Here’s a new DC EKG podcast I recently appeared on to discuss the current state of policy development surrounding artificial intelligence. In our wide-ranging chat, we discussed:

• why a sectoral approach to AI policy is superior to general purpose licensing
• why comprehensive AI legislation will not pass in Congress
• the best way to deal with algorithmic deception
• why Europe lost its tech sector
• how a global AI regulator threatens our safety
• the problem with Biden’s AI executive order
• will AI policy follow same path as nuclear policy?
• global innovation arbitrage & the innovation cage
• AI, health care & FDA regulation
• AI regulation vs trade secrets
• is AI transparency / auditing the solution?

Listen to the full show here or here. To read more about current AI policy developments, check out my “Running List of My Research on AI, ML & Robotics Policy.”

My latest dispatch from the frontlines of the artificial intelligence policy wars in Washington looks at the major proposals to regulate AI. In my new essay, “Artificial Intelligence Legislative Outlook: Fall 2023 Update,” I argue that there are 3 major impediments to getting major AI legislation over the finish line in Congress: (1) Breadth and complexity of the issue; (2) Multiplicity of concerns & special interests; & (3) Extreme rhetoric / proposals are dominating the discussion.

If Congress wants to get something done in this session, they’ll need to do two things: (1) set aside the most radical regulatory proposals (like big new AI agencies or licensing schemes); and (2) break AI policy down into its smaller subcomponents and then prioritize among them where policy gaps might exist.

Prediction: Congress will not pass any AI-related legislation this session due to the factors identified in my essay. The temptation to “go big” with everything-and-the-kitchen-sink approaches to AI regulation will (especially with extreme ideas like new agencies & licenses) will doom AI legislation. It’s also worth noting that Washington’s swelling interest in AI policy is having a crowding-out effect on other important legislative proposals that might have advanced otherwise, such as the baseline privacy bill (ADPPA) and other things like driverless car legislation. Many want to advance those efforts first, but the AI focus makes that hard.

Read the entire essay here.

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:

• Adam Thierer, “The Biden Administration’s Plan to Regulate AI without Waiting for Congress,” Medium, May 4, 2023.
• Adam Thierer, “NEPA for Al? The Problem with Mandating Algorithmic Audits & Impact Assessments,” Medium, April 23, 2023.
• Adam Thierer, “Flexible, Pro-Innovation Governance Strategies for Artificial Intelligence, R Street Institute Policy Study №283 (April 2023).
• Adam Thierer, “A balanced AI governance vision for America,” The Hill, April 16, 2023.
• Adam Thierer, Brent Orrell, & Chris Meserole, “Stop the AI Pause,” AEI Ideas, April 6, 2023.
• Adam Thierer, “Getting AI Innovation Culture Right,” R Street Institute Policy Study №281 (March 2023).
• Adam Thierer, “Can We Predict the Jobs and Skills Needed for the AI Era?,” R Street Institute Policy Study №278 (March 2023).
• Adam Thierer, “U.S. Chamber AI Commission Report Offers Constructive Path Forward,” R Street Blog, March 9, 2023.
• Adam Thierer, “What If Everything You’ve Heard about AI Policy is Wrong?” Medium, February 20, 2023.
• Adam Thierer, “Policy Ramifications of the ChatGPT Moment: AI Ethics Meets Evasive Entrepreneurialism,” Medium, February 14, 2023.
• Adam Thierer, “Mapping the AI Policy Landscape Circa 2023: Seven Major Fault Lines,” R Street Blog, February 9, 2023.
• Adam Thierer, “Artificial Intelligence Primer: Definitions, Benefits & Policy Challenges,” Medium, December 2, 2022.
• Neil Chilson & Adam Thierer, “The Coming Onslaught of ‘Algorithmic Fairness’ Regulations,” Regulatory Transparency Project of the Federalist Society, November 2, 2022.
• Adam Thierer, “We Really Need To ‘Have a Conversation’ About AI … or Do We?” Discourse, October 6, 2022.

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:

• Adam Thierer, “A balanced AI governance vision for America,” The Hill, April 16, 2023.
• Adam Thierer, Brent Orrell, & Chris Meserole, “Stop the AI Pause,” AEI Ideas, April 6, 2023.
• Adam Thierer, “Getting AI Innovation Culture Right,” R Street Institute Policy Study No. 281 (March 2023).
• Adam Thierer, “Can We Predict the Jobs and Skills Needed for the AI Era?,” R Street Institute Policy Study No. 278 (March 2023).
• Adam Thierer, “U.S. Chamber AI Commission Report Offers Constructive Path Forward,” R Street Blog, March 9, 2023.
• Adam Thierer, “What If Everything You’ve Heard about AI Policy is Wrong?” Medium, February 20, 2023.
• Adam Thierer, “Mapping the AI Policy Landscape Circa 2023: Seven Major Fault Lines,” R Street Blog, February 9, 2023.
• Adam Thierer, “Artificial Intelligence Primer: Definitions, Benefits & Policy Challenges,” Medium, December 2, 2022.
• Neil Chilson & Adam Thierer, “The Coming Onslaught of ‘Algorithmic Fairness’ Regulations,” Regulatory Transparency Project of the Federalist Society, November 2, 2022.
• Adam Thierer, “AI Eats the World: Preparing for the Computational Revolution and the Policy Debates Ahead,” Medium, September 10, 2022.
• Adam Thierer, “How Science Fiction Dystopianism Shapes the Debate over AI & Robotics,” Discourse, July 26, 2022.

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.

In my latest R Street Institute blog post, “Mapping the AI Policy Landscape Circa 2023: Seven Major Fault Lines,” I discuss the big issues confronting artificial intelligence and machine learning in the coming year and beyond. I note that the AI regulatory proposals are multiplying fast and coming in two general varieties: broad-based and targeted. Broad-based algorithmic regulation would address the use of these technologies in a holistic fashion across many sectors and concerns. By contrast, targeted algorithmic regulation looks to address specific AI applications or concerns. In the short-term, it is more likely that targeted or “sectoral” regulatory proposals have a chance of being implemented.

I go on to identify seven major issues of concern that will drive these policy proposals. They include:

1) Privacy and Data Collection

2) Bias and Discrimination

3) Free Speech and Disinformation

4) Kids’ Safety

5) Physical Safety and Cybersecurity

6) Industrial Policy and Workforce Issues

7) National Security and Law Enforcement Issues

Of course, each of these issues includes many sub-issues and nuanced concerns. But I also noted that “this list only scratches the surface in terms of the universe of AI policy issues.” Algorithmic policy considerations are now being discussed in many other fields, including education, insurance, financial services, energy markets, intellectual property, retail and trade, and more. I’ll be rolling out a new series of essays examining all these issues throughout the year.

But, as I note in concluding my new essay, the danger of over-reach exists with early regulatory efforts:

AI risks deserve serious attention, but an equally serious risk exists that an avalanche of fear-driven regulatory proposals will suffocate different life-enriching algorithmic innovations. There is a compelling interest in ensuring that AI innovations are developed and made widely available to society. Policymakers should not assume that important algorithmic innovations will just magically come about; our nation must get its innovation culture right if we hope to create a better, more prosperous future.

America needs a flexible governance approach for algorithmic systems that avoids heavy-handed, top-down controls as a first-order solution. “There is no use worrying about the future if we cannot even invent it first,” I conclude.

Additional Reading

• Adam Thierer, “Artificial Intelligence Primer: Definitions, Benefits & Policy Challenges,” Medium, December 2, 2022.
• Neil Chilson & Adam Thierer, “The Coming Onslaught of ‘Algorithmic Fairness’ Regulations,” Regulatory Transparency Project of the Federalist Society, November 2, 2022.
• Adam Thierer, “We Really Need To ‘Have a Conversation’ About AI … or Do We?” Discourse, October 6, 2022.
• Adam Thierer, “How the Embedding of AI Ethics Works in Practice & How It Can Be Improved,” Medium, September 22, 2022.
• Adam Thierer, “No Goldilocks Formula for Content Moderation in Social Media or the Metaverse, But Algorithms Still Help,” Medium, September 13, 2022.
• Adam Thierer, “AI Eats the World: Preparing for the Computational Revolution and the Policy Debates Ahead,” Medium, September 10, 2022.
• Adam Thierer, “‘Running Code and Rough Consensus’ for AI: Polycentric Governance in the Algorithmic Age,” Medium, September 1, 2022.
• Adam Thierer, “AI Governance ‘on the Ground’ vs ‘on the Books,’” Medium, August 19, 2022.
• Adam Thierer, “Why the Future of AI Will Not Be Invented in Europe,” Technology Liberation Front, August 1, 2022.
• Adam Thierer, “Existential Risks & Global Governance Issues around AI & Robotics,” [DRAFT CHAPTER, July 2022].
• Adam Thierer, “How Science Fiction Dystopianism Shapes the Debate over AI & Robotics,” Discourse, July 26, 2022.
• Adam Thierer, “Why is the US Following the EU’s Lead on Artificial Intelligence Regulation?” The Hill, July 21, 2022.
• Adam Thierer, “Algorithmic Auditing and AI Impact Assessments: The Need for Balance,” Medium, July 13, 2022.
• Adam Thierer, “The Proper Governance Default for AI,” Medium, May 26, 2022.
• Adam Thierer, “What I Learned about the Power of AI at the Cleveland Clinic,” Medium, May 6, 2022.
• Adam Thierer, Governing Emerging Technology in an Age of Policy Fragmentation and Disequilibrium, American Enterprise Institute (April 2022).

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 :

• Adam Thierer, “We Really Need To ‘Have a Conversation’ About AI … or Do We?,” Discourse, October 6, 2022.
• Adam Thierer, “AI Eats the World: Preparing for the Computational Revolution and the Policy Debates Ahead,” Medium, September 10, 2022.
• Adam Thierer, “’Running Code and Rough Consensus’ for AI: Polycentric Governance in the Algorithmic Age,” Medium, September 1, 2022.
• Adam Thierer, “AI Governance ‘on the Ground’ vs ‘on the Books,’” Medium, August 19, 2022.
• Adam Thierer, “Responses to Jack Clark’s AI Policy Tweetstorm,” Medium, August 8, 2022.
• Adam Thierer, “Why the Future of AI Will Not Be Invented in Europe,” Technology Liberation Front, August 1, 2022.
• Adam Thierer, “How Science Fiction Dystopianism Shapes the Debate over AI & Robotics,” Discourse, July 26, 2022.
• Adam Thierer, “Why is the US Following the EU’s Lead on Artificial Intelligence Regulation?” The Hill, July 21, 2022.
• Adam Thierer, “Algorithmic Auditing and AI Impact Assessments: The Need for Balance,” Medium, July 13, 2022.
• Adam Thierer, “The Proper Governance Default for AI,” Medium, May 26, 2022.
• Adam Thierer, “What I Learned about the Power of AI at the Cleveland Clinic,” Medium, May 6, 2022.
• Adam Thierer, Governing Emerging Technology in an Age of Policy Fragmentation and Disequilibrium, American Enterprise Institute (April 2022).
• Adam Thierer and John Croxton, “Elon Musk and the Coming Federal Showdown Over Driverless Vehicles,” Discourse, November 22, 2021.
• Adam Thierer, “A Global Clash of Visions: The Future of AI Policy,” The Hill, May 4, 2021.
• Adam Thierer, “A Brief History of Soft Law in ICT Sectors: Four Case Studies,” Jurimetrics, Vol. 61 (Fall 2021): 79-119.
• Adam Thierer, “U.S. Artificial Intelligence Governance in the Obama–Trump Years,” IEEE Transactions on Technology and Society, Vol, 2, Issue 4 (2021).
• Adam Thierer, “The Worst Regulation Ever Proposed,” The Bridge, September 2019.
• Ryan Hagemann, Jennifer Huddleston Skees & Adam Thierer, “Soft Law for Hard Problems: The Governance of Emerging Technologies in an Uncertain Future,” Colorado Technology Law Journal, Vol. 17 (2018).
• Adam Thierer & Trace Mitchell, “No New Tech Bureaucracy,” Real Clear Policy, September 10, 2020.
• Adam Thierer, “OMB’s AI Guidance Embodies Wise Tech Governance,” Mercatus Center Public Comment, March 13, 2020.
• Adam Thierer, “Europe’s New AI Industrial Policy,” Medium, February 20, 2020.
• Adam Thierer, “Trump’s AI Framework & the Future of Emerging Tech Governance,” Medium, January 8, 2020.
• Adam Thierer, “Soft Law: The Reconciliation of Permissionless & Responsible Innovation,” Chapter 7 in Adam Thierer, Evasive Entrepreneurs & the Future of Governance (Washington, DC: Cato Institute, 2020): 183-240.
• Andrea O’Sullivan & Adam Thierer, “Counterpoint: Regulators Should Allow the Greatest Space for AI Innovation,” Communications of the ACM, Volume 61, Issue 12, (December 2018): 33-35.
• Adam Thierer, Andrea O’Sullivan & Raymond Russell, “Artificial Intelligence and Public Policy,” Mercatus Research (2017).
• Adam Thierer, “Shouldn’t the Robots Have Eaten All the Jobs at Amazon By Now?” Technology Liberation Front, July 26, 2017.
• Adam Thierer, “Are ‘Permissionless Innovation’ and ‘Responsible Innovation’ Compatible?” Technology Liberation Front, July 12, 2017.
• Adam Thierer, “The Growing AI Technopanic,” Medium, April 27, 2017.
• Adam Thierer, “The Day the Machines Took Over,” Medium, May 11, 2017.
• Adam Thierer, “When the Trial Lawyers Come for the Robot Cars,” Slate, June 10, 2016.
• Adam Thierer, “Learning by Doing,” the Process of Innovation & the Future of Employment,” Technology Liberation Front, September 25, 2015.
• Adam Thierer, “Problems with Precautionary Principle-Minded Tech Regulation & a Federal Robotics Commission,” Medium, September 22, 2014.
• Adam Thierer, “On the Line between Technology Ethics vs. Technology Policy,” Technology Liberation Front, August 1, 2013.

[Cross-posted from Medium.]

Over the past decade, tech policy experts have debated the impact of “software eating the world.” In coming years, the debate will turn to what happens when that software can be described as artificial intelligence (AI) and comes to have an even greater influence. Every segment of the economy will be touched by AI, machine learning (ML), robotics, and the Computational Revolution more generally. And public policy will be radically transformed along the way.

This process is already well underway and accelerating every day. AI, ML, and advanced robotics technologies are rapidly transforming a diverse array of sectors and professions such as medicine and health care, financial services, transportation, retail, agriculture, entertainment, energy, aviation, the automotive industry, and many others.

As every industry integrates AI, all policy will involve AI and computational considerations. The stakes here are profound for individuals, economies, and nations. It is not hyperbole when we hear how AI will drive “the biggest geopolitical revolution in human history” and that “AI governance will become among the most important global issue areas.”

Unfortunately, many policy wonks — especially liberty-loving, pro-innovation policy analysts — are unaware of or ignoring these realities. They are not focusing on preparing for the staggering constellation of issues and controversies that await us in the world of AI policy.

Innovation defenders need to keep the Gretzky principle in mind. Hockey legend Wayne Gretzky once famously noted that the key to his success was, “I skate to where the puck is going to be, not where it has been.” Yet today, many analysts and organizations are focused on the where the tech policy puck is now and not anticipating where it will be tomorrow.

Because of its breadth, AI policy will be the most important technology policy fight of the next quarter century. As proposals to regulate AI proliferate, those who are passionate about preserving the freedom to innovate must prepare to meet the challenge. Here’s what we need to do to prepare for it.

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.”

Contemporary AI technology fits the bill. AI combines computation, data, algorithms, machine learning, networks, and advanced mathematics, to drive a broad range of powerful applications and surfaces new techno-economic and techno-social paradigms. It will transform everything.

Several underlying realities make AI both the most important technological revolution and all-encompassing technology policy issue of our lifetime. First, AI reflects the power of combinatorial innovation in which new technologies symbiotically build on top of one another, holistically accelerating each technology’s development and sophistication over time. AI and machine-learning capabilities build upon knowledge and capabilities developed through many other important technologies and sectors, including microprocessors, the Internet, high-speed broadband networks, sensors and geolocation technologies, and data storage/processing systems. In turn, AI and ML will become the building blocks for a great many other innovations going forward.

Indeed, AI/ML is set to become the “most important general-purpose technology of our era.” This general-purpose nature is the second complicating reality of AI. AI will benefit almost all organizations’ analytics and marketing, customer service, and sales. It will also affect many other business practices, social norms and interactions, artistic endeavors, governmental operations, and much more. This broad scope of application is what makes AI so important for future innovation and growth, but also complicates its governance.

