: There is no free lunch.

Conclusion: There Is a Better Way

Some advocates of the COMPETES Act label it a “competitiveness bill” or an “innovation initiative.” It takes a great deal of hubris to pretend that that the economy is just a giant machine to be manipulated and that policymakers can easily “dial in” the desired innovation results through massive bills and expanded bureaucracy.

Lawmakers and bureaucrats are not going to allocate capital more efficiently than private innovators and investors. Nor are they going to be able to “shore up supply chains” or create tech hubs in every city just by sprinkling a little magical industrial policy pixie dust thinly across the entire nation.

We should not try to compete with China by becoming China. Nor do we need to. Markets and supply chains recover from setbacks faster than governments can. This week, the White House reiterated its support for industrial policy efforts to strengthen supply chains and extend subsidies to the semiconductors industry. But, assuming the COMPETES Act passes, it’ll take years to get all the planning and spending going. When government spins those proverbial dials, it does so very slowly and extremely inefficiently. Meanwhile, the same day the White House was making these announcements, it was also touting that $80 billion in private investment has been announced by the US semiconductor industry recently. Just last week, Intel announced it plans to invest at least $20 billion in two new chip-making facilities in Ohio. Scott Lincicome and Ilana Blumsack have documented the many other private initiatives underway by the semiconductor industry to expand domestic manufacturing capacity, as well as efforts by foreign firms like Samsung to invest here to take advantage of our skilled workforce and vibrant capital market. This is all happening despite the fact that Congress is still debating an industrial policy measure that may end up being too bloated to even achieve successful passage this session.

Does government have any role to play? It certainly does. Most current industrial policy proposals fail to understand that the most important thing that policymakers can do is to clean up decades of earlier failed industrial policy efforts. Industrial policies in fields like energy, aviation, space, communications and other sectors skewed markets in unnatural and inefficient ways by favoring specific technologies and companies over others. This is because industrial policy all too often devolves into the business of picking winners and losers. This is not always done in a formal way or even with clear intent. Rather, when government is throwing around billions and engaging in casino economics by placing big bets, a lucky few will win at the expense of others.

Of course, not all government support is as wasteful or corporatist in character. “Basic” R&D efforts are certainly more defensible than most “applied” or “targeted” efforts. “When government is supporting basic R&D,” Connor Haaland and I have noted, “the chances of wasting scarce resources on risky investments can be minimized to some degree, at least as compared with highly targeted applied R&D investments in unproven technologies and firms.”

And then there are all of the education and training efforts governments can undertake. If lawmakers were smart, they would have just limited their efforts to the sort of things found in Titles III, V, and VI of the COMPETES Act, which relates to boosting STEM education, high-tech workforce training, improving National Science Foundation research efforts, and funding various other federal science agencies and labs, that conduct more basic research. And more flexible immigration policies are also essential.

Meanwhile, government defense spending isn’t going to dry up anytime soon and it continues to represent an indirect form of industrial policy given the trillions of dollars that are spread around through the so-called “military-industrial complex.” That certainly doesn’t mean America should be greatly expanding its already bloated defense budgets in the name of expanding industrial policy. Yet, for better or worse, government is always going to be spending a lot of money on defense priorities and it gives it a chance to address whatever “strategic” needs it has.

But the current industrial policy behemoth advancing in Congress represents a misguided effort at domestic retrenchment and a collapse into a lamentable sort of techno-mercantilism thinking that happens every quarter century or so. In my paper with Haaland as well as a separate essay, I have documented just how misguided the “Japan panic” of the 1980s and 90s was. One policymaker and pundit after another lined up to breathlessly proclaim the end of America if we failed to adopt a grandiose industrial policy to counter Japan. Of course, that industrial policy approach ended up being such a disaster that even the Japanese government itself declared in a 2000 report that “the Japanese model was not the source of Japanese competitiveness but the cause of our failure.”

Moreover, it is worth noting what happened with the Internet and digital technology in the U.S. versus the rest of the world in the 1990s and beyond. America essentially put a policy firewall between the emerging digital technology sector and the old industrial policy regime we had for analog sectors and technologies, like broadcasting and wireline telephony. And thank God we did! America’s digital technology sector thrived, and U.S.-headquartered tech companies became household names across the globe. Meanwhile, the Europeans have spent 20 years crafting one misguided industrial policy scheme after another to equal America’s accomplishments. Despite highly targeted and expensive efforts to foster a domestic digital tech base, the EU has instead generated a string of industrial policy failures that Haaland and I documented in detail here.