Much like consumer electronics, computing, and the internet before it, AI is difficult to govern in the abstract; it is much easier to imagine how to govern individual applications. This is one reason that governance frameworks for driverless cars, drones, and robotics are developing more rapidly than overarching regulation for general AI.

Finally, AI also raises special governance challenges because it is a dual-use (and often open source) technology that, like chemical and nuclear technologies before it, has both beneficial peaceful uses but also potentially many military or law enforcement applications. This fact is particularly important when discussing so-called existential risks.

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.

Market-oriented research centers tend to have lots of lawyers and economists on staff today. Those skillsets will remain essential. But AI opens new policy horizons and demands new capabilities. “Machine learning is at the intersection of statistics and computer science, occasionally also taking inspiration from cognitive science and neuroscience,” notes computer engineer Ethem Alpaydin. Those skillsets are rare in think tanks or policy advocacy shops today. But AI and ML also intersect with many softer sciences, including philosophy, sociology, anthropology, and countless others. The most important policy battles over the future of AI will be about ethics, and yet few think tanks have philosophers on staff.

Yet advocates of aggressive AI regulation can be found in many of these academic fields, and many think tanks and policy advocacy organizations on the Left are already gearing up to handle AI policy in a more holistic fashion, incorporating perspectives from many of these disciplines. This leaves individuals and groups who defend markets and innovation woefully behind. When one examines the major conferences on AI and robotics today, there is very little ideological balance. That’s not just because the conference sponsors are guilty of a pro-regulatory bias, but also because the pipeline of talent on the other side of the fence is dry. There are not many obvious free-market scholars who could bring greater balance to such programs.

Thus, the first order of business for our movement is clear: We need to get serious about developing new talent and bringing new skillsets to better address AI policy issues and defend innovation and progress in this arena. The free-market movement has done a good job developing young talent in economics programs and law schools, but it’s far behind in developing a diverse new generation of scholars in all those other fields mentioned. As AI eats the world, it also eats the academy, and it won’t be just the lawyers and economists weighing in on policy matters.

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.

These categories correspond to the two different forms of AI: strong and weak. Strong AI generally refers to general machine-based cognitive capabilities, the strongest of which is sometimes also called artificial general intelligence (AGI). An AGI would have cognitive traits as broad and as plastic as human cognition, and would be able to engage on many different types of problems — perhaps even surpassing human ability.

The vast majority of AI experts agree that such AGI and especially so-called superintelligence claims are wildly overplayed and that there is no possibility of machines gaining human-equivalent abilities any time soon — or perhaps ever. “In any ranking of near-term worries about AI, superintelligence should be far down the list,” says AI expert Melanie Mitchell, author of Artificial Intelligence: A Guide for Thinking Humans.

Nonetheless, superintelligence claims attract considerable public attention because it conjures up gloom-and-doom scenarios. In popular culture, AGI figures prominently in the plots of many dystopian depictions of artificial intelligence, including many science-fiction books, movies, and television shows. Thus, while over-hyped and unrealistic, techno-panicky fears about superintelligent robots or AI systems will need to be addressed to ensure policy discussions are not dominated by sensationalism and irrational speculation about machines attaining human-level capabilities. This broad concern about AI is particularly acute in discussions about what governments should do to address existential risks or global catastrophic risks around “killer robots” or other military or law enforcement uses of AI. These issues will demand more serious consideration, but few free-market analysts are paying attention to them today.

Most of the AI policy action today involves various classes of narrow or “weak” AI applications, Weak AI executes a specific task extraordinarily well. Examples include mundane, behind-the-scenes functions such as playing games, image or language translation, or recommender systems on various websites. But narrow AI is also used in the other sectors already identified, such as medicine, fintech, energy, etc.

In one area of weak AI, transportation, free-market analysts and organizations are relatively well represented. A growing number of analysts and organizations are participating in the debate over autonomous driving and flying systems. These are critical policy areas that will continue to require attention. Unfortunately, the involvement of free-market analysts and organizations here is an outlier. Such views are not well-represented in many of the other sectors that computational science and machine learning are set to revolutionize.

This is why far more specialized knowledge — of both the technologies and the nuanced issues and policies surrounding them — will be essential. Tech analysts will need to work their way up entirely new learning curves and master a much wider array of topics and skills if they hope to defend AI innovation in targeted fields and sectors.

As research organizations get more involved in AI policy, they will need to consider whether they have the capacity to take on AI issues both generally and specifically. For many organizations, their core competency will likely lie in the targeted policy topics that they’ve long covered and for which they have skilled analysts who can expand their portfolio to include AI-related matters as AI enters those fields.

This is entirely logical, but a good grasp of the big picture — and some policy focus on it — is essential. Again, AI is amorphous and increasingly ubiquitous; technologies and related policy issues will collide and entangle as combinatorial innovation accelerates. Previously distinct technologies or issues will no longer be easily compartmentalized the way they were in the past.

For example, the safety, security, and privacy considerations surrounding data-driven and connected “smart” devices or applications in one sector (say, health care) could intersect with similar concerns in other fields (like financial technology) when their underlying technologies interact. Likewise, the regulation of algorithmic processes for one purpose (ex: online content moderation on social media sites), could end up creating a variety of unanticipated policy issues (ex: cybersecurity vulnerabilities or privacy considerations).

In sum, attempts to regulate computational capabilities in one way could have profound implications for many other technologies, sectors, and fields of science. Thus, when critics blithely suggests “we should take steps to control AI,” slow its development, or even shut it down, they are (perhaps unknowingly) recommending that we should take steps to control or influence a wide swath of economic activity and innovation.

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.”

So too for AI. Resistance to AI-driven technological change will grow far more intense. The challenge for innovation defenders will be to craft constructive responses to the many arguments and policies set forth by those who oppose further progress in our computation capabilities.

One thing should be clear: China and many other nations understand the stakes in the global AI race, and they are looking to greatly enhance their computational capabilities to ensure they possess the talent, firms, capital resources, and policies to challenge the U.S.’s early leadership in AI. America’s early lead in this race is an outgrowth of our success with the Internet, e-commerce, and digital technologies. That stunning success story was enabled by wise policy choices that promoted a dynamic culture of creativity and innovation and rejected calls to settle for 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? Will our nation’s governance vision be rooted in the power of permissionless innovation, giving entrepreneurs the green light to find new and better ways of improving the human condition with life-enriching and life-saving technologies? Or will our governance vision shackle innovators with precautionary principle-based regulatory mandates, that put up the red light or endless prior restraints on creative activity?

It’s time for liberty-loving analysts to step up and prepare to do their part to ensure the benefits of this revolution come to fruition. I personally plan to spend every waking moment of my life in coming years making the continuing case for the importance of innovation and progress in this crucial technological sector. Will you join me?

[I thank Neil Chilson for feedback on this essay.]

__________

Additional Reading

• Adam Thierer, “‘Running Code and Rough Consensus’ for AI: Polycentric Governance in the Algorithmic Age,” Medium, September 1, 2022.
• Adam Thierer, “AI Governance ‘on the Ground’ vs ‘on the Books,’” Medium, August 19, 2022.
• Adam Thierer, “Why the Future of AI Will Not Be Invented in Europe,” Technology Liberation Front, August 1, 2022.
• Adam Thierer, “Existential Risks & Global Governance Issues around AI & Robotics,” [DRAFT CHAPTER, July 2022].
• Adam Thierer, “How Science Fiction Dystopianism Shapes the Debate over AI & Robotics,” Discourse, July 26, 2022.
• Adam Thierer, “Why is the US Following the EU’s Lead on Artificial Intelligence Regulation?” The Hill, July 21, 2022.
• Adam Thierer, “Algorithmic Auditing and AI Impact Assessments: The Need for Balance,” Medium, July 13, 2022.
• Adam Thierer, “The Proper Governance Default for AI,” Medium, May 26, 2022.
• Adam Thierer, “What I Learned about the Power of AI at the Cleveland Clinic,” Medium, May 6, 2022.
• Adam Thierer, Governing Emerging Technology in an Age of Policy Fragmentation and Disequilibrium, American Enterprise Institute (April 2022).
• Adam Thierer and John Croxton, “Elon Musk and the Coming Federal Showdown Over Driverless Vehicles,” Discourse, November 22, 2021.
• Adam Thierer, “A Global Clash of Visions: The Future of AI Policy,” The Hill, May 4, 2021.
• Adam Thierer, “A Brief History of Soft Law in ICT Sectors: Four Case Studies,” Jurimetrics, Vol. 61 (Fall 2021): 79–119.
• Adam Thierer, “U.S. Artificial Intelligence Governance in the Obama–Trump Years,” IEEE Transactions on Technology and Society, Vol, 2, Issue 4 (2021).
• Adam Thierer, “The Worst Regulation Ever Proposed,” The Bridge, September 2019.
• Ryan Hagemann, Jennifer Huddleston Skees & Adam Thierer, “Soft Law for Hard Problems: The Governance of Emerging Technologies in an Uncertain Future,” Colorado Technology Law Journal, Vol. 17 (2018).
• Adam Thierer & Trace Mitchell, “No New Tech Bureaucracy,” Real Clear Policy, September 10, 2020.
• Adam Thierer, “OMB’s AI Guidance Embodies Wise Tech Governance,” Mercatus Center Public Comment, March 13, 2020.
• Adam Thierer, “Europe’s New AI Industrial Policy,” Medium, February 20, 2020.
• Adam Thierer, “Trump’s AI Framework & the Future of Emerging Tech Governance,” Medium, January 8, 2020.
• Adam Thierer, “Soft Law: The Reconciliation of Permissionless & Responsible Innovation,” Chapter 7 in Adam Thierer, Evasive Entrepreneurs & the Future of Governance (Washington, DC: Cato Institute, 2020): 183–240.
• Andrea O’Sullivan & Adam Thierer, “Counterpoint: Regulators Should Allow the Greatest Space for AI Innovation,” Communications of the ACM, Volume 61, Issue 12, (December 2018): 33–35.
• Adam Thierer, Andrea O’Sullivan & Raymond Russell, “Artificial Intelligence and Public Policy,” Mercatus Research (2017).
• Adam Thierer, “Shouldn’t the Robots Have Eaten All the Jobs at Amazon By Now?” Technology Liberation Front, July 26, 2017.
• Adam Thierer, “Are ‘Permissionless Innovation’ and ‘Responsible Innovation’ Compatible?” Technology Liberation Front, July 12, 2017.
• Adam Thierer, “The Growing AI Technopanic,” Medium, April 27, 2017.
• Adam Thierer, “The Day the Machines Took Over,” Medium, May 11, 2017.
• Adam Thierer, “When the Trial Lawyers Come for the Robot Cars,” Slate, June 10, 2016.
• Adam Thierer, “Learning by Doing,” the Process of Innovation & the Future of Employment,” Technology Liberation Front, September 25, 2015.
• Adam Thierer, “Problems with Precautionary Principle-Minded Tech Regulation & a Federal Robotics Commission,” Medium, September 22, 2014.
• Adam Thierer, “On the Line between Technology Ethics vs. Technology Policy,” Technology Liberation Front, August 1, 2013.

[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

• Adam Thierer, “My Forthcoming Book on Artificial Intelligence & Robotics Policy,” Medium, July 22, 2022.
• Adam Thierer, “Responses to Jack Clark’s AI Policy Tweetstorm,” Medium, August 8, 2022.
• Adam Thierer, “Why the Future of AI Will Not Be Invented in Europe,” Technology Liberation Front, August 1, 2022.
• Adam Thierer, “How Science Fiction Dystopianism Shapes the Debate over AI & Robotics,” Discourse, July 26, 2022.
• Adam Thierer, “Why is the US Following the EU’s Lead on Artificial Intelligence Regulation?” The Hill, July 21, 2022.
• Adam Thierer, “Algorithmic Auditing and AI Impact Assessments: The Need for Balance,” Medium, July 13, 2022.
• Adam Thierer, “What I Learned about the Power of AI at the Cleveland Clinic,” Medium, May 6, 2022.
• Adam Thierer, Governing Emerging Technology in an Age of Policy Fragmentation and Disequilibrium, American Enterprise Institute (April 2022).
• Adam Thierer and John Croxton, “Elon Musk and the Coming Federal Showdown Over Driverless Vehicles,” Discourse, November 22, 2021.
• Adam Thierer, “A Global Clash of Visions: The Future of AI Policy,” The Hill, May 4, 2021.
• Adam Thierer, “A Brief History of Soft Law in ICT Sectors: Four Case Studies,” Jurimetrics, Vol. 61 (Fall 2021): 79–119.
• Adam Thierer, “U.S. Artificial Intelligence Governance in the Obama–Trump Years,” IEEE Transactions on Technology and Society, Vol, 2, Issue 4 (2021).
• Adam Thierer, “The Worst Regulation Ever Proposed,” The Bridge, September 2019.
• Ryan Hagemann, Jennifer Huddleston Skees & Adam Thierer, “Soft Law for Hard Problems: The Governance of Emerging Technologies in an Uncertain Future,” Colorado Technology Law Journal, Vol. 17 (2018).
• Adam Thierer & Trace Mitchell, “No New Tech Bureaucracy,” Real Clear Policy, September 10, 2020.
• Adam Thierer, “OMB’s AI Guidance Embodies Wise Tech Governance,” Mercatus Center Public Comment, March 13, 2020.
• Adam Thierer, “Europe’s New AI Industrial Policy,” Medium, February 20, 2020.
• Adam Thierer, “Trump’s AI Framework & the Future of Emerging Tech Governance,” Medium, January 8, 2020.
• Adam Thierer, “Soft Law: The Reconciliation of Permissionless & Responsible Innovation,” Chapter 7 in Adam Thierer, Evasive Entrepreneurs & the Future of Governance (Washington, DC: Cato Institute, 2020): 183–240.
• Andrea O’Sullivan & Adam Thierer, “Counterpoint: Regulators Should Allow the Greatest Space for AI Innovation,” Communications of the ACM, Volume 61, Issue 12, (December 2018): 33–35.
• Adam Thierer, Andrea O’Sullivan & Raymond Russell, “Artificial Intelligence and Public Policy,” Mercatus Research (2017).
• Adam Thierer, “Shouldn’t the Robots Have Eaten All the Jobs at Amazon By Now?” Technology Liberation Front, July 26, 2017.
• Adam Thierer, “Are ‘Permissionless Innovation’ and ‘Responsible Innovation’ Compatible?” Technology Liberation Front, July 12, 2017.
• Adam Thierer, “The Growing AI Technopanic,” Medium, April 27, 2017.
• Adam Thierer, “The Day the Machines Took Over,” Medium, May 11, 2017.
• Adam Thierer, “When the Trial Lawyers Come for the Robot Cars,” Slate, June 10, 2016.
• Adam Thierer, “Learning by Doing,” the Process of Innovation & the Future of Employment,” Technology Liberation Front, September 25, 2015.
• Adam Thierer, “Problems with Precautionary Principle-Minded Tech Regulation & a Federal Robotics Commission,” Medium, September 22, 2014.
• Adam Thierer, “On the Line between Technology Ethics vs. Technology Policy,” Technology Liberation Front, August 1, 2013.

For my latest column in The Hill, I explored the European Union’s (EU) endlessly expanding push to regulate all facets of the modern data economy. That now includes a new effort to regulate artificial intelligence (AI) using the same sort of top-down, heavy-handed, bureaucratic compliance regime that has stifled digital innovation on the continent over the past quarter century.

The European Commission (EC) is advancing a new Artificial Intelligence Act, which proposes banning some AI technologies while classifying many others under a heavily controlled “high-risk” category. A new bureaucracy, the European Artificial Intelligence Board, will be tasked with enforcing a wide variety of new rules, including “prior conformity assessments,” which are like permission slips for algorithmic innovators. Steep fines are also part of the plan. There’s a lengthy list of covered sectors and technologies, with many others that could be added in coming years. It’s no wonder, then, that the measure has been labelled the measure “the mother of all AI laws” and analysts have argued it will further burden innovation and investment in Europe.

As I noted in my new column, the consensus about Europe’s future on the emerging technology front is dismal to put it mildly. The International Economy journal recently asked 11 experts from Europe and the U.S. where the EU currently stood in global tech competition. Responses were nearly unanimous and bluntly summarized by the symposium’s title: “The Biggest Loser.” Respondents said Europe is “lagging behind in the global tech race,” and “unlikely to become a global hub of innovation.” “The future will not be invented in Europe,” another analyst bluntly concluded.

That’s a grim assessment, but there is no doubt that European competitiveness is suffering today and that excessive regulation plays a fairly significant role in causing it. As I noted in my column, “the EU’s risk-averse culture and preference for paperwork compliance over entrepreneurial freedom” had serious consequences for continent-wide innovation.  I note in my recent column how:

After the continent piled on layers of data restrictions beginning in the mid-1990s, innovation and investment suffered. Regulation grew more complex with the 2018 General Data Protection Regulation (GDPR), which further limits data collection and use. As a result of all the red tape, the EU came away from the digital revolution with “the complete absence of superstar companies.” There are no serious European versions of Microsoft, Google, Facebook, Apple or Amazon. Europe’s leading providers of digital technology services today are American-based companies.

Let’s take a look at a few numbers that illustrate what’s happened in Europe’s tech sector over the past quarter century. Here’s an old KPGM breakdown of market caps for public Internet companies over an important 20 year period, from 1995 to 2015, when the digital technology marketplace was taking shape. Besides the remarkable amount of churn over that period (with only Apple appearing on both lists), the other notable thing is the complete absence of any European companies in 2015.

Next, here’s a chart I constructed using CB Insights data for global unicorns ($billion valued companies) from 2010 up through early 2022. It shows how the U.S. dominates fully half the list with China having a 16% share, but all of the European Union’s firms equal just a 9 percent slice of the world’s share.

If you want to see a per capita breakdown of VC investment by country, here’s a handy Crunchbase News chart. While the U.S. is geographically much larger than Europe, a breakdown of VC funding on a per capita basis reveals that only Estonia ($915B) and Sweden ($700B) have startup investment on par with America ($808B). No other European country has even half as much per capita VC investment as the U.S., and most don’t even have a quarter as much.

As we enter the “age of AI,” what will the EU’s same regulatory model for mean for AI, machine learning, and robotics in Europe? We do have some early data on that, too. Here’s a breakdown of AI-related VC activity and AI unicorn in 2021 from the recent State of AI Report 2021, with European countries already trailing far behind:

Also, here’s some data on recent AI investment by region from the latest Stanford “AI Index Report 2022” which again highlights a gap that is only growing larger:

It’s important to listen to what actual AI innovators across the Atlantic have to say about the new EU regulatory efforts. Just last month, the UK-based Coalition for a Digital Economy (Coadec), an advocacy group for Britain’s technology-led startups, published a report entitled, “What do AI Startups Want from Regulation?” Coadec surveyed its members to gauge their feelings about the EU’s proposed approach to AI regulation, as well as the UK’s. 76% of those startups said that their business model would be either negatively affected or become infeasible if the UK were to echo the EU by making AI developers liable, and an equal percentage said they had varying concerns about whether it’s technically even feasible to make their datasets “free of errors,” as the EU looks set to demand. Respondents also said they feared that the new AI Act would be particularly burdensome to small and mid-size entrepreneurs because they cannot afford to deal with the costly compliance hassles like the larger competitors they face. This would end of being a replay of the burdens they faced from GDPR, which decimated small businesses. “The experience of GDPR demonstrated how unclear, complex and expensive regulations drove many startups out of business, and disproportionately impact startups that survived–GDPR compliance cost startups significantly more than it did the Tech Giants,” the Coadec report concluded.

At least those UK-based innovators might be in a slightly better position post-Brexit with the British government now looking to chart a different–and much less burdensome–governance approach for digital technologies. In fact, the UK government recently released a major policy document on “Establishing a Pro-Innovation Approach to Regulating AI,” which makes a concerted effort to distinguish its approach from the EU’s. “We will ask that regulators focus on high risk concerns rather than hypothetical or low risks associated with AI,” the report noted. “We want to encourage innovation and avoid placing unnecessary barriers in its way.” This is consistent with what the UK government has been saying on technology governance more generally. For example, in recent report advocating for Innovation Friendly Regulation, the UK government’s Regulatory Horizons Council argued that, when it comes to the regulation of emerging technologies like AI, “it is also necessary to consider the risk that the intervention itself poses.” “This would include the potential impact on benefits from a particular innovation that might be foregone; it would also include the potential creation of a ‘chilling effect’ on innovation more generally,” the Council concluded. Clearly, this approach to technology policy stands in stark contrast to the EU’s heavy-handed model. So, there is a chance that at least some innovators based in the UK can escape the EU’s regulatory hell.

What about AI innovators stuck on the European continent? What are they saying about the regulations they will soon face? The European DIGITAL SME Alliance, which is the largest network of small and medium sized enterprises (SMEs) in the European ICT sector, represents roughly 45,000 digital SMEs. In comments to the EC about the impact of the law, the Alliance highlighted how costly the AI Act’s conformity assessments and other regulations will be for smaller innovators. “This may put a burden on AI innovation” the Alliance argued, because smaller developers have limited financial and human resources of SMEs.” “[A] regulation that requires SMEs to make these significant investments, will likely push SMEs out of the market,” the group noted. “This is exactly the opposite of the intention to support a thriving and innovative AI ecosystem in Europe.” Moreover, “SMEs will not be able to pass on these costs to their customers in the final customer end pricing,” the Alliance correctly noted because, “[t[he market is global and highly competitive. Therefore, customers will choose cheaper solutions and Europe risks to be left behind in technology development and global competition.”

In March, the Alliance also hosted a forum on “The European AI Act and Digital SMEs,” which featured comments from some operators in this space. Some speakers were quite timid and you could sense that they might have feared pushing back too aggressively against the European Commission so as not to get on the bad side of regulators before the rules go into effect. But Mislav Malenica, Founder & CEO Mindsmiths didn’t pull any punches in his remarks. His company Mindsmiths is trying to build autonomous support systems in many different fields, but their ability to innovate and compete globally will be severely curtailed by the EU AI Act, he argued.

I usually don’t spend time transcribing people’s comments from events, but I went back and watched Malenica’s multiple times because his remarks are so powerful and I wanted to make sure others hear what he was saying. [Malenica’s opening comments during the event run from 42:29 to 49:34 of the video and then he has more to say during Q&A beginning at the 1:27:28 of the video.] Here’s a quick summary of a few of Malenica’s key points (listed chronologically):

• “I’m not sure we are doing everything we can do actually to create an environment that’s innovation friendly.”
• “we see a lot of uncertainty. We see fear.”
• “basically we won’t be able to get funding here.”
• while reading through the AI Act, he notes, “I don’t see start-ups being mentioned anywhere, and startups are the main vehicles of innovation.” […] “I find it very arrogant”
• if AI Act becomes law, “what we’ll do in Europe is we’ll create a new market and that’s the AI markets based on fear,” and in how to just build products that avoid the wrath of government or lawsuits.
• “we are really stifling innovation” and that means Europeans will have to import autonomous products from foreign companies instead of making them there.

Later, during in the Q&A period, Malenica notes how his first virtual currency startup had to use half it’s investment capital just dealing with regulatory compliance issues, and most venture capitalists wouldn’t get behind launching in Europe because of such legal hassles. He reflects upon what this mean for other innovators going forward as the EU prepares to expand their regulatory regime for AI sectors:

• “I don’t think we’re missing talent. That’s just a consequence” of all the regulation. “We are missing a sense that you have opportunities here. If you the opportunities here, then the talent will come, the funding will come, and so on because people see that they’ll be able to make money, they’ll be able to build companies, and so on.”
• “If we now take a look at the 10 biggest companies market capitalizations in the world, we’ll see that none of them comes actually from Europe” with U.S. tech companies dominating the list. “So, we missed that wave completely.” Why? “Because we didn’t inspire anyone to take action,” and that is about to happen for AI.
• “We need to decide if we are going to be a land of opportunities, or will we be just consumers of other people’s tech, the same we are right now” for digital software and services.
• “We’re already finding excuses for the loss” of the AI market, he argues.

Malenica’s comments are extraordinarily demoralizing if you care about innovation. Now, I’m an American and one way to look at this dismal situation is that, by hobbling its own startups and existing AI innovators, Europe is doing the U.S. another favor by essentially taking itself out of the running in next great global tech race. Europe’s actions may also mean that America gains many of their best and brightest if they come to the U.S. when looking to create the next great algorithmic service or application because they can’t do so in the EU. This is exactly what happened over the past few decades for Internet startups, Malenica noted.

But that’s dismal news in another sense. Europe is filled with brilliant innovators, highly-skilled talent, world-class educational institutions, and even many venture capitalists looking to invest in this arena. Unfortunately, the continent’s suffocating regulatory approach makes it nearly impossible for digital technology innovators to have a fighting chance. Through their heavy-handed policies, European officials have essentially declared their innovators “guilty until proven innocent.” And that means that Europeans and the rest of the world are being deprived of many important life-enriching and life-saving AI applications that those innovators could create. Technological innovation is not a zero-sum game that only one country can “win.” Innovation drives growth and prosperity and lifts all boats as its benefits spread throughout the world. When European innovators prosper, people all over the world prosper along with them.

Is there any chance the European Commission softens its stance toward emerging technologies and looks to adopt a more flexible governance approach that instead treats AI innovators as innocent until proven guilty? I think it is extremely unlikely that will happen because, as Malenica noted, European technology policy is too rooted in fear of disruption and extreme risk-aversion. EU officials are forgetting that the most important lesson from the history of technological innovation is there can be no progress without some risk-taking and corresponding disruption. My favorite quote about the relationship between risk-taking and human progress comes from Wilbur Wright who, along with his brother, helped pioneer human flight. “If you are looking for perfect safety,” Wright said, “you would do well to sit on a fence and watch the birds.” European policymakers are essentially forcing their best and brightest innovators to sit on the fence and watch the rest of the world fly right past them on the digital technology and AI front. The ramifications for the continent will be disastrous. Regardless, as I noted in concluding my recent Hill column, Europe’s approach to AI “shouldn’t be the model the U.S. follows if it hopes to maintain its early lead in AI and robotics. America should instead welcome European companies, workers and investors looking for a more hospitable place to launch bold new AI innovations.”

Alas, European officials appear ready to ignore the deleterious impact of their policies on innovation and competition and instead make regulation their leading export to the world. In fact, the European Commission will soon open a San Francisco office to work more closely with Silicon Valley companies affected by EU tech regulation. European leaders have basically surrendered on the idea of home-grown innovation and are now plowing all their energies into regulating the rest of the world’s largest digital technology companies, most of which are headquartered in the United States. It’s no wonder, then, that The Economist magazine concludes that, “Europe is the free-rider continent” that “has piggybacked on innovation from elsewhere, keeping up with rivals, not forging ahead.” Instead, “the cuddly form of capitalism embraced in Europe has markedly failed to create world-beating companies,” the magazine argues.

European officials want us to believe that they are somehow doing the world a favor by being its global tech regulator, when instead the are simply solidifying the power of the largest digital tech companies, who are the only ones with enough resources–mainly in the form of massive legal compliance teams–to live under the EU’s innovation-crushing regulations. Sadly, many US policymakers hate our own home-grown tech companies so much now, that they are willing to let this happen. In a better world, those American lawmakers would stand up to European officials looking to bully tech innovators and we would reject the innovation-killing recipe that the EU is cooking up for AI markets and expects the rest of the world to eat.

Additional Reading on AI & Robotics:

• Adam Thierer, “How Science Fiction Dystopianism Shapes the Debate over AI & Robotics,” Discourse, July 26, 2022.
• Adam Thierer, “Why is the US Following the EU’s Lead on Artificial Intelligence Regulation?” The Hill, July 21, 2022.
• Adam Thierer, “Algorithmic Auditing and AI Impact Assessments: The Need for Balance,” Medium, July 13, 2022.
• Adam Thierer, “What I Learned about the Power of AI at the Cleveland Clinic,” Medium, May 6, 2022.
• Adam Thierer, Governing Emerging Technology in an Age of Policy Fragmentation and Disequilibrium, American Enterprise Institute (April 2022).
• Adam Thierer, “How to Get the Future We Were Promised,” Discourse, January 18, 2022.
• Adam Thierer, “A Global Clash of Visions: The Future of AI Policy,” The Hill, May 4, 2021.
• Adam Thierer, “A Brief History of Soft Law in ICT Sectors: Four Case Studies,” Jurimetrics, Vol. 61 (Fall 2021): 79-119.
• Adam Thierer, “Artificial Intelligence Governance in the Obama–Trump Years,” IEEE Transactions on Technology and Society, Vol, 2, Issue 4 (2021).
• Adam Thierer, “The Worst Regulation Ever Proposed,” The Bridge, September 2019.
• Ryan Hagemann, Jennifer Huddleston Skees & Adam Thierer, “Soft Law for Hard Problems: The Governance of Emerging Technologies in an Uncertain Future,” Colorado Technology Law Journal, Vol. 17 (2018).
• Adam Thierer & Trace Mitchell, “No New Tech Bureaucracy,” Real Clear Policy, September 10, 2020.
• Adam Thierer, “OMB’s AI Guidance Embodies Wise Tech Governance,” Mercatus Center Public Comment, March 13, 2020.
• Adam Thierer, “Europe’s New AI Industrial Policy,” Medium, February 20, 2020.
• Adam Thierer, “Trump’s AI Framework & the Future of Emerging Tech Governance,” Medium, January 8, 2020.
• Adam Thierer, “Soft Law: The Reconciliation of Permissionless & Responsible Innovation,” Chapter 7 in Adam Thierer, Evasive Entrepreneurs & the Future of Governance (Washington, DC: Cato Institute, 2020): 183-240.
• Andrea O’Sullivan & Adam Thierer, “Counterpoint: Regulators Should Allow the Greatest Space for AI Innovation,” Communications of the ACM, Volume 61, Issue 12, (December 2018): 33-35.
• Adam Thierer, Andrea O’Sullivan & Raymond Russell, “Artificial Intelligence and Public Policy,” Mercatus Research (2017).
• Adam Thierer, “Shouldn’t the Robots Have Eaten All the Jobs at Amazon By Now?” Technology Liberation Front, July 26, 2017.
• Adam Thierer, “Are ‘Permissionless Innovation’ and ‘Responsible Innovation’ Compatible?” Technology Liberation Front, July 12, 2017.
• Adam Thierer, “The Growing AI Technopanic,” Medium, April 27, 2017.
• Adam Thierer, “The Day the Machines Took Over,” Medium, May 11, 2017.
• Adam Thierer, “When the Trial Lawyers Come for the Robot Cars,” Slate, June 10, 2016.
• Adam Thierer, “Learning by Doing,” the Process of Innovation & the Future of Employment,” Technology Liberation Front, September 25, 2015.
• Adam Thierer, “Problems with Precautionary Principle-Minded Tech Regulation & a Federal Robotics Commission,” Medium, September 22, 2014.
• Adam Thierer, “On the Line between Technology Ethics vs. Technology Policy,” Technology Liberation Front, August 1, 2013.

[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

• Dean Ball, Greg Lukianoff & Adam Thierer, “How state AI regulations threaten innovation, free speech, and knowledge creation,” The Eternally Radical Idea, April 3, 2025.
• Adam Thierer, “Comments of R Street Institute on a Learning Period Moratorium for AI Regulation in Response to Request for Information (RFI) Exploring a Data Privacy and Security Framework,” R Street Institute Regulatory Comments, Apr. 3, 2025.
• PODCAST: “Lawfare Daily: Adam Thierer on the AI Regulatory Landscap e,” Lawfare, Apr. 1, 2025.
• Adam Thierer, “Texas & Virginia Steer States Away from European-Style AI Regulation,” R Street Analysis, Mar. 25, 2025. [Also reprinted as: Adam Thierer, “More States Reject Fear-Based AI Regulation,” Governing, Mar. 27, 2025.]
• Adam Thierer, “Don’t let the states derail America’s AI revolution,” The Hill, March 23, 2025.
• Adam Thierer, “Comments of the R Street Institute in Request for Information on the Development of an Artificial Intelligence (AI) Action Plan,” March 15, 2025.
• PODCAST: “A tech policy bonanza! The FCC, FTC, AI regulations, and more,” So to Speak (FIRE) Podcast, March 12, 2025.
• TESTIMONY: Adam Thierer, “R Street Testimony in Opposition to CT SB 2: ‘An Act Concerning Artificial Intelligence’,” Feb. 25, 2025.
• Adam Thierer & Robert Melvin, “R Street Institute Letter to Virginia Governor Glenn Youngkin in Opposition to VA HB 2094, Restrictions on Artificial Intelligence,” Feb. 20, 2025.
• Adam Thierer, “Ramifications of China’s DeepSeek Moment, Part 3: What Both Parties Need to Accept and Do Next,” R Street Analysis, Feb. 18, 2025.
• Adam Thierer, “The Radicalism of the ‘Future for the Family’ Technology Manifesto,” Medium, Feb, 17, 2025.
• Adam Thierer, “Vice President JD Vance Resets the Global AI Agenda with Paris AI Action Summit Address” R Street Real Analysis, Feb. 11, 2025.
• Adam Thierer, “Ramifications of China’s DeepSeek Moment, Part 2: AI, Cultural Values, and Global Freedom,” R Street Analysis, Feb. 7, 2025.
• Adam Thierer, “Can Trump Hold the Tech Right and Populist Right Together?” Discourse, Feb. 7, 2025.
• TESTIMONY: Adam Thierer, “Testimony In Opposition to LB 642, “The Artificial Intelligence Consumer Protection Act,” Feb. 5, 2025.
• Adam Thierer, “Ramifications of China’s DeepSeek Moment, Part 1: AI, Technological Supremacy and National Security,” R Street Analysis, Feb. 3, 2025.
• Keegan McBride & Adam Thierer, “The Trouble With AI Safety Treaties,” Lawfare, Jan. 29, 2025.
• TESTIMONY: Adam Thierer, “R Street Testimony in Opposition to VA HB 2094: ‘High-Risk Artificial Intelligence Developer and Deployer Act,”’ Jan. 27, 2025.
• Adam Thierer, “Updated Compendium of Bills Pushed by theMultistate AI Policymaker Working Group,” Medium, Jan. 23, 2025. [regularly updated]
• Adam Thierer, “Trump’s New AI Executive Order Begins Undoing Biden’s Bureaucratic Mess,” R Street Analysis, Jan. 23, 2025.
• EVENT: “The Worst Tech Policies of 2024: How the New Administration and Congress Can Turn the Page ,” ITIF, Jan. 21, 2024.