Corporatism, cronyism, and profligate pork-barrel spending were not the sources of America’s competitive advantage in digital technology, and top-down planning did not make our digital technology companies global powerhouses.  Instead, we got our innovation culture right for digital technology. First and foremost, our the default regulatory policy for the digital economy was permissionless innovation. No one had to ask anyone for the right to develop all those new digital technologies and online platforms. The Clinton Administration’s 1997 “Framework for Global Electronic Commerce” announced that “governments should encourage industry self-regulation and private sector leadership where possible” and “avoid undue restrictions on electronic commerce.” Second, investors saw that positive policy ecosystem developing and moved quickly to shower entrepreneurs in this sector with unprecedented private venture capital investment. Third, education and career opportunities in these sectors expanded accordingly. Real-time “learning by doing” took place as millions of people learned new digital skillsets on the fly. Kids learned how to code before anyone could even teach them how to type. Most importantly, talented immigrants and foreign investors then came here to take advantage of all this, allowing America to steal away the best and brightest from the rest of the world.

This constitutes one of the greatest capitalist success stories in human history, and it all happened without targeted, technocratic, top-down industrial policy planning. This is the more principled and less costly vision for innovation policy America needs today to counter China and the rest of the world. There is absolutely no reason that we can’t apply this same vision to aviation, space, semiconductors, energy, nanotech, AI, and many other sectors of importance.

Additional Reading from Adam Thierer on Industrial Policy:

Other critical essays on industrial policy:

]]> https://techliberation.com/2022/01/26/thoughts-on-the-competes-act-the-most-corporatist-wasteful-industrial-policy-ever/feed/ 2 76942 The Case for Innovation, Progress & Abundance: Some Readings https://techliberation.com/2022/01/25/the-case-for-innovation-progress-abundance-some-readings/ https://techliberation.com/2022/01/25/the-case-for-innovation-progress-abundance-some-readings/#comments Tue, 25 Jan 2022 20:27:31 +0000 https://techliberation.com/?p=76937

This is a compendium of readings on “ progress studies ,” or essays and books which generally make the case for technological innovation, dynamism, economic growth, and abundance. I will update this list as additional material of relevance is brought to my attention.   

[Last update: 10/11/22]

Recent Essays

Books

]]> https://techliberation.com/2022/01/25/the-case-for-innovation-progress-abundance-some-readings/feed/ 3 76937 The Most Important Technology Policy Book of the Past Quarter Century https://techliberation.com/2022/01/20/the-most-important-technology-policy-book-of-the-past-quarter-century/ https://techliberation.com/2022/01/20/the-most-important-technology-policy-book-of-the-past-quarter-century/#comments Thu, 20 Jan 2022 14:17:10 +0000 https://techliberation.com/?p=76935

Discourse magazine has just published my review of Where Is My Flying Car?, by J. Storrs Hall, which I argue is the most important book on technology policy written in the past quarter century. Hall perfectly defines what is at stake if we fail to embrace a pro-progress policy vision going forward. Hall documents how a “Jetsons” future was within our grasp, but it was stolen away from us. What held back progress in key sectors like transportation, nanotech & energy was anti-technological thinking and the overregulation that accompanies it. “[T]he Great Stagnation was really the Great Strangulation,” he argues. The culprits: negative cultural attitudes toward innovation, incumbent companies or academics looking to protect their turf, litigation-happy trial lawyers, and a raft of risk-averse laws and regulations.

Hall coins the term “the Machiavelli Effect” to identify why many people simultaneously fear the new and different, and they also want to protect whatever status quo they benefit from (or at least feel comfortable with). He builds on this passage from Niccolò Machiavelli’s classic 1532 study of political power, “The Prince”:

[I]t ought to be remembered that there is nothing more difficult to take in hand, more perilous to conduct, or more uncertain in its success, then to take the lead in the introduction of a new order of things. Because the innovator has for enemies all those who have done well under the old conditions, and lukewarm defenders in those who may do well under the new. This coolness arises partly from fear of the opponents, who have the laws on their side, and partly from the incredulity of men, who do not readily believe in new things until they have had a long experience of them. Thus it happens that whenever those who are hostile have the opportunity to attack they do it like partisans, whilst the others defend lukewarmly, in such wise that the prince is endangered along with them.