2024

• Adam Thierer, “The House AI Task Force Report: Positive Steps, but One Big Problem,” Medium, Dec. 17, 2024.
• EVENT VIDEO: “AI Policy In President Trump’s Second Term,” Federalist Society Webinar, Dec. 10, 2024.
• Adam Thierer, “Testimony Notes for Presentation to Future of Privacy Forum Multistate AI Working Group,” Dec. 9, 2024.
• Joint letter: Letter from coalition of over 20 groups opposing “Texas Responsible AI Governance Act”, Dec. 2024.
• Adam Thierer, “What Trump’s New AI Czar David Sacks Can Do to Hit the Ground Running,” Medium, Dec. 6, 2024.
• EVENT VIDEO: “Understanding AI & AI Policy in 2024 and Beyond,” Cato Institute event, Dec. 5, 2024.
• Adam Thierer, “There are Two Different AI Policy Debates, and You Need to Start Paying More Attention to the One about ‘Woke AI,’” Medium, Nov 11, 2024.
• Adam Thierer, “AI Policy in the Trump Administration and Congress after the 2024 Elections,” R Street Analysis, Nov. 7, 2024.
• Adam Thierer, “The 2024 Election Results & AI Policy: Here Comes the Mother of All State Regulatory Patchworks,” Medium, Nov. 6, 2024.
• Adam Thierer, “Texas should reject the European path toward AI regulation,” R Street Analysis, Oct. 31, 2024.
• EVENT VIDEO: “What Should the Next Administration Do About AI?” Federalist Society Regulatory Transparency Project, [featuring Ash Kazaryan, Adam Kovacevich, Neil Chilson, and Adam Thierer moderating], Oct. 15, 2024.
• Adam Thierer, “AI and Public Health, Part 3: How AI Can Revolutionize Drug Discovery,” R Street Real Solutions, Oct. 15, 2024.
• Adam Thierer, “AI Is Not the Cause of Rental Woes,” NH Journal, Oct. 14, 2024.
• PODCAST: “AI Policy and Innovation ,” The Spirit of Enterprise, Episode #510, October 2024
• Neil Chilson & Adam Thierer, “A Sensible Approach to State AI Policy,” Federalist Society Regulatory Transparency Project blog, Oct. 9, 2024.
• PODCAST: “Where AI Regulation Can Go Wrong,” The Road to Accountable AI, October 2024.
• Adam Thierer, “California Rejects AI Regulatory Extremism,” R Street Analysis, Sept. 30, 2024.
• Adam Thierer, “Eurocrats plot to hobble US AI leadership on our own shores,” The Hill, Sept. 28, 2024.
• PODCAST: “Navigating AI Policy: Balancing Innovation and Regulation ,” Corner Alliance’s AI, Government, and the Future Podcast, Sept. 18, 2024.
• Adam Thierer, “Biden’s Move Against Nvidia Is a Gift to China,” City Journal, Sept. 16, 2024.
• PODCAST: “California’s AI Law SB 1047 & What It Means for Tech — Adam Thierer,” SVIC Podcast, Sept. 10, 2024.
• Joint letter: “Coalition Urges Governor Newsom To Consider Vetoing SB 1047,” August 27, 2024.
• Adam Thierer, “W​here Does California’s AI Bill (SB 1047) Fit Historically?” Medium, Aug. 26, 2024.
• Adam Thierer, “The Policy Origins of the Digital Revolution & the Continuing Case for the Freedom to Innovate,” R Street Real Solutions, Aug. 15, 2024. [+ video of panel talk]
• Adam Thierer, “AI and Public Health Series: Part 2: How AI Can Help Tackle Major Causes of Suffering and Death,” R Street Analysis, August 6, 2024.
• Adam Thierer, “Regulators are misguided in efforts to restrict open-source AI,” Cointelegraph, July 31, 2024.
• Adam Thierer, “How Trump and Harris Clash on AI Policy,” Medium, July 24, 2024.
• Adam Thierer, “The Hickenlooper AI Auditing Bill and the Expanding Role of the Commerce Department in AI Policy,” R Street Real Solutions, July 22. 2024.
• Adam Thierer, “AI and Public Health Series: How AI can advance medical knowledge and improve the patient experience,” R Street Analysis, July 9, 2024.
• Adam Thierer, “AI and Public Health Series: How AI can advance medical knowledge and improve the patient experience,” R Street Analysis, July 9, 2024.
• Adam Thierer, “AI and Public Health Series: Introduction,” R Street Analysis, July 9, 2024.
• Adam Thierer, “Why the End of Chevron Deference is Largely Meaningless for AI Policy, Part 2,” Medium, July 2, 2024.
• Adam Thierer, “What the Supreme Court Decisions This Week Mean for AI Policy,” Medium, June 28, 2024.
• Joint letter: “Coalition Letter on California bill SB-1047, The Safe and Secure Innovation for Frontier Artificial Intelligence Systems Act,” June 18, 2024.
• WEBINAR: “AI Policy Roundup,” Federalist Society, June 6, 2024.
• TESTIMONY: Adam Thierer, Testimony for U.S. Joint Economic Committee Hearing on “Artificial Intelligence and Its Potential to Fuel Economic Growth and Improve Governance,” June 4, 2024.
• PODCAST: “Adam Thierer on regulating AI,” Faster, Please! — The Podcast #49, May 30, 2024.
• Adam Thierer, “Getting AI Policy Right Through a Learning Period Moratorium,” R Street Real Solutions, May 29, 2024.
• Nirit Weiss-Blatt, Adam Thierer & Taylor Barkley, “The AI Technopanic and Its Effects ,” Abundance Institute report, May 2024.
• Adam Thierer, “Colorado Opens Door to an AI Patchwork as Congress Procrastinates,” R Street Analysis, May 20, 2024.
• Adam Thierer, “The Schumer AI Working Group Report: A Move Toward Policy Normalcy?” Medium, May 16, 2024.
• Group Letter: “A Pro-Innovation Framework for Artificial Intelligence,” May 6, 2024.
• Adam Thierer, “California and Other States Threaten to Derail the AI Revolution,” R Street Analysis, May 2, 2024.
• Adam Thierer, “Artificial Intelligence Legislative Outlook: Spring 2024 Update,” R Street Analysis, April 24, 2024.
• Adam Thierer, “Artificial Intelligence, Section 230 & Looming Liability Threats,” Medium, April 2, 2024.
• Adam Thierer, “Policymakers Should Let Open Source Play a Role in the AI Revolution,” R Street Institute Analysis, March 28, 2024.
• Adam Thierer, Comments in NTIA’s “Openness in AI Request for Comment” proceeding, March 21, 2024.
• Adam Thierer, Testimony for House Oversight Committee hearing on “White House Overreach on AI,” March 21, 2023.
• Adam Thierer, “We Can’t Predict the Future of Work,” in Navigating the Future of Work: Perspectives on Automation, AI, and Economic Prosperity, American Enterprise Institute, March 20, 2024.
• Adam Thierer, “Every Lawmaker Gets Their Own Personal AI Bill!,” Medium, March 1, 2024.
• Adam Thierer, “Artificial Intelligence Task Force: 10 Principles to Guide AI Policy,” R Street blog, February 21, 2024.
• Adam Thierer, “More on the Realpolitik of Global AI Regulation & Computational Control,” Medium, February 14, 2024.
• Adam Thierer, “AI and Technologies of Freedom in the Age of “Weaponized” Government,” R Street blog, February 8, 2024.
• Adam Thierer, “Will California lawmakers give AI innovators a chance?” Orange County Register, January 31, 2024.
• Adam Thierer, “State and local meddling threatens to undermine the AI revolution,” The Hill, January 21, 2024.
• Adam Thierer, “My 2024 Tech Policy Prediction is Same as Always: No Legislative Action,” Medium, January 8, 2024.

2023

• PODCAST: “AI: DC Policymakers Face a Crossroads,” DC EKG podcast, December 11, 2023.
• Adam Thierer & Shoshana Weissmann, “Without Section 230 Protections, Generative AI Innovation Will Be Decimated,” R Street blog, December 6, 2023.
• Adam Thierer, “Is AI Policy Compromise Possible? A Look at the Thune-Klobuchar AI Bill,” R Street blog, December 4, 2023.
• Neil Chilson & Adam Thierer, “Overregulating AI Will Disrupt Markets and Discourage Competition,” Bloomberg Law, November 17, 2023.
• Adam Thierer, “White House Executive Order Threatens to Put AI in a Regulatory Cage,” R Street blog, October 30, 2023.
• Adam Thierer, “Artificial Intelligence Legislative Outlook: Fall 2023 Update,” R Street blog, October 17, 2023.
• Adam Thierer, “Artificial Intelligence, Medical Devices & Soft Law Governance,” unpublished manuscript prepared for an Arizona State law school symposium, (Fall 2023)
• Adam Thierer, “AI Concessions and Commitments in the Name of Democratic Accountability,” Medium, September 28, 2023.
• EVENT: Debating Frontier AI Regulation, Brookings, September 14, 2023. (My remarks begin at 51-minute mark of the video).
• Adam Thierer, “Blumenthal-Hawley AI Regulatory Framework Escalates the War on Computation,” Medium, September 13, 2023.
• Adam Thierer, Statement for the Record, Hearing on “The Need for Transparency in Artificial Intelligence,” September 12, 2023.
• EVENT: “Who’s Leading on AI Policy?” Cato Institute event, September 12, 2023.
• Neil Chilson & Adam Thierer, “Resolving to Defend AI Innovation in the States,” Now + Next, July 24, 2024.
• Adam Thierer, “Will AI Policy Became a War on Open Source Following Meta’s Launch of LLaMA 2?” Medium, July 19, 2023.
• Adam Thierer, “The FTC Looks to Become the Federal AI Commission,” Medium, July 15, 2023.
• Adam Thierer, “Is Telecom Licensing a Good Model for Artificial Intelligence?” Medium, July 8, 2023.
• SLIDES: “AI Worldviews: Similarities & Differences” (July 2023).
• Adam Thierer, “The Schumer AI Framework and the Future of Emerging Tech Policymaking,” R Street Institute Real Solutions, June 27, 2023.
• Adam Thierer, “Is AI Really an Unregulated Wild West?” Technology Liberation Front, June 22, 2023.
• Adam Thierer, “The Most Important Principle for AI Regulation,” R Street Institute Real Solutions, June 21, 2023.
• INTERVIEW: “5 Quick Questions for AI policy analyst Adam Thierer,” interview for the Faster Please! newsletter with James Pethokoukis, June 12, 2024.
• PODCAST: “Who’s Afraid of Artificial Intelligence?” Tech Freedom TechPolicyPodcast, June 12, 2023.
• Adam Thierer, “Existential Risks & Global Governance Issues around AI & Robotics,” R Street Institute Policy Study No. 291 (June 2023).
• FILING: Comments of Adam Thierer, R Street Institute to the National Telecommunications and Information Administration (NTIA) on “AI Accountability Policy,” June 12, 2023.
• PODCAST: Adam Thierer: “Artificial Intelligence For Dummies,” SheThinks (Independent Women’s Forum) podcast, June 9, 2023.
• EVENT: “Does the US Need a New AI Regulator?” Center for Data Innovation & R Street Institute, June 6, 2023.
• Neil Chilson & Adam Thierer, “The Problem with AI Licensing & an ‘FDA for Algorithms,’” Federalist Society Blog, June 5, 2023.
• Adam Thierer, “The Many Ways Government Already Regulates Artificial Intelligence,” Medium, June 2, 2023.
• Adam Thierer, “Microsoft’s New AI Regulatory Framework & the Coming Battle over Computational Control,” Medium, May 29, 2023.
• PODCAST: Neil Chilson & Adam Thierer, “The Future of AI Regulation: Examining Risks and Rewards,” Federalist Society Regulatory Transparency Project podcast, May 26, 2023.
• Adam Thierer, “Here Come the Code Cops: Senate Hearing Opens Door to FDA for Algorithms & AI Occupational Licensing,” Medium, May16, 2023.
• Adam Thierer, “What OpenAI’s Sam Altman Should Say at the Senate AI Hearing,” R Street Institute Blog, May 15, 2023.
• PODCAST: “Should we regulate AI?” Adam Thierer and Matthew Lesh discuss artificial intelligence policy on the Institute for Economic Affairs podcast, May 6, 2023.
• Adam Thierer, “The Biden Administration’s Plan to Regulate AI without Waiting for Congress,” Medium, May 4, 2023.
• Adam Thierer, “NEPA for Al? The Problem with Mandating Algorithmic Audits & Impact Assessments,” Medium, April 23, 2023.
• Adam Thierer, “Flexible, Pro-Innovation Governance Strategies for Artificial Intelligence,” R Street Institute Policy Study No. 283 (April 2023).
• Adam Thierer, “A balanced AI governance vision for America,” The Hill, April 16, 2023.
• Adam Thierer, Brent Orrell, & Chris Meserole, “Stop the AI Pause,” AEI Ideas, April 6, 2023.
• Adam Thierer, “Getting AI Innovation Culture Right,” R Street Institute Policy Study No. 281 (March 2023).
• Adam Thierer, “Can We Predict the Jobs and Skills Needed for the AI Era?,” R Street Institute Policy Study No. 278 (March 2023).
• Adam Thierer, “U.S. Chamber AI Commission Report Offers Constructive Path Forward,” R Street Blog, March 9, 2023.
• Adam Thierer, “Statement for the Record on ‘Artificial Intelligence: Risks and Opportunities,'” U.S. Senate Homeland Security and Governmental Affairs Committee, March 8, 2023.
• Adam Thierer, “What If Everything You’ve Heard about AI Policy is Wrong?” Medium, February 20, 2023.
• Adam Thierer, “Policy Ramifications of the ChatGPT Moment: AI Ethics Meets Evasive Entrepreneurialism,” Medium, February 14, 2023.
• Adam Thierer, “Mapping the AI Policy Landscape Circa 2023: Seven Major Fault Lines,” R Street Blog, February 9, 2023.

2022

• Adam Thierer, “Artificial Intelligence Primer: Definitions, Benefits & Policy Challenges,” Medium, December 2, 2022.
• Neil Chilson & Adam Thierer, “The Coming Onslaught of ‘Algorithmic Fairness’ Regulations,” Regulatory Transparency Project of the Federalist Society, November 2, 2022.
• Adam Thierer, “We Really Need To ‘Have a Conversation’ About AI … or Do We?” Discourse, October 6, 2022.
• Adam Thierer, “How the Embedding of AI Ethics Works in Practice & How It Can Be Improved,” Medium, September 22, 2022.
• Adam Thierer, “No Goldilocks Formula for Content Moderation in Social Media or the Metaverse, But Algorithms Still Help,” Medium, September 13, 2022.
• Adam Thierer, “AI Eats the World: Preparing for the Computational Revolution and the Policy Debates Ahead,” Medium, September 10, 2022.
• Adam Thierer, “‘Running Code and Rough Consensus’ for AI: Polycentric Governance in the Algorithmic Age,” Medium, September 1, 2022.
• Adam Thierer, “AI Governance ‘on the Ground’ vs ‘on the Books,’” Medium, August 19, 2022.
• Adam Thierer, “Why the Future of AI Will Not Be Invented in Europe,” Technology Liberation Front, August 1, 2022.
• Adam Thierer, “How Science Fiction Dystopianism Shapes the Debate over AI & Robotics,” Discourse, July 26, 2022.
• Adam Thierer, “Why is the US Following the EU’s Lead on Artificial Intelligence Regulation?” The Hill, July 21, 2022.
• Adam Thierer, “Algorithmic Auditing and AI Impact Assessments: The Need for Balance,” Medium, July 13, 2022.
• Adam Thierer, “The Proper Governance Default for AI,” Medium, May 26, 2022.
• Adam Thierer, “What I Learned about the Power of AI at the Cleveland Clinic,” Medium, May 6, 2022.
• Adam Thierer, Governing Emerging Technology in an Age of Policy Fragmentation and Disequilibrium, American Enterprise Institute (April 2022).

2021 (and earlier)

• Adam Thierer and John Croxton, “Elon Musk and the Coming Federal Showdown Over Driverless Vehicles,” Discourse, November 22, 2021.
• Adam Thierer, “A Global Clash of Visions: The Future of AI Policy,” The Hill, May 4, 2021.
• Adam Thierer, “A Brief History of Soft Law in ICT Sectors: Four Case Studies,” Jurimetrics, Vol. 61 (Fall 2021): 79-119.
• Adam Thierer, “U.S. Artificial Intelligence Governance in the Obama–Trump Years,” IEEE Transactions on Technology and Society, Vol, 2, Issue 4 (2021).
• Adam Thierer, “The Worst Regulation Ever Proposed,” The Bridge, September 2019.
• Ryan Hagemann, Jennifer Huddleston Skees & Adam Thierer, “Soft Law for Hard Problems: The Governance of Emerging Technologies in an Uncertain Future,” Colorado Technology Law Journal, Vol. 17 (2018).
• Adam Thierer & Trace Mitchell, “No New Tech Bureaucracy,” Real Clear Policy, September 10, 2020.
• Adam Thierer, “OMB’s AI Guidance Embodies Wise Tech Governance,” Mercatus Center Public Comment, March 13, 2020.
• Adam Thierer, “Europe’s New AI Industrial Policy,” Medium, February 20, 2020.
• Adam Thierer, “Trump’s AI Framework & the Future of Emerging Tech Governance,” Medium, January 8, 2020.
• Adam Thierer, “Soft Law: The Reconciliation of Permissionless & Responsible Innovation,” Chapter 7 in Adam Thierer, Evasive Entrepreneurs & the Future of Governance (Washington, DC: Cato Institute, 2020): 183-240.
• Andrea O’Sullivan & Adam Thierer, “Counterpoint: Regulators Should Allow the Greatest Space for AI Innovation,” Communications of the ACM, Volume 61, Issue 12, (December 2018): 33-35.
• Adam Thierer, Andrea O’Sullivan & Raymond Russell, “Artificial Intelligence and Public Policy,” Mercatus Research (2017).
• Adam Thierer, “Shouldn’t the Robots Have Eaten All the Jobs at Amazon By Now?” Technology Liberation Front, July 26, 2017.
• Adam Thierer, “Are ‘Permissionless Innovation’ and ‘Responsible Innovation’ Compatible?” Technology Liberation Front, July 12, 2017.
• Adam Thierer, “The Growing AI Technopanic,” Medium, April 27, 2017.
• Adam Thierer, “The Day the Machines Took Over,” Medium, May 11, 2017.
• Adam Thierer, “When the Trial Lawyers Come for the Robot Cars,” Slate, June 10, 2016.
• Adam Thierer, “Learning by Doing,” the Process of Innovation & the Future of Employment,” Technology Liberation Front, September 25, 2015.
• Adam Thierer, “Problems with Precautionary Principle-Minded Tech Regulation & a Federal Robotics Commission,” Medium, September 22, 2014.
• Adam Thierer, “On the Line between Technology Ethics vs. Technology Policy,” Technology Liberation Front, August 1, 2013.

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

• Adam Thierer, “Why is the US Following the EU’s Lead on Artificial Intelligence Regulation?” The Hill, July 21, 2022.
• Adam Thierer, “Algorithmic Auditing and AI Impact Assessments: The Need for Balance,” Medium, July 13, 2022.
• Adam Thierer, “What I Learned about the Power of AI at the Cleveland Clinic,” Medium, May 6, 2022.
• Adam Thierer, Governing Emerging Technology in an Age of Policy Fragmentation and Disequilibrium, American Enterprise Institute (April 2022).
• Adam Thierer, “A Global Clash of Visions: The Future of AI Policy,” The Hill, May 4, 2021.
• Adam Thierer, “A Brief History of Soft Law in ICT Sectors: Four Case Studies,” Jurimetrics, Vol. 61 (Fall 2021): 79-119.
• Adam Thierer, “U.S. Artificial Intelligence Governance in the Obama–Trump Years,” IEEE Transactions on Technology and Society, Vol, 2, Issue 4 (2021).
• Adam Thierer, “The Worst Regulation Ever Proposed,” The Bridge, September 2019.
• Ryan Hagemann, Jennifer Huddleston Skees & Adam Thierer, “Soft Law for Hard Problems: The Governance of Emerging Technologies in an Uncertain Future,” Colorado Technology Law Journal, Vol. 17 (2018).
• Adam Thierer & Trace Mitchell, “No New Tech Bureaucracy,” Real Clear Policy, September 10, 2020.
• Adam Thierer, “OMB’s AI Guidance Embodies Wise Tech Governance,” Mercatus Center Public Comment, March 13, 2020.
• Adam Thierer, “Europe’s New AI Industrial Policy,” Medium, February 20, 2020.
• Adam Thierer, “Trump’s AI Framework & the Future of Emerging Tech Governance,” Medium, January 8, 2020.
• Adam Thierer, “Soft Law: The Reconciliation of Permissionless & Responsible Innovation,” Chapter 7 in Adam Thierer, Evasive Entrepreneurs & the Future of Governance (Washington, DC: Cato Institute, 2020): 183-240.
• Andrea O’Sullivan & Adam Thierer, “Counterpoint: Regulators Should Allow the Greatest Space for AI Innovation,” Communications of the ACM, Volume 61, Issue 12, (December 2018): 33-35.
• Adam Thierer, Andrea O’Sullivan & Raymond Russell, “Artificial Intelligence and Public Policy,” Mercatus Research, Mercatus Center at George Mason University, Arlington, VA, (2017).
• Adam Thierer, “Are ‘Permissionless Innovation’ and ‘Responsible Innovation’ Compatible?” Technology Liberation Front, July 12, 2017.
• Adam Thierer, “The Growing AI Technopanic,” Medium, April 27, 2017.
• Adam Thierer, “The Day the Machines Took Over,” Medium, May 11, 2017.
• Adam Thierer, “When the Trial Lawyers Come for the Robot Cars,” Slate, June 10, 2016.
• Adam Thierer, “Problems with Precautionary Principle-Minded Tech Regulation & a Federal Robotics Commission,” Medium, September 22, 2014.
• Adam Thierer, “On the Line between Technology Ethics vs. Technology Policy,” Technology Liberation Front, August 1, 2013.

On Thursday, June 9, it was my great pleasure to return to my first work office at the Adam Smith Institute in London and give a talk on the future of innovation policy and the governance of artificial intelligence. James Lawson, who is affiliated with the ASI and wrote a wonderful 2020 study on AI policy, introduced me and also offered some remarks. Among the issues discussed:

• What sort of governance vision should govern the future of innovation generally and AI in particular: the “precautionary principle” or “permissionless innovation”?
• Which AI sectors are witnessing the most exciting forms of innovation currently?
• What are the fundamental policy fault lines in the AI policy debates today?
• Will fears about disruption and automation lead to a new Luddite movement?
• How can “soft law” and decentralized governance mechanism help us solve pressing policy concerns surrounding AI?
• How did automation affect traditional jobs and sectors?
• Will the European Union’s AI Act become a global model for regulation and will it have a “Brussels Effect” in terms of forcing innovators across the world to come into compliance with EU regulatory mandates?
• How will global innovation arbitrage affect the efforts by governments in Europe and elsewhere to regulate AI innovation?
• Can the common law help address AI risk? How is the UK common law system superior to the US legal system?
• What do we mean by “existential risk” as it pertains to artificial intelligence?

I have a massive study in the works addressing all these issues. In the meantime, you can watch the video of my London talk here. And thanks again to my friends at the Adam Smith Institute for hosting!

Additional Reading:

• Adam Thierer, “The Proper Governance Default for AI,” Medium, May 26, 2022, https://medium.com/@AdamThierer/the-proper-governance-default-for-ai-d05db6970924.
• Adam Thierer, “What I Learned about the Power of AI at the Cleveland Clinic,” Medium, May 6, 2022, https://medium.com/@AdamThierer/what-i-learned-about-the-power-of-ai-at-the-cleveland-clinic-e5b7768d057d.
• 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
• Adam Thierer, “A Global Clash of Visions: The Future of AI Policy,” The Hill, May 4, 2021, https://thehill.com/opinion/technology/551562-a-global-clash-of-visions-the-future-of-ai-policy.
• Adam Thierer, “S. Artificial Intelligence Governance in the Obama–Trump Years,” IEEE Transactions on Technology and Society, Vol, 2, Issue 4, (2021), https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4013880.
• Ryan Hagemann, Jennifer Huddleston Skees & Adam Thierer, “Soft Law for Hard Problems: The Governance of Emerging Technologies in an Uncertain Future,” Colorado Technology Law Journal, Vol. 17 (2018), https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3118539.
• Adam Thierer, “OMB’s AI Guidance Embodies Wise Tech Governance,” Mercatus Center Public Comment, March 13, 2020, https://www.mercatus.org/publications/technology-and-innovation/ombs-ai-guidance-embodies-wise-tech-governance.
• Adam Thierer, “Europe’s New AI Industrial Policy,” Medium, February 20, 2020, https://medium.com/@AdamThierer/europes-new-ai-industrial-policy-c5d945c5579f.
• Adam Thierer, “Trump’s AI Framework & the Future of Emerging Tech Governance,” Medium, January 8, 2020, https://medium.com/@AdamThierer/trumps-ai-framework-the-future-of-emerging-tech-governance-e504943e07d4.
• Adam Thierer, “Soft Law: The Reconciliation of Permissionless & Responsible Innovation,” Chapter 7 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.
• Andrea O’Sullivan & Adam Thierer, “Counterpoint: Regulators Should Allow the Greatest Space for AI Innovation,” Communications of the ACM, Volume 61, Issue 12, (December 2018): 33-35, https://doi.org/10.1145/3241035.
• Adam Thierer, Andrea O’Sullivan & Raymond Russell, “Artificial Intelligence and Public Policy,” Mercatus Research, Mercatus Center at George Mason University, Arlington, VA, (2017), https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3021135.
• 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.
• Adam Thierer, “The Growing AI Technopanic,” Medium, April 27, 2017, https://aboveintelligent.com/the-growing-ai-technopanic-5d6658b00fed.
• Adam Thierer, “The Day the Machines Took Over,” Medium, May 11, 2017, https://medium.com/@AdamThierer/the-day-the-machines-took-over-51076ba8e4f4.
• Adam Thierer, “When the Trial Lawyers Come for the Robot Cars,” Slate, June 10, 2016, https://slate.com/technology/2016/06/if-a-driverless-car-crashes-who-is-liable.html.
• Adam Thierer, “Problems with Precautionary Principle-Minded Tech Regulation & a Federal Robotics Commission,” Medium, September 22, 2014, https://medium.com/tech-liberation/problems-with-precautionary-principle-minded-tech-regulation-a-federal-robotics-commission-c71f6f20d8bd.
• Adam Thierer, “On the Line between Technology Ethics vs. Technology Policy,” Technology Liberation Front, August 1, 2013, https://techliberation.com/2013/08/01/on-the-line-between-technology-ethics-vs-technology-policy.

It is my honor to have the lead paper in this new series. My 19-page essay is entitled, Governing Emerging Technology in an Age of Policy Fragmentation and Disequilibrium, and it represents my effort to concisely tie together all my writing over the past 30 years on governance trends for the Internet and related technologies. The key takeaways from my essay are:

• Traditional governance mechanisms are being strained by modern technological and political realities. Newer technologies, especially digital ones, are developing at an ever-faster rate and building on top of each other, blurring lines between sectors.
• Congress has failed to keep up with the quickening pace of technological change. It also continues to delegate most of its constitutional authority to agencies to deal with most policy concerns. But agencies are overwhelmed too. This situation is unlikely to change, creating a governance gap.
• Decentralized governance techniques are filling the gap. Soft law—informal, iterative, experimental, and collaborative solutions—represents the new normal for technological governance. This is particularly true for information sectors, including social media platforms, for which the First Amendment acts as a major constraint on formal regulation anyway.
• No one-size-fits-all tool can address the many governance issues related to fast-paced science and technology developments; therefore, decentralized governance mechanisms may be better suited to address newer policy concerns.

My arguments will frustrate many people of varying political dispositions because I adopt a highly pragmatic approach to technological governance. No matter what your preferred ideal state of affairs looks like in terms of technological governance, you’re bound to be disappointed by the way high-tech policy is unfolding today. Many people desire bright-letter hard law that has government(s) establishing comprehensive, precautionary regulation of various tech sectors. Others prefer a clearly defined but more light-touch policy regime for emerging technology. Alas, neither of these preferred hard law dispositions describe the world we live in today, nor will either of them likely govern the future. My essay outlines a variety of reasons why such hard law approaches are breaking down today, including general legislative dysfunctionalism, the endless delegation of power from Congress to regulatory agencies or the states, and the the intensifying “pacing problem” (i.e., the fact that technological change is happening at a must faster rate than policy change).

In light of this, I argue:

it is smart to think practically about alternative governance frameworks when traditional hard-law approaches prove slow or ineffective in addressing governance needs. It is also wise to consider alternative governance frameworks that might address the occasional downsides of disruptive technologies without completely foreclosing ongoing innovation opportunities the way many hard-law solutions would.

I also show that, whether anyone cares to admit it or not, we already live in a world of multiplying “soft law” mechanisms and decentralized governance approaches. I use the example of how these new governance trends are unfolding for autonomous vehicles, but note how we see decentralized governance approaches being utilized in many other sectors. This is equally true across the Atlantic where the United Kingdom is increasingly experimenting with new governance approached for emerging technologies.

What counts as “soft law” or “decentralized governance” is an open-ended and ever-changing topic of discussion. But I note that it, at a minimum, it includes: multi-stakeholder processes, experimental “sandboxes,” industry best practices or codes of conduct, technical standards, private certifications, agency workshops and guidance documents, informal negotiations, and education and awareness building efforts. I unpack these ideas in the essay in more detail.

For social media, soft law approaches are the current governance norm, even as hard law regulatory proposals continue to multiply rapidly. But I note that despite all that pressure for more formal regulatory governance of social media platforms, the First Amendment presents a formidable barrier to most of those proposals. Thus, soft law will continue to be the dominant governance approach here. I also conclude by predicting that that soft law will become the dominant approach for artificial intelligence, too, even as regulatory proposals multiply there as well.

I’ll have more to say about my paper and other papers in the AEI series in coming weeks and month. For now, I encourage you to jump over to the website AEI has set up for the series and take a look at my new paper.

Additional Reading :

• Ryan Hagemann, Jennifer Huddleston Skees, and Adam Thierer, “Soft Law for Hard Problems: The Governance of Emerging Technologies in an Uncertain Future,” Colorado Technology Law Journal 17 (2018): 37–130, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3118539.
• Adam Thierer, “Soft Law in U.S. ICT Sectors: Four Case Studies,” Jurimetrics 61, no. 1 (Fall 2020): 79–119, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3777490.
• Adam Thierer, “Congress as a Non-Actor in Tech Policy,” Medium, February 4, 2020, https://medium.com/@AdamThierer/congress-as-a-non-actor-in-tech-policy-5f3153313e11.
• Adam Thierer, “The Pacing Problem and the Future of Technology Regulation,” Bridge, August 8, 2018, https://www.mercatus.org/bridge/commentary/pacing-problem-and-future-technology-regulation.
• Adam Thierer, “Artificial Intelligence Governance in the Obama–Trump Years,” IEEE Transactions on Technology and Society, Vol, 2, Issue 4, (2021), https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4013880.
• Adam Thierer, “Left and Right Take Aim at Big Tech—and the First Amendment,” Hill, December 8, 2021, https://thehill.com/opinion/technology/584874-left-and-right-take-aim-at-big-tech-and-the-first-amendment.
• Adam Thierer, “The Classical Liberal Approach to Digital Media Free Speech Issues,” Technology Liberation Front, December 8, 2021, https://techliberation.com/2021/12/08/the-classical-liberal-approach-to-digital-media-free-speech-issues.
• Adam Thierer, “The Great Deplatforming of 2021,” Discourse, January 14, 2021, https://www.discoursemagazine.com/politics/2021/01/14/the-great-deplatforming-of-2021.

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.

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.