Hall notes that the Machiavelli Effect “has nothing to do with any conspiracy.” Rather, it comes down to human nature: Many people simultaneously fear the new and different, and they also want to protect whatever status quo they benefit from (or at least feel comfortable with). Isaac Asimov identified the same problem in a 1974 lecture when he noted how there had been “bitter, exaggerated, last-stitch resistance . . . to every significant technological change that had taken place on earth.” [On this same point, also see Innovation and Its Enemies: Why People Resist New Technologies, by Calestous Juma. It’s the best history on the topic.]

Hall identifies how the Machiavelli Effect held back nuclear, nanotech, and aviation technologies. “Over the long run, unchecked regulation destroys the learning curve, prevents innovation, protects and preserves inefficiency, and makes progress run backward.” The problem is the Precautionary Principle, which undermines the learning curve is by setting policy defaults to no trial and error as opposed to free to experiment. There can be no reward without some risk! Hall quotes Wilbur Wright on this, who once noted that, “If you are looking for perfect safety, you would do well to sit on a fence and watch the birds.”

Over-regulation of those sectors also resulted in massive misallocation of talent, “taking more than a million of the country’s most talented and motivated people and putting them to work making arguments and filing briefs instead of inventing, developing, and manufacturing.” Hall is equally critical of government R&D efforts. “One of the great tragedies of the latter 20th century, and clearly one of the causes of the Great Stagnation,” he argues, “was the increasing centralization and bureaucratization of science and research funding.”

Hall’s book builds on Jason Crawford’s insight that, “We need a new philosophy of progress,” that is rooted in optimism about the future and support for a culture of trial-and-error experimentation. Hall’s book is a major contribution to that effort. Hall makes a profoundly moral case for innovation. “The zero-sum society is a recipe for evil,” because it leaves us with a “static level of existence” that denies us the ability to improve the human condition. Indeed, Hall’s book is the most full-throated defense of innovation by a trained scientist or engineer since Samuel Florman’s 1976 “Existential Pleasures of Engineering.” Both are celebrations of the potential for humanity to build more and better tools to improve the world.

Hall’s book should also be read alongside books from Virginia Postrel (“The Future and Its Enemies”), Steven Pinker (“Enlightenment Now”), Matt Ridley (“How Innovation Works”) and Deirdre McCloskey’s three-volume trilogy about the history of modern economic growth. These scholars argue that there is a symbiotic relationship between innovation, economic growth, pluralism and human betterment, and that to deny people the ability to improve their lot in life is fundamentally anti-human.

Image

I just cannot recommend Hall’s Where Is My Flying Car? highly enough. It’s a masterpiece. And bravo to Stripe Press for publishing a beautiful hardbound edition. It is a stunning book both to behold and read. Order it now, and jump over to Discourse to read my entire review of it.

 

]]> https://techliberation.com/2022/01/20/the-most-important-technology-policy-book-of-the-past-quarter-century/feed/ 2 76935 New Mercatus Center Report on Industrial Policy https://techliberation.com/2021/11/17/new-mercatus-center-report-on-industrial-policy/ https://techliberation.com/2021/11/17/new-mercatus-center-report-on-industrial-policy/#comments Wed, 17 Nov 2021 21:21:29 +0000 https://techliberation.com/?p=76921

The Mercatus Center has just released a new special study that I co-authored with Connor Haaland entitled, “Does the United States Need a More Targeted Industrial Policy for High Tech?” With industrial policy reemerging as a major issue — and with Congress still debating a $250 billion, 2,400-page industrial policy bill — our report does a deep dive into the history various industrial policy efforts both here and abroad over the past half century. Our 64-page survey of the historical record leads us to conclude that, “targeted industrial policy programs cannot magically bring about innovation or economic growth, and government efforts to plan economies from the top down have never had an encouraging track record.”

We zero in on the distinction between general versus targeted economic development efforts and argue that:

whether we are referring to federal, state, or local planning efforts—the more highly tar­geted development efforts typically involve many tradeoffs that are often not taken into consider­ation by industrial policy advocates. Downsides include government steering of public resources into unproductive endeavors, as well as more serious problems, such as cronyism and even corruption.

We also stress the need to more tightly define the term “industrial policy” to ensure rational evaluation is even possible. We argue that, “industrial policy has intentionality and directionality, which distinguishes it from science policy, innovation policy, and economic policy more generally.” We like the focus definition used by economist Nathaniel Lane, who defines industrial policy as “intentional political action meant to shift the industrial structure of an economy.”