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

• Marc Andreessen, “The Techno-Optimist Manifesto,” a16z.com, October 16, 2023.
• Will Rinehart, “The Abundance Agenda,” The Exformation Newsletter, October 15, 2022.
• Sarah Constantin, “Unblocking Abundance: A Model for Activism,” Rough Diamonds, October 10, 2022.
• Derek Thompson, “The Forgotten Stage of Human Progress,” The Atlantic, May 11, 2022.
• Adam Thierer, “Where is ‘Progress Studies’ Going?” Progress Forum, April 23, 2022.
• Katherine Boyle, “The Case for American Seriousness,” Common Sense, April 18, 2022.
• William Rinehart, “Vetocracy, the Costs of Vetos and Inaction,” Center for Growth & Opportunity at Utah State University, March 24, 2022.
• James Pethokoukis, “Forget about Left Wing and Right Wing. How about an Up Wing America?” Faster Please, March 23, 2022.
• John W. Lettieri & Kenan Fikri, “The Case for Economic Dynamism and Why it Matters for the American Worker,” Economic Innovation Group, March 2022.
• Adam Kovacevich, “Saying YIMBY (Yes In My Back Yard) to “Civic Innovation,” Chamber of Progress, March 21, 2022.
• Eli Dourado, “Remove Barriers to Productivity,” City Journal, March 18, 2022.
• “A Case for Innovation and Optimism,” (A conversation with Jason Crawford), Discourse, March 2, 2022.
• Noah Smith, “A New Industrialist Roundup,” Noahpinion, February 3, 2022.
• James Pethokoukis, “When Will the Next Big Thing Arrive?” Faster Please, February 3, 2022.
• Alec Stapp & Caleb Watney,  “ Progress is a Policy Choice ,” Institute for Progress, January 20, 2022.
• Adam Thierer, “ How to Get the Future We Were Promised ,” Discourse, January 18, 2022.
• Katherine Boyle, “ Building American Dynamism ,” Future, January 14, 2022.  
• Derek Thompson, “ A Simple Plan to Solve All of America’s Problems ,” The Atlantic, January 12, 2022.
• Jason Crawford, “Progress, Humanism, Agency: An Intellectual Core for the Progress Movement,” Roots of Progress, January 11, 2022.
• Adam Thierer, “Defending Innovation Against Attacks from All Sides,” Discourse, November 9, 2021.
• Matthew Yglesias, “The Case for More Energy,” October 7, 2021.
• Jason Crawford, “ We need a new philosophy of progress ,” The Roots of Progress, August 23, 2021.
• Gale Pooley & Marian L. Tupy, “The Simon Abundance Index 2021,” Human Progress, April 22, 2021.
• Noah Smith, “ Techno-optimism for the 2020s ,” December 3, 2020. 
• Ezra Klein, “ Why We Can’t Build ,” Vox, April 22, 2020.
• Marc Andreesen, “ It’s Time to Build ,” Future, April 18, 2020.
• Eli Dourado, “ How do we move the needle on progress ?” September 26, 2019.
• José Luis Ricón, “ About the ‘Progress’ in Progress Studies ” September 6, 2019.
• Will Rinehart, “ Progress Studies: Some Initial Thoughts ,” August 30, 2019.
• Adam Thierer, “ Is There a Science of Progress ?” AIER, August 8, 2019.
• Patrick Collison and Tyler Cowen, “ We Need a New Science of Progress ,” The Atlantic, July 30, 2019.
• Tyler Cowen, “ The Case for the Longer Term ,” Cato Unbound, January 9, 2019.
• Vinod Khosla, “ We Need Large Innovations ,” Medium, January 1, 2018.
• Adam Thierer, “ How Technology Expands the Horizons of Our Humanity ,” Medium, November 19, 2018. 
• Chelsea Follett, “Utopianism: One of the Biggest Obstacles to Progress,” Human Progress, August15, 2018.
• Eli Dourado, “ How Technological Innovation Can Massively Reduce the Cost of Living ,” PlainText, January 29, 2016.

Books

• J. Storrs Hall, Where Is My Flying Car ? (Stripe Press, 2021).
• Matt Ridley, How Innovation Works: And Why It Flourishes in Freedom (New York: Harper, 2020).
• Andrew McAfee, More from Less (New York: Simon & Schuster, 2020).
• Ronald Bailey & Marian L. Tupy, Ten Global Trends Every Smart Person Should Know: And Many Others You Will Find Interesting (Cato Institute, 2020).
• Arthur M. Diamond Jr., Openness to Creative Destruction: Sustaining Innovative Dynamism (Oxford: Oxford University Press, 2019).
• Tyler Cowen, Stubborn Attachments: A Vision for a Society of Free, Prosperous, and Responsible Individuals (San Francisco, CA: Stripe Press, 2018).
• Steven Pinker, Enlightenment Now: The Case for Reason, Science, Humanism, and Progress (New York: Viking, 2018).
• Hans Rosling, Factfulness: Ten Reasons We’re Wrong about the World—and Why Things Are Better Than You Think (New York: Flatiron Books, 2018).
• Tim Harford, 50 Things That Made the Modern Economy (New York: Riverhead Books, 2017).
• Joel Mokyr, A Culture of Growth: The Origins of the Modern Economy (Princeton, NJ: Princeton University Press, 2017).
• Adam Thierer, Permissionless Innovation: The Continuing Case for Comprehensive Technological Freedom , 2nd ed. (Arlington, VA: Mercatus Center at George Mason University, 2016).
• Calestous Juma, Innovation and Its Enemies: Why People Resist New Technologies (New York: Oxford University Press, 2016).
• Deirdre N. McCloskey, Bourgeois Equality: How Ideas, Not Capital or Institutions, Enriched the World (Chicago: University of Chicago Press, 2016).
• Joe Carlen, A Brief History of Entrepreneurship: The Pioneers, Profiteers, and Racketeers Who Shaped Our World (New York: Columbia University Press, 2016).
• Robert Bryce, Smaller Faster Lighter Denser Cheaper: How Innovation Keeps Proving the Catastrophists Wrong (New York: Public Affairs, 2014).
• Matt Ridley, The Rational Optimist: How Prosperity Evolves (New York: Harper Collins, 2010).
• Larry Downes, The Laws of Disruption: Harnessing the New Forces That Govern Life and Business in the Digital Age (New York: Basic Books, 2009).
• Amar Bhidé, The Venturesome Economy: How Innovation Sustains Prosperity in a More Connected World (Princeton, NJ: Princeton University Press, 2008).
• Robert Friedel, A Culture of Improvement: Technology and the Western Millennium (Cambridge, MA: The MIT Press, 2007).
• Benjamin M. Friedman, The Moral Consequences of Economic Growth , (New York: Vintage Books, 2006).
• Virginia Postrel, The Future and Its Enemies (New York: The Free Press, 1998).
• David Landes, The Wealth and Poverty of Nations: Why Some Are So Rich and Some are So Poor (New York: W.W. Norton & Co, 1998).
• Robert Nisbet, History of the Idea of Progress (New Brunswick, NJ: Transaction Publishers, 1994).
• Joel Mokyr, Lever of Riches: Technological Creativity and Economic Progress (New York: Oxford University Press, 1990).
• Nathan Rosenberg and L. E.. Birdzell, How the West Grew Rich: The Economic Transformation of the Industrial World (New York: Basic Books, 1986).
• Samuel C. Florman, The Existential Pleasures of Engineering (New York: St. Martin’s Griffin, 1976, 1994).

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.

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.

A short presentation I do for Mercatus Center graduate students every couple of years offering advice to aspiring policy scholars looking to develop their personal brand & be more effective public policy analysts.

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.

• Adam Thierer & Connor Haaland, “Does the US Need a More Targeted Industrial Policy for AI & High-Tech?” Presentation for IHS Papers Workshop: Does America Need a New Industrial Policy?, 2021.
• Adam Thierer, “Government Planning and Spending Won’t Replicate Silicon Valley,” Discourse, August 18, 2021.
• Adam Thierer, “To Promote Tech Hubs Across the Country, Governments Should Focus on Improving the General Business Environment,” Discourse, September 9, 2021.
• Adam Thierer, “‘Japan Inc.’ and Other Tales of Industrial Policy Apocalypse,” Discourse, June 28, 2021.
• Adam Thierer, “Industrial Policy as ‘Casino Economics‘,” The Hill, July 12, 2021.
• Adam Thierer & Connor Haaland, “Should the U.S. Copy China’s Industrial Policy?” Discourse, March 11, 2021.
• Connor Haaland & Adam Thierer, “Can European-Style Industrial Policies Create Tech Supremacy?” Discourse, February 11, 2021.
• Matthew D. Mitchell and Adam Thierer, “Industrial Policy is a Very Old, New Idea,” Discourse, April 6, 2021.
• Adam Thierer, “On Defining ‘Industrial Policy,’” Technology Liberation Front, September 3, 2020.
• Adam Thierer, “Skeptical Takes on Expansive Industrial Policy Efforts,” Technology Liberation Front, ongoing series.

In my latest column for The Hill, I consider that dangers of government gambling our tax dollars on risky industrial policy programs. I begin by noting:

Roll the dice at a casino enough times, and you are bound to win a few games. But knowing the odds are not in your favor, how much are you willing to risk losing by continuing to gamble? This is the same issue governments confront when they gamble taxpayer dollars on industrial policy efforts, which can best be described as targeted and directed efforts to plan for specific future industrial outputs and outcomes. Throwing enough money at risky ventures might net a few wins, but at what cost? Could those resources have been better spent? And do bureaucrats really make better bets than private investors?

I continue on to note that, while the US is embarking on a major new industrial policy push, history does not provide us with a lot of hope regarding Uncle Sam’s betting record when he starts rolling those industrial policy dice. “How much tolerance should the public have for government industrial policy gambling?” I ask. I continue on:

Generally speaking, “basic” support (broad-based funding for universities and research labs) is wiser than “applied” (targeted subsidies for specific firms or sectors). With basic R&D funding, the chances of wasting resources on risky investments can be contained, at least as compared to highly targeted investments in unproven technologies and firms.

I also argue that “The riskiest bets on new technologies and sectors are better left to private investors,” and note how, “America’s venture capital industry remains the envy of the world because it continues to power world-beating advanced technology.” Accordingly, I conclude:

While some government investments will always be necessary, policymakers engaging in casino economics means bad industrial policy bets and taxpayer money squandered on risky ventures best made by private actors. We need to keep Uncle Sam’s gambling habits in check.

Read the whole thing here. And here’s a list of more of my recent writing on industrial policy:

• Adam Thierer & Connor Haaland, “Does the US Need a More Targeted Industrial Policy for AI & High-Tech?” Presentation for IHS Papers Workshop: Does America Need a New Industrial Policy?, forthcoming, July 23, 2021.
• Adam Thierer, “‘Japan Inc.’ and Other Tales of Industrial Policy Apocalypse,” Discourse, June 28, 2021.
• Adam Thierer & Connor Haaland, “Should the U.S. Copy China’s Industrial Policy?” Discourse, March 11, 2021.
• Connor Haaland & Adam Thierer, “Can European-Style Industrial Policies Create Tech Supremacy?” Discourse, February 11, 2021.
• Matthew D. Mitchell and Adam Thierer, “Industrial Policy is a Very Old, New Idea,” Discourse, April 6, 2021.
• Adam Thierer, “On Defining ‘Industrial Policy,’” Technology Liberation Front, September 3, 2020.
• “Skeptical Takes on Expansive Industrial Policy Efforts,” Technology Liberation Front, ongoing series.

Discourse magazine has just published my latest essay, “‘Japan Inc.’ and Other Tales of Industrial Policy Apocalypse.” It is a short history of the hysteria surrounding the growth of Japan in the 1980s and early 1990s and its various industrial policy efforts. I begin by noting that, “American pundits and policymakers are today raising a litany of complaints about Chinese industrial policies, trade practices, industrial espionage and military expansion. Some of these concerns have merit. In each case, however, it is easy to find identical fears that were raised about Japan a generation ago.” I then walk through many of the leading books, opeds, movies, and other things from that past era to show how that was the case.

“Hysteria” is not too strong a word to use in this case. Many pundits and politicians were panicking about the rise of Japan economically and more specifically about the way Japan’s Ministry of International Trade and Industry (MITI) was formulating industrial policy schemes for industrial sectors in which they hoped to make advances. This resulted in veritable “MITI mania” here in America. “U.S. officials and market analysts came to view MITI with a combination of reverence and revulsion, believing that it had concocted an industrial policy cocktail that was fueling Japan’s success at the expense of American companies and interests,” I note. Countless books and essays were being published with breathless titles and predictions. I go through dozens of them in my essay. Meanwhile, the debate in policy circles and Capitol Hill even took on an ugly racial tinge, with some lawmakers calling the the Japanese “leeches.” and suggesting the U.S. should have dropped more atomic bombs on Japan during World War II. At one point, several members of Congress gathered on the lawn of the U.S. Capitol in 1987 to smash Japanese electronics with sledgehammers.

All this hysteria about Japan and MITI bore little semblance to reality. In fact, as I note in the essay, the MITI industrial planning model fell apart after it made a host of horrible bad bets and the stock market tanked in the late 1980s. Corruption also became a huge problem within many state-led efforts. A 2000 report by the Policy Research Institute within Japan’s Ministry of Finance concluded that “the Japanese model was not the source of Japanese competitiveness but the cause of our failure.” MITI was renamed the Ministry of Economy, Trade and Industry at about the same time, and its mission shifted more toward market-oriented reforms.

Industrial policy came to be viewed as a bit of a joke in America after that, but now it is back with a vengeance, thanks largely to the rise of Chinese economic power. Thus, because “we hear echoes from the Japan Inc. era debates in today’s policy discussions about China and industrial policy planning,” I end my essay with some lessons from the ‘Japan Inc.’ era for today’s industrial policy debates:

This similarity demonstrates the first lesson we can learn from the previous era: It is important to separate serious geopolitical and economic analysis from breathless fear-mongering and borderline xenophobia. The former has a serious place in policy discussions; the latter needs to be called out and shunned. After all, there are many legitimate worries about rising Chinese power, particularly when it involves Chinese Communist Party efforts to squash human rights domestically or to engage in industrial espionage, trade mercantilism and military adventurism abroad. Separating serious matters from trivial or imaginary ones is crucial, especially to help keep peace between nations. Avoiding hysteria is especially pertinent today with a wave of anti-Asian sentiment and attacks on the rise in the U.S. A second lesson from the Japan Inc. experience relates to today’s renewed interest in industrial policy: Forecasting the future of nations and economies—and trying to plan for it—is a tricky business. A huge range of variables affects global competitiveness and technological advancement. A nonexhaustive list of some of the most important factors would include legal and political stability, physical and intellectual property rights, tax burdens, competition policy, trade and investment laws, monetary policy, research and development efforts, and even demographic factors and access to certain natural resources. Understanding how these and other factors all work together is an inexact science. When targeted industrial policy mechanisms are added to the mix, it becomes even harder to untangle which variables are making the most difference. Both in the past and today, a less visible group of scholars has suggested that an embrace of entrepreneurialism and free trade was the fundamental factor driving Japanese economic expansion in the past and China’s amazing growth today. Openness to markets, they say, drove the enormous economic expansions—which also happened during times of much-needed catch-up modernization in both countries. But these perspectives have usually been shouted out of the room by louder voices, who either bombastically blast or praise industrial policy mechanisms as the prime mover in the economic rejuvenation of both nations. We need to tamp down on the magical thinking that governments can easily achieve technological innovation and economic growth by simply spinning a few industrial policy gauges. A few big bets may pay off, but that doesn’t justify governments engaging in casino economics regularly. History more often shows that grandiose industrial policy schemes simply result in cost overruns, cronyism and even corruption.

I also conclude by noting that:

Perhaps the most ironic indictment of industrial policy punditry lies in the way all the earlier books and essays about Japanese planning not only failed to forecast the many flops associated with it, but also did not foresee China as a potential future economic juggernaut. Korea, Singapore and Taiwan were mentioned as potential Asian challengers, but no one gave China much consideration. What might that tell us about the ability of experts to predict the future course of countries and economies? It is a reminder of the wisdom of another great Yogi Berra quote: “It’s tough to make predictions, especially about the future.”

You can read the entire piece, as well as several others listed below, over at Discourse.

• Adam Thierer & Connor Haaland, “Does the US Need a More Targeted Industrial Policy for AI & High-Tech?” Presentation for IHS Papers Workshop: Does America Need a New Industrial Policy?, forthcoming, July 23, 2021.
• Adam Thierer, “‘Japan Inc.’ and Other Tales of Industrial Policy Apocalypse,” Discourse, June 28, 2021.
• Adam Thierer & Connor Haaland, “Should the U.S. Copy China’s Industrial Policy?” Discourse, March 11, 2021.
• Connor Haaland & Adam Thierer, “Can European-Style Industrial Policies Create Tech Supremacy?” Discourse, February 11, 2021.
• Matthew D. Mitchell and Adam Thierer, “Industrial Policy is a Very Old, New Idea,” Discourse, April 6, 2021.
• Adam Thierer, “On Defining ‘Industrial Policy,'” Technology Liberation Front, September 3, 2020.
• “Skeptical Takes on Expansive Industrial Policy Efforts,” Technology Liberation Front, ongoing series.

Over at Discourse magazine I’ve posted my latest essay on how conservatives are increasingly flirting with the idea of greatly expanding regulatory control of private speech platforms via some sort of common carriage regulation or new Fairness Doctrine for the internet. It begins:

Conservatives have traditionally viewed the administrative state with suspicion and worried about their values and policy prescriptions getting a fair shake within regulatory bureaucracies. This makes their newfound embrace of common carriage regulation and media access theory (i.e., the notion that government should act to force access to private media platforms because they provide an essential public service) somewhat confusing. Recent opinions from Supreme Court Justice Clarence Thomas as well as various comments and proposals of Sen. Josh Hawley and former President Trump signal a remarkable openness to greater administrative control of private speech platforms. Given the takedown actions some large tech companies have employed recently against some conservative leaders and viewpoints, the frustration of many on the right is understandable. But why would conservatives think they are going to get a better shake from state-regulated monopolists than they would from today’s constellation of players or, more importantly, from a future market with other players and platforms?

I continue on to explain why conservatives should be skeptical of the administrative state being their friend when it comes to the control of free speech. I end by reminding conservatives what President Ronald Reagan said in his 1987 veto of legislation to reestablish the Fairness Doctrine: “History has shown that the dangers of an overly timid or biased press cannot be averted through bureaucratic regulation, but only through the freedom and competition that the First Amendment sought to guarantee.”

Read more at Discourse, and down below you will find several other recent essays I’ve written on the topic.

• “FCC’s O’Rielly on First Amendment & Fairness Doctrine Dangers“
• “A Good Time to Re-Read Reagan’s Fairness Doctrine Veto“
• “Sen. Hawley’s Radical, Paternalistic Plan to Remake the Internet“
• “How Conservatives Came to Favor the Fairness Doctrine & Net Neutrality“
• “Sen. Hawley’s Moral Panic Over Social Media“
• “The White House Social Media Summit and the Return of ‘Regulation by Raised Eyebrow’“
• “The Not-So-SMART Act“
• “The Surprising Ideological Origins of Trump’s Communications Collectivism“

Industrial Policy is a red-hot topic once again with many policymakers and pundits of different ideological leanings lining up to support ambitious new state planning for various sectors — especially 5G, artificial intelligence, and semiconductors. A remarkably bipartisan array of people and organizations are advocating for government to flex its muscle and begin directing more spending and decision-making in various technological areas. They all suggest some sort of big plan is needed, and it is not uncommon for these industrial policy advocates to suggest that hundreds of billions will need to be spent in pursuit of those plans.

Others disagree, however, and I’ll be using this post to catalog some of their concerns on an ongoing basis. Some of the criticisms listed here are portions of longer essays, many of which highlight other types of steps that governments can take to spur innovative activities. Industrial policy is an amorphous term with many definitions of a broad spectrum of possible proposals. Almost everyone believes in  some form of industrial policy if you define the term broadly enough. But, as I argued in a September 2020 essay “On Defining ‘Industrial Policy‘,” I believe it is important to narrow the focus of the term such that we can continue to use the term in a rational way. Toward that end, I believe a proper understanding of industrial policy refers to targeted and directed efforts to plan for specific future industrial outputs and outcomes.

The collection of essays below is merely an attempt to highlight some of the general concerns about the most ambitious calls for expansive industrial policy, many of which harken back to debates I was covering in the late 1980s and early 1990s, when I first started a career in policy analysis. During that time, Japan and South Korea were the primary countries of concern cited by industrial policy advocates. Today, it is China’s growing economic standing that is fueling calls for ambitious state-led targeted investments in “strategic” sectors and technologies. To a lesser extent, grandiose European industrial policy proposals are also prompting new US counter-proposals.

All this activity is what has given rise to many of the critiques listed below. If you have suggestions for other essays I might add to this list, please feel free to pass them along. FYI: There’s no particular order here.

Scott Lincicome and Huan Zhu, “Questioning Industrial Policy: Why Government Manufacturing Plans Are Ineffective and Unnecessary,” Cato Institute Working Paper, June 16, 2021.

[I]ndustrial policy – properly defined – has an extensive and underwhelming history in the United States, featuring high costs (seen and unseen), failed objectives, and political manipulation. Surely, not every U.S. industrial policy effort has ended in disaster, but facts here and abroad argue strongly against new government efforts to boost “critical” industries and workers and thereby fix alleged market failures. Such efforts warrant intense skepticism – skepticism that today is unfortunately in short supply.

Adam Thierer, “Industrial Policy as Casino Economics,” The Hill, July 12, 2021.

While some government investments will always be necessary, policymakers engaging in casino economics means bad industrial policy bets and taxpayer money squandered on risky ventures best made by private actors. We need to keep Uncle Sam’s gambling habits in check.

Adam Thierer, “Thoughts on the America COMPETES Act: The Most Corporatist & Wasteful Industrial Policy Ever,” Technology Liberation Front, January 26, 2022.

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.

Adam Thierer & Connor Haaland, “Does the US Need a More Targeted Industrial Policy for AI & High-Tech?” Mercatus Center at George Mason University, Special Study, November 2021.

This paper considers how both the recent history of high-tech industrial policy efforts at the national and international level—as well as some state and local economic development efforts in the United States—might better inform the wisdom of proposed efforts for AI or other high-tech sectors. That history is spotted with some limited successes alongside a long string of costly failures. We explore the reasons for those failures and recommend that the US refocus on the policy prerequisites that helped give rise to the computing and internet revolutions: a more generalized approach to economic development rooted in light-touch regulation and taxation of emerging technology.

Samuel Gregg, “Can America Build A Broad-Based Economy?”  Law & Liberty, March 1, 2022

Of course, if a government decides to put enough money and resources behind a given industrial policy, it will likely produce some results. Yet the same is true of the gambler. If she stays in the casino long enough and spends enough money, she will win a few hands of cards. But the odds are that she will also lose a great deal of money, especially if she is as inept a gambler as the government is maladroit at identifying industry trends or entrepreneurial opportunities. Moreover, just as a compulsive gambler’s behavior will have numerous negative effects on her family’s well-being, so too does industrial policy risk inflicting wider damage upon a nation’s economy and political system. The harms range from gross misallocations of resources to the rampant cronyism and rent-seeking that seems inseparable from industrial policy (which, I again note, its advocates studiously avoid discussing), to name just a few.

Phil Gramm & Mike Solon, “Peace Through Strength Requires Economic Freedom,” Wall Street Journal, March 1, 2022.

The America Competes Act is the House’s effort to outdo the Chinese Communist Party’s latest five-year plan. The 2,900-page bill would make an old Soviet commissar blush.  [. . . ] America’s success in the world economy has never depended on industrial policy or government subsidies. It has come from the relative absence of government planning and subsidies. This is hardly news. The U.S. government provided support for the efforts of Samuel Langley, the greatest aviation expert of the 1890s, in his effort to make America first in powered flight. His manned Aerodrome flopped into the Potomac River. It was the Wright brothers, two unsubsidized but determined bicycle makers from Dayton, Ohio, who flew at Kitty Hawk, N.C., and changed the world.

Scott Lincicome, “Moving Fast and Breaking Things,” Capitolism, February 2, 2022.

Adam Thierer, “The Coming Industrial Policy Hangover,”  The Hill, February 16, 2022.

Podcast: “What’s Wrong with Industrial Policy,” Hold These Truths with Rep. Dan Crenshaw, February 16, 2022.

Tad DeHaven and Adam Thierer, “ The Military-Industrial Complex Offers a Cautionary Tale for Industrial Policy Planning,” Discourse, March 25, 2022.

Wayne Crews, “What To Do Instead Of The America COMPETES Act,” Forbes, February 2, 2022.

All this spending and expansion of the federal government, atop which our leaders would lay the America COMPETES Act and doubtless its own accompanying guidebook, has massive, ignored regulatory effects. Trillions in government spending (”investment”) have altered and will alter the entire trajectory and competitive environment of industries engaged in large-scale enterprises and transactions. This removes vast swaths of business activity from free competitive enterprise altogether, and creates displacements and distortions such that the restoration of free enterprise becomes a near-impossible disentanglement. The result is, after 100 years of big government and seduction of and fusion with big business, the greatest endeavors—from infrastructure to artificial intelligence, from smart cities to space—now consist of “partnerships” with governments rather than free enterprise, at scales and at costs so gigantic they can only be ignored.

Adam Thierer, “‘Japan Inc.’ and Other Tales of Industrial Policy Apocalypse,” Discourse, June 28, 2021.

Perhaps the most ironic indictment of industrial policy punditry lies in the way all the earlier books and essays about Japanese planning not only failed to forecast the many flops associated with it, but also did not foresee China as a potential future economic juggernaut. [. . .] What might that tell us about the ability of experts to predict the future course of countries and economies?

Adam Thierer, “Can Government Reproduce Silicon Valley Everywhere?”  Technology Liberation Front, September 12, 2021.

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.

Weifeng Zhong, “Beijing Can’t Make Sense of Biden’s China Strategy. Can Biden?” Washington Examiner, July 01, 2021.

America is not China, and it would be a fatal mistake to equate competing with China with imitating what China does. Doing so would risk the advantageous U.S. position as the world’s chief innovator, whose ideas are turned into products by vibrant private sectors both domestically and internationally.

Mike Watson, “Industrial Policy in the Real World,” National Affairs, Summer 2021.

Given the nature of industrial policymaking in the United States, there’s little reason to believe future attempts at industrial planning will result in a more coherent, rational, or strategic allocation of resources than they have in the past. [. . .] In short, industrial policy in the United States cannot be steered by a small group of enlightened individuals, because a small group of enlightened individuals will never be at the helm. Indeed, in some sense, there is no single “helm” to speak of.

Samuel Gregg, “Industrial Policy Mythology Confronts Economic Reality,” Law & Liberty, September 3, 2021.

If prizes in policy debates were given out for persistence, those advocating for more widespread use of industrial policy in America would be first in line. No matter how many times it is pointed out that they don’t understand the nature and workings of comparative advantage; or avoid acknowledging how industrial policy fosters rampant cronyism and corruption; or highlight what they consider examples of countries in which industrial policy has been employed successfully (only to have it demonstrated that it didn’t quite work out the way they suggested), they don’t give up.

Elizabeth Nolan Brown, “If This Is How America COMPETES, We’re Going to Lose,” Reason, January 26, 2022.

the bill can’t simply address one main issue or a few critical needs. Instead, it tries to insert the government into every aspect of all sorts of industries and markets and pretend that bureaucrats can solve complex social and cultural issues.

Chang-Tai Hsieh, “Countering Chinese Industrial Policy Is Counterproductive,” Project Syndicate, September 15, 2021.

US political leaders have long tried to counter Chinese industrial policy. And now they seem to have decided that the best way to do that is to emulate it. But their agenda betrays a profound lack of understanding of the unique challenge posed by China’s coupling of an authoritarian political regime with a dynamic market economy.

Adam Thierer, “Industrial Policy Advocates Should Learn from Don Lavoie,” Discourse, November 5, 2021.

“In light of the inherent deficiencies of central planning,” Lavoie said, “it might be argued that the U.S. should instead try to reduce current government interference with the competitive process to the absolute minimum consistent with other political goals.” It remains wise advice for today’s policymakers.

Anne O. Krueger, “America’s Muddled Industrial Policy,” CGTN, June 25, 2021.

Governments have a poor track record of identifying “winners” – be it a company or a category of technology – whereas private companies have proved better at transforming new discoveries into new products or cost savings. That is why the U.S. state traditionally has stuck to funding basic research.

Eric Boehm, “Massive Subsidies Won’t Solve the Semiconductor Supply Chain Crisis,” Reason, January 28, 2022.

Tracy C. Miller, “The Case for Limiting Government Semiconductor Subsidies,” The Hill, June 26, 2021.

Without the subsidies, firms would be more cautious about building or expanding foundries. If long-term production capacity is truly insufficient, high prices and anticipated profits give firms the right incentives to build or expand and satisfy demand at cost-covering prices.

Scott Lincicome, “The ‘Endless Frontier’ and American Industrial Policy,” Cato Institute Blog, May 26, 2021.

U.S. industrial policy has a long history of struggling to overcome political pressures, just as public choice predicts, and the EFA is no different. None of this means that all legislating is bad, or that politicians don’t at least occasionally vote in the national interest. Instead, the public choice framework simply adds another hurdle—along with things like the “knowledge problem,” seen and unseen costs, and misaligned incentives—to designing and implementing commercial policies specifically intended to beat the admittedly messy and imperfect situation that the market generates. It’s imperative that we understand these risks before supporting policies that, while they might look good on paper, could easily morph into a counterproductive boondoggle—one we’ve seen countless times with respect to U.S. industrial policy.

Daniel W. Drezner, “Is the United States capable of industrial policy in 2021?” Washington Post, June 14, 2021.

To believe that the United States can pursue a high-caliber industrial policy, however, requires assuming a more competent state than I have seen in the past decade.

Douglas Holtz-Eakin, “The Nicest Thing I Can Write About Supply Chain Policy,” The Daily Dish, June 10, 2021.

Nevertheless, the Senate just passed a provision for $50 billion to subsidize chip fabrication – something the president had requested – and the House will doubtlessly concur. That might seem like an industry victory, but wait until it realizes that the administration will assume it gives it the right to insist on union jobs, micromanage the design of chips, and dictate the pricing and distribution of the products. Good luck with that. As the definitive volume on policy analysis (Benjamin Franklin’s Poor Richard’s Almanack) put it, “He that lieth down with dogs shall rise up with fleas.”

Lipton Matthews, “Industrial Policy—a.k.a. Central Planning—Won’t Make America Great,” Mises Wire, November 5, 2021.

Although industrial policy is in vogue, the evidence suggests that it is not necessary for long-term development. Moreover, despite the popularity of industrial policy in China, America remains the world’s economic power, and by following China, it may lose this vaunted position.

Richard Beason, “Japanese Industrial Policy: An Economic Assessment,” National Foundation for American Policy, November 2021.

There is no evidence to support the claim that Japanese industrial policy during the 1955-1990 period enhanced growth rates by sector, industries with economies of scale (greater efficiency when produced in increased amounts), productivity growth or “competitiveness.” The reality of the political process and government spending priorities makes it very difficult for such policies to be effective. Furthermore, even if political pressures had not intervened, it seems questionable to suggest that government policymakers would be better than actual market participants in determining the most efficient allocation of resources to produce the best economic outcomes.

Douglas Irwin, “ Memo to the Biden administration on how to rethink industrial policy,” Peterson Institute for International Economics, October 2020.

The challenge for policymakers is to identify such industries without succumbing to the notion that every industry is vital to some public objective. For example, the goal of “economic security” is so broadly defined and open-ended that virtually every domestic producer could claim the need for government support on that basis. The risk is that ill-conceived government programs will encourage corrupt behavior in which industries benefit themselves without contributing to national welfare.

Jim Pethokoukis, “Will Biden’s embrace of industrial policy pay off?” AEI Blog, January 15, 2021.

The history of such efforts in advanced capitalist economies gives ample reason for skepticism about the effectiveness of such top-down government planning, from Japanese economic stagnation to the now-mothballed Concorde supersonic jet to France’s failed attempt to create a thriving tech sector. The Internet might seem like the exception that negates the rule, but what turned out to be a successful partnership of government and entrepreneurs didn’t arise out of some master plan from Washington. And what do even the smartest plans look like when filtered through the dodgy quality of American governance? Maybe as an excuse for cronyism and protectionism.

Adam Thierer & Connor Haaland, “Should the U.S. Copy China’s Industrial Policy?” Discourse, March 11, 2021.

America needs to embrace its already vibrant venture capital market, the benefits of basic science and prize competitions, and a light-touch regulatory approach instead of gambling taxpayer dollars on grandiose industrial policy schemes that would likely become boondoggles.

Connor Haaland & Adam Thierer, “Can European-Style Industrial Policies Create Tech Supremacy?” Discourse, February 11, 2021.

Thus far, however, the Europeans don’t have much to show for their attempts to produce home-grown tech champions. Despite highly targeted and expensive efforts to foster a domestic tech base, the EU has instead generated a string of industrial policy failures that should serve as a cautionary tale for U.S. pundits and policymakers, who seem increasingly open to more government-steered innovation efforts.

Phil Levy & Christine McDaniel, “ Does the U.S. Need a Vigorous Industrial Policy?” Discourse, February 16, 2021.

we are certainly hearing new enthusiasm these days about industrial policy. It seems to have proponents or converts on both sides of the aisle. This either means that a new consensus has emerged, or it means that the term is being used so loosely that it has lost its original meaning. I’ll go with the latter; it now means different things to different people.