Our report examines the so-called “Japan model” of industrial policy that was all the rage in intellectual circles a generation ago and then compares it to the Chinese and European industrial policy efforts of today, which many pundits claim that the US needs to mimic. We find problems with those models and argue that:

America’s goal should not be to “imitate China” or “copy its playbook” when it comes to targeted industrial policy and technological governance of AI and other high-tech sectors. Europe’s approach, although not as heavy-handed, is also not a good model. Not only would the Chinese and European approaches potentially undermine the permissionless innovation ethos that made America’s tech companies become global powerhouses, but expanded industrial policy efforts would entail massive state bets on risky ventures using taxpayer resources.

We discuss the public choice dynamics surrounding many industrial development efforts and note that, “what is often described as “industrial policy” is in reality nothing more than industrial politics.” We highlight how many of the largest industrial policy programs have been prone to highly inefficient contracting procedures and massive cost overruns. Sometimes outright corruption even becomes a problem with some of the largest programs. But that’s not the only cost. Sometimes, in their effort to promote specific industrial outputs or outcomes, government undermines the very innovation they hope to spur.

When governments repress the entrepreneurial spirit of their most innovative creators and companies, this is bound to have negative ramifications for long-term competitiveness and economic growth. Heavy-handed industrial policy schemes can contribute to this sort of repression as the state gains more levers of control over private companies.

We note how that has certainly been the case in the European Union, where “countries have adopted a highly precautionary regulatory model for new digital sectors that shuns risk-taking and focuses on maximizing other values at the expense of disruptive change. This approach has resulted in fewer national champions, and it has cost Europe in terms of global competitive advantage,” we note. We also highlight the long string of failed European industrial policy programs.

Ours is not a doctrinaire analysis; we take a pragmatic approach to the evaluation of industrial policy programs and proposals. Some of them may succeed based simply on the reality that “if government officials roll the proverbial industrial policy dice enough times, some bets are bound to pay off, at least indirectly.” But any serious analysis of these efforts, we argue, must fully weigh the trade-offs associated with the potential tax and compliance burdens associated with funding them to begin with.

But we admit that, “industrial policy will always be with us to some extent, given the sheer size of government and the many existing programs already devoted to economic development or high-tech initiatives.” Toward that end, we wrap up the paper with a variety of high-level recommendations about industrial policy. We highlight how:

The priority should be generalized economic development over targeted development efforts. The most important thing that policymakers can do to boost economic opportunities is to create a legal and regulatory environment that is conducive to entrepreneurship, investment, innovation, and free trade.  [. . . ] government should focus on setting the table for entrepreneurial activity instead of trying to determine everything on the plate. To put this differently, policymakers need to avoid the “fun stuff” and focus on “boring” issues that often get neglected.

We apply these insights to the ongoing debate over regional economic development and the specific effort currently underway at the federal level to encourage “regional innovation hubs,” as federal and state lawmakers look to create “the next Silicon Valley” elsewhere.

In terms of our nation’s overall investment in R&D, we note that “[t]he United States has the most vibrant venture capital (VC) market in the world, and this market helps support risky ventures without gambling with taxpayer dollars.” While some bemoan the fact that private enterprise provides the bulk of R&D expenditures in the US – and that amount is increasing relative to governmental sources – this is actually something that should be celebrated. The strength of private-funded R&D helps set the US apart and make investment markets nimbler and more responsive to real-world needs. Moreover, global unicorn growth in the US continues at a healthy clip. From 2010 to mid-2021, the US created 53 percent of global unicorns, compared with 20 percent for China. These facts are often overlook in industrial policy debates.

While our paper is comprehensive, admittedly, there are some things we leave out of the analysis or do not spend as much time discussing. For example, there is a never-ending debate about the relationship between national security and industrial policy that raises many hard questions. A nation needs military hardware to defend itself, and almost every program to provide weapons and military equipment in the US involve private contracting to get them. These are the biggest industrial policy programs at all, but we don’t spend a lot of time focus on them in our paper because that would have taken us far afield.

We have a short section on these issues that notes how “defense-related programs have also been prone to highly inefficient contracting procedures and massive cost overruns.” Many of these programs remain vital, however, and must find a way to make them more efficient and cost-effective. But there are still other issues related to national security and industrial policy that raise hard questions, including: export or import controls, trade restrictions, and more. These continue to be challenging issues and I personally hope to revisit some of them in upcoming essays.

With Congress still trying to finalize its mega industrial policy bill, our paper is relevant to the short-term debate over these issues. But our hope is that this paper offers a big-picture, long-term framework for thinking through the challenges associated with industrial policy issues both here and abroad.

Here is the outline of the paper and, again, you can find it at this link. (The report can also be found on SSRN & Research Gate).

  1. Introduction: Definitional Challenges 5
  2. Calls for Expanding Industrial Policy to Boost High-Tech Innovation 8
  3. Some (Quickly Forgotten) Recent History 11
  4. The Romantic View of Industrial Policy vs. Reality 15
  5. The Challenge of Creating “National Champions”: Europe’s Failures 20
  6. Adverse Effects of State-Led Promotion: The China Model Examined 23
  7. Where Does Real Competitive Advantage Come From? 27
  8. Industrial Policy Did Not Give Us the Internet and the iPhone 33
  9. Evaluating Other Industrial Policy Efforts 39
  10. Using Competitions and Prizes to Encourage Innovation More Efficiently 46
  11. Conclusion: Generality Is Better Than Targeting

Additional Reading:

]]> https://techliberation.com/2021/11/17/new-mercatus-center-report-on-industrial-policy/feed/ 1 76921 Can Government Reproduce Silicon Valley Everywhere? https://techliberation.com/2021/09/12/can-government-reproduce-silicon-valley-everywhere/ https://techliberation.com/2021/09/12/can-government-reproduce-silicon-valley-everywhere/#comments Sun, 12 Sep 2021 17:36:07 +0000 https://techliberation.com/?p=76903

Wishful thinking is a dangerous drug. Some pundits and policymakers believe that, if your intentions are pure and you have the “right” people in power, all government needs to do is sprinkle a little pixie dust (in the form of billions of taxpayer dollars) and magical things will happen.

Of course, reality has a funny way of throwing a wrench into the best-laid plans. Which brings me to the question I raise in a new 2-part series for  Discourse magazine: Can governments replicate Silicon Valley everywhere?

In the first installment, I explore the track record of federal and state attempts to build tech clusters, science parks & “regional innovation hubs” using state subsidies and industrial policy. This is highly relevant today because of the huge new industrial policy push at the federal level is building on top of growing state and local efforts to create tech hubs, science parks, or various other types of industrial “clusters.

At the federal level, this summer, the Senate passed a 2,300-page industrial policy bill, the “United States Innovation and Competition Act of 2021,” that included almost $10 billion over four years for a Department of Commerce-led effort to fund 20 new regional technology hubs, “in a manner that ensures geographic diversity and representation from communities of differing populations.” A similar proposal that is moving in the House, the “Regional Innovation Act of 2021,” proposes almost $7 billion over five years for 10 regional tech hubs. Meanwhile, the Biden administration also is pitching ideas for new high-tech hubs. In late July, the Commerce Department’s Economic Development Administration announced plans to allocate $1 billion in pandemic recovery funds to create or expand “regional industry clusters” as part of the administration’s new Build Back Better Regional Challenge. Among the possible ideas the agency said might win funding are an “artificial intelligence corridor,” an “agriculture-technology cluster” in rural coal counties, a “blue economy cluster” in coastal regions, and a “climate-friendly electric vehicle cluster.”

In my essay, I note that the economic literature on these efforts has been fairly negative, to put it mildly. There is no precise recipe for growing tech clusters, as most economists and business analysts note.

“Despite several attempts, Silicon Valley has not been successfully copied elsewhere,” notes Mark Zachary Taylor, author of “The Politics of Innovation: Why Some Countries Are Better Than Others at Science and Technology.” Judge Glock, a senior policy adviser with the Cicero Institute, offers a more blistering assessment of such efforts: “Almost every American state has tried to fund the creation of biotech clusters, projects that almost inevitably end with weeds growing through the parking-lot pavement and a trail of corrupt bargains.”

I then highlight the key findings from several major studies of these efforts, all of which make it clear that, as cluster scholars by Aaron Chatterji, Edward Glaeser and William Kerr noted in 2014 after gathering all the research conducted on the topic: existing evidence “suggests that the regional foundation for growth-enabling innovation is complex and that we should be cautious of single policy solutions that claim to fit all needs.” Furthermore, “even if clusters of entrepreneurship are good for local growth, it is less clear that cities or states have the ability to generate those clusters.”

I also highlight research from my Mercatus Center colleagues on “The Economics of a Targeted Economic Development Subsidy” documenting costs of state-level planning & case study of Foxconn fiasco. They summarize the fairly miserable track record of state and local mini-industrial policy efforts. As they note, the extensive economic literature on this matter finds that “the net effect of targeted economic development subsidies is likely to be negative” because “the taxes funding the subsidies will discourage more economic activity than will be encouraged by the subsidies themselves.” Similarly, Harvard Business School economist Josh Lerner evaluated dozens of similar targeted development efforts from around the globe in his 2009 book Boulevard of Broken Dreams: Why Public Efforts to Boost Entrepreneurship and Venture Capital Have Failed—and What to Do About It. He concluded that “for each effective government intervention, there have been dozens, even hundreds, of failures, where substantial public expenditures bore no fruit.”

In my essay, I also discuss the astonishing array of federal efforts to promote the geographic spread of high-tech sectors and jobs since 2000. Throughout Bush, Obama, Trump & Biden admins, there’s been a lot of spending, but not a lot of success. Just lots of new laws and bureaucracies:

In 2012, the Obama administration launched the multiagency Rural Jobs and Innovation Accelerator Challenge and Advanced Manufacturing Jobs and Innovation Accelerator Challenge. This occurred at roughly the same time President Obama was launching his Startup America initiative. He also signed the JOBS Act (Jump-start Our Business Startups) in 2012. All these efforts included various measures to support the spread of advanced manufacturing and high-tech startups across the U.S. But none of these efforts have borne much fruit so far.

In the second installment of this series, I explore better ways to encourage regional tech innovation and economic development without doubling down on failed programs of the past. Specifically, I explain why, when it comes to economic development efforts, policymakers would be wise to avoid the costly, ineffective “fun stuff” and refocus on time-tested “boring” strategies:

The boring approach to economic development seeks to promote an open innovation culture that is conducive to risk-taking, investment and growth without the need to extend targeted privileges to particular firms or industries. Such a culture comes down to a classic mix of simplified and equally applied taxes, streamlined permitting processes and sensible regulations, limits on frivolous lawsuits, and clear protection of contracts and property rights. As Matt Mitchell and I argued previously, policymakers need to resist the urge to go for broke with splashy policies and programs. They need to appreciate the benefits of generalized economic development policy (a.k.a. the boring approach) as opposed to far riskier targeted development efforts.

I also highlight recent research explaining how perhaps the simplest way to strengthen existing clusters, or give rise to new ones, is to make sure America’s immigration policies are hospitable to the best and brightest minds from across the globe.

And I note how, due to the problems associated with many other forms of government-sponsored R&D assistance, many scholars and policymakers are increasingly turning to the idea of government-sponsored competitions and prizes as a superior way to distribute R&D assistance.

With competitions, governments can set broad goals to help facilitate the search for important societal needs. The prizes then create a powerful incentive for innovators to pursue those goals, not only to win money, but also to gain recognition from peers and the public. Another alternative is just using lotteries to distribute R&D money instead of having agencies target grants. That at least avoids political shenanigans and paperwork delays, although it may not be a particularly effective approach.

There is also some good news is overlooked in today’s rush to make big industrial policy gambles: Venture capitalists and new startups are already spreading out naturally.

A 2021 study on “The State of the Startup Ecosystem” by Engine, a research and advocacy organization supporting startups, revealed that “as Series A funding grew over the last fifteen years, more of that growth has started to shift to areas located outside of the largest ecosystems.” Series A funding refers to the initial round of outside venture capitalist investment in startups. The report looked at Series A deals from 2003 to 2018 and found that “Series A rounds outside of the top five ecosystems grew nearly 900 percent, while the number of rounds outside of the top nine grew nearly tenfold.” Whereas Series A fundings outside of the top five ecosystems stood at 38% in 2003, they had jumped up to 43% in 2018. “The increase in deal location diversity over this period reflects an increasing spread in venture capital investment across the country and less centralization of investment in areas like Silicon Valley,” the report concluded.

Meanwhile, tech innovators and investors are increasingly engaging in innovation arbitrage as they move to cities and states across the nation that are more hospitable to entrepreneurial activities. Firms and investors are voting with their feet (and dollars) by flocking to areas where tech clusters can more naturally sprout because the general policy environment is sound.

But government efforts to artificially try to create regional innovation hubs in a top-down, technocratic fashion will almost certainly persist. As they do, some will argue that this time will be different! Perhaps, but it is more likely that the past is prologue; these new hubs will likely cause federal politicians to jockey for position to have their regions named one of the winners and get a big cut of all the new high-tech pork being served up by Washington. We can do better.

Jump over to  Discourse to read both installments here and here.

Also, down below I list several other things I have written recently on industrial policy efforts more generally.

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