Wall Street Journal columnist Greg Ip discussing why “ The traditional skepticism toward industrial policy is well deserved.”

The traditional skepticism toward industrial policy is well deserved. Once Washington starts writing checks for semiconductors, other industries may get in line with the outcome determined more by political clout than economic merit. As in shipbuilding, the targeted companies may end up in perpetual need of federal protection and unable to compete internationally

David Ignatius, “The U.S. is quietly mobilizing its economy against China,” Washington Post, March 4, 2021.

The industrial policy the AI commission recommends could unlock talent and innovation. But if officials aren’t careful, government intervention could also afflict our best companies with the dead weight and dysfunction of our broken political system. We need government to spawn brainpower, not bureaucracy.

Veronique de Rugy, “Support for Industrial Policy is Growing,” AIER, January 18, 2020.

Looking at the federal government today tells me that the problems surrounding R&D programs in the past continue today, and will continue tomorrow, because they are simply a consequence of the normal functioning of government. It is hard to wish these problems away, even in the face of the private sector’s “imperfections.” Those arguing for more funding in R&D should proceed with caution.

This bill is proposing to give money with risk-averse restrictions to a risk-averse organization (the NSF) to be dispersed among other risk-averse organizations (Universities) into a system with increasingly risk-averse incentives. Note that I’m not saying “it’s all fubar’d lets burn it to the ground!” but I am suggesting that instead of slamming on the accelerator, we should be asking “what would a tune-up and an oil change look like instead?”

Ryan Bourne, “Do Oren Cass’s Justifications for Industrial Policy Stack Up?”  Cato Commentary, August 15, 2019.

Oren Cass asserts that markets cannot generally allocate resources efficiently by industry. Yet he provides no meaningful metrics to show this is the case, nor shows why his policies would deliver better outcomes. His two main claims about the benefits of a manufacturing sector — “stable employment” and “strong productivity growth” — are directly contradictory. A plethora of evidence suggests as countries’ get richer due to automation and technological improvements, they demand relatively more services, and so the industrial sector declines in employment terms.

Over at Discourse magazine, Connor Haaland and I have an new essay (“Can European-Style Industrial Policies Create Tech Supremacy?”) examining Europe’s effort to develop national champion in a variety of tech sectors using highly targeted industrial policy efforts. The results have not been encouraging, we find.

Thus far, however, the Europeans don’t have much to show for their attempts to produce home-grown tech champions. Despite highly targeted and expensive efforts to foster a domestic tech base, the EU has instead generated a string of industrial policy failures that should serve as a cautionary tale for U.S. pundits and policymakers, who seem increasingly open to more government-steered innovation efforts.

We examine case studies in internet access, search, GPS, video services, and the sharing economy. We then explore newly-proposed industrial policy efforts aimed at developing their domestic AI market. We note how:

no amount of centralized state planning or spending will be able to overcome Europe’s aversion to technological risk-taking and disruption. The EU’s innovation culture generally values stability—of existing laws, institutions and businesses—over disruptive technological change. […] There are no European versions of Microsoft, Google or Apple, even though Europeans obviously demand and consume the sort of products and services those U.S.-based companies provide. It’s simply not possible given the EU’s current regulatory regime.

It seems unlikely that Europe will have much better luck developing home-grown champions in AI and robotics using this same playbook. “American academics and policymakers with an affinity for industrial policy might want to consider a model other than Europe’s misguided combination of fruitless state planning and heavy-handed regulatory edicts,” we conclude.

Head over to Discourse  to read the entire essay.

After a slight delay, Jurimetrics has finally published my latest law review article, “Soft Law in U.S. ICT Sectors: Four Case Studies.” It is part of a major symposium that Arizona State University (ASU) Law School put together on “Governing Emerging Technologies Through Soft Law: Lessons For Artificial Intelligence” for the journal. I was 1 of 4 scholars invited to pen foundational essays for this symposium. Jurimetrics is a official publication of the American Bar Association’s Section of Science & Technology Law.

This report was a major undertaking that involved dozens of interviews, extensive historic research, several events and presentations, and then numerous revisions before the final product was released. The final PDF version of the journal article is attached.

Here is the abstract:

Traditional hard law tools and processes are struggling to keep up with the rapid pace of innovation in many emerging technologies sectors. As a result, policy­makers in the United States rely increasingly on less formal “soft law” governance mech­anisms to address concerns surrounding many newer technologies. This Article explores four case studies from different information technology areas where soft law mechanisms have already been utilized to address governance concerns. These four sectoral case stud­ies include domain name management, content oversight, privacy policy, and cyberse­curity matters. After considering the various soft law mechanisms used to address those issues, the Article concludes with some general thoughts about the effectiveness of those approaches and what lessons those case studies might hold for the use of soft law in other emerging technology sectors and contexts.

In his debut essay for the new Agglomerations blog, my former colleague Caleb Watney, now Director of Innovation Policy for the Progressive Policy Institute, seeks to better define a few important terms, including: technology policy, innovation policy, and industrial policy. In the end, however, he decides to basically dispense with the term “industry policy” because, when it comes to defining these terms, “it is useful to have a limiting principle and it’s unclear what the limiting principle is for industrial policy.”

Japan-loathing probably reached its apex around 1991 or ’92 with the publication of the non-fiction book, The Coming War with Japan, and then Michael Crichton’s fictional book (and then adapted movie), Rising Sun.  Japan’s new economic model was going to steamroll US innovators and allow them to dominate the global economy for decades to come. Three decades later, we know how all this played out. The US never went to war again with Japan. We just kept trading peacefully with them, thankfully. Meanwhile, the “Japan, Inc.” industrial policy model didn’t quite pan out the way they hoped (or that US pundits feared). In a 2007 report, Marcus Noland of the Peterson Institute for International Economics summarized Japan’s industrial policy results in bleak terms:

Japan faces significant challenges in encouraging innovation and entrepreneurship. Attempts to formally model past industrial policy interventions uniformly uncover little, if any, positive impact on productivity, growth, or welfare. The evidence indicates that most resource flows went to large, politically influential “backward” sectors, suggesting that political economy considerations may be central to the apparent ineffectiveness of Japanese industrial policy.

But I don’t want to get diverted into the specifics of why Japan’s industrial policy didn’t work. Rather, I just want to make the simple point that Japan definitely had an industrial policy that we can still evaluate today. We should not abandon all use of the term industrial policy because, once defined in a more focused fashion, it remains a useful concept worthy of serious academic study and deliberation.

Jump back to the mid-80s and flip through the individual contributions to this AEI book on The Politics of Industrial Policy. It features hot debates over the exact issue we’ve still trying to figure out today. Essays by Aaron Wildavsky, Thomas McCraw, and James Fallows generally argued for a broad conception of what industrial policy should include. Others such as economist Herbert Stein insisted upon a much narrower reading of the term. Into that debate stepped economic historian Ellis W. Hawley with a wonderful essay on industrial policy efforts in the pre-New Deal era. Hawley began his essay with what I still regard as the best understanding of what “industry policy” really means in practice. Here is Hawley’s definition:

By industrial policy I mean a national policy aimed at developing or retrenching selected industries to achieve national economic goals. In this usage, I follow those who distinguish such a policy, both from policies aimed at making the macroeconomic environment more conducive to industrial development in general and from the totality of microeconomic interventions aimed at particular industries. To have an industrial policy, a nation must not only be intervening at the microeconomic level but also have a planning and coordinating mechanism through which the intervention is rationally related to national goals, a general pattern of microeconomic targets is decided upon, and particular industrial programs are worked out and implemented.

I think Hawley’s conception of industrial policy gets it just right. Crucially, he clearly distinguished industrial policy from “policy” more generally. And he also specifies the requirement that “a planning and coordinating mechanism” is necessary and that targets are established.

Interoperability is a topic that has long been of interest to me. How networks, platforms, and devices work with each other–or sometimes fail to–is an important engineering, business, and policy issue. Back in 2012, I spilled out over 5,000 words on the topic when reviewing John Palfrey and Urs Gasser’s excellent book, Interop: The Promise and Perils of Highly Interconnected Systems.

I’ve always struggled with the interoperability issues, however, and often avoided them became of the sheer complexity of it all. Some interesting recent essays by sci-fi author and digital activist Cory Doctorow remind me that I need to get back on top of the issue. His latest essay is a call-to-arms in favor of what he calls “adversarial interoperability.” “[T]hat’s when you create a new product or service that plugs into the existing ones without the permission of the companies that make them,” he says. “Think of third-party printer ink, alternative app stores, or independent repair shops that use compatible parts from rival manufacturers to fix your car or your phone or your tractor.”

Doctorow is a vociferous defender of expanded digital access rights of many flavors and his latest essays on interoperability expand upon his previous advocacy for open access and a general freedom to tinker. He does much of this work with the Electronic Frontier Foundation (EFF), which shares his commitment to expanded digital access and interoperability rights in various contexts.

I’m in league with Doctorow and EFF on some of these things, but also find myself thinking they go much too far in other ways. At root, their work and advocacy raise a profound question: should there be any general right to exclude on digital platforms? Although he doesn’t always come right out and say it, Doctorow’s work often seems like an outright rejection of any sort of property rights in networks or platforms. Generally speaking, he does not want the law to recognize any right for tech platforms to exclude using digital fences of any sort.

Where to Draw the Lines?

As someone who has authored a book about the importance of permissionless innovation, I need to be able to answer questions about where these lines between open versus closed systems are drawn. Definitions and framing matter, however. I use “permissionless innovation” as a descriptor for one possible policy disposition when considering where legal and regulatory defaults should be set. Another conception of permissionless innovation is more of an engineering ideal; a general freedom to connect, tinker, modify, etc. (I speak more about these conceptions in my latest book, Evasive Entrepreneurs.) Of course, someone advocating permissionless innovation as a policy default will sometimes be confronted with the question of what the law should say when someone behaves in an “evasive” fashion in the latter conception of permissionless innovation.

Doctorow would generally answer that question by saying that law should not be rigged to favor exclusion through laws like the DMCA (and specifically the law’s anti- circumvention provisions), Computer Fraud and Abuse Act, patent law, and various other rules and laws. “[T]he current crop of Big Tech companies has secured laws, regulations, and court decisions that have dramatically restricted adversarial interoperability.”

Generally speaking, I agree. I’m not a fan of technocratic laws or regulations that seek to micro-manage interoperability and which stack the deck in favor of exclusionary conduct with steep penalties for evasion. But does that mean adversarial interoperability should be permitted in all cases? Should there exist any sort of common law presumption one way or the other when a user or competitor seeks access to an existing private platform or device?

Specifics matter here and I don’t have time to get into all the case studies that Doctorow goes through. Some are no-brainers, like the infamous Lexmark case involving refillable printer ink cartridges. Other cases are far more complicated, at least for me. Does Epic, creator of Fortnite, have a right of adversarial interoperability that it can exercise against Apple and their AppStore? As Dirk Auer suggests in a new essay, this episode looks more like a straightforward pricing dispute. Epic is making it out to be much more than that, suggesting Apple is guilty of unfair and exclusionary practices that require a legal remedy.

Why not take that logic further and just say Apple’s App Store us tantamount to a natural monopoly or digital essential facility that Epic and everyone else is entitled to on whatever terms they want? For that matter, why not apply the same logic to Epic’s Fortnite platform or even its Unreal Engine? Does every other gaming developer have a right to piggyback on the juggernaut that Epic has built?

This gets to the core question about Doctorow’s concept of adversarial interoperability: Exactly what should common law and the courts say platform owners make access rights a simple pricing matter and say: “You pay or you are out.” Like Doctorow and EFF, I don’t want Apple to benefit from any special favors from laws like DMCA. Where we differ is that I would still leave the door open for Apple to exercise various other common law contractual rights or property rights in court.

I suspect Doctorow would deny any such claims by Apple or anyone else. If so, I would like to see him spell out in more precise terms exactly what Apple’s property rights and contractual rights are in this instance. Or, again, should we just treat the App Store as a digital commons with unfettered open access rights for developers? If so, would Apple be required to still manage the resource once it is a quasi-commons?

I think that would end miserably, but would like to hear Doctorow’s preferred approach before saying more. I suspect a lot rides on the distinction between “open” verses “proprietary” standards, but compared to Doctorow and EFF, I am willing to embrace a world of both open and proprietary systems, and many hybrids in between. I don’t want the law favoring one type over the other, but that means I need to endorse a generalized property right for digital operators such that they can still exclude others (even in the absence of artificial regulatory rights like DMCA creates). Again, I suspect Doctorow would reject that standard, preferring a generalized right of access, even if that means the platforms become de facto commons.

More Radical Steps

Elsewhere, Doctorow has said is that some of these questions would be better addressed through more aggressive antitrust regulation. Mere data portability or mandatory interoperability isn’t enough for him. “Data portability is important,” Doctorow says, “but it is no substitute for the ability to have ongoing access to a service that you’re in the process of migrating away from.”

In his latest online book on “How to Destroy Surveillance Capitalism,” Doctorow suggests that it is time to “make Big Tech small again” through an “anti-monopoly ecology movement.” That “means bans on mergers between large companies, on big companies acquiring nascent competitors, and on platform companies competing directly with the companies that rely on the platforms.” And he desires a host of other remedies.

So, here we have the convergence of interoperability policy and antitrust policy, with a layer of property confiscation layered on top apparently. “Now it’s up to us to seize the means of computation, putting that electronic nervous system under democratic, accountable control,” he insists in his latest manifesto.

What’s funny about this is that Doctorow begins most of his essays by pointing out all the ways that politics is the problem when it comes to access issues, only to end by suggesting that a lot more political meddling is the required solution. He repeatedly laments how large tech players have so often been able to convince lawmakers and regulators to pass special laws or regulations that work to their favor. Yet, in his We-Can-Build-A-Better-Bureaucrat model of things, all those old problems will apparently disappear when we get the right people in power and get rid of those nefarious capitalist schemers.

Thus, what really animates Doctorow’s advocacy for adversarial interoperability is a deep suspicion of free market capitalism and property rights in particular. In this worldview, interoperability really just becomes a Trojan Horse meant to help bring down the entire capitalist order. Am I exaggerating? “As to why things are so screwed up? Capitalism.” Those are his exact words from the conclusion of his latest book.

Adversarial Innovation & Evolutionary Interop

Still, Doctorow raises many legitimate issues about interconnection and digital access rights. But we need a better approach to work though these questions than the one he suggests.

In my lengthy review of the Palfrey and Gasser Interop book, I tried to sketch out an alternative framework for thinking seriously about these issues. I referred to my preferred approach as “experimental interoperability” or “evolutionary interoperability.” I described this as the theory that ongoing marketplace experimentation with technical standards, modes of information production and dissemination, and interoperable information systems, is almost always preferable to the artificial foreclosure of this dynamic process through state action. The former allows for better learning and coping mechanisms to develop while also incentivizing the spontaneous, natural evolution of the market and market responses.

Adversarial interoperability is important, but not nearly as important as adversarial innovation and facilities-based competition. Stated differently, access rights to existing systems is an important value, but the incentives we have in place to encourage entirely new systems is what really matters most. At some point, a generalized right of access to existing systems discourages the sort of platform-building that could help give rise to the sort of creative destruction we have seen at work repeatedly in the past and that we still need today. Taken too far, adversarial interoperability threatens to undermine this goal. Why seek to build a better alternative platform if you can just endlessly free ride off someone else’s by force of law?

Thus, I prefer to work at the margins and think through how to balance these competing claims of access / interoperability rights versus contractual / property rights. My take will be too utilitarian for not only Doctorow but also for some libertarians, who want clear answers to all these questions based upon their preferred natural law-oriented constructions of rights. The problem with that approach is that it leads to all-or-nothing extremes (complete digital property rights, or virtually none) and that approach is fundamentally unworkable and destructive. We need to work harder about how to balance these rights and values in pro-competitive, pro-innovation fashion.

There is No Such Thing as Optimal Interoperability

In sum, there is no such thing as “optimal interoperablity.” Sometimes proprietary or “closed” systems will offer the public features and options that they will find preferable to “open” ones.  “There are many reasons why consumers might prefer ‘closed’ systems – even when they have to pay a premium for them,” argues Dirk Auer in a separate essay. It could be greater convenience, security, or other things. Palfrey and Gasser correctly noted in their book that, “the state is rarely in a position to call a winner among competing technologies” (p. 174). Moreover, they concluded:

“Lawmakers need to keep in view the limits of their own effectiveness when it comes to accomplishing optimal levels of interoperability. Case studies of government intervention, especially where complex information technologies are involved, show that states tend to be ill suited to determine on their own what specific technology will be the best option for the future (p. 175)

A thousand amens to that! The law should not artificially foreclose experimentation with many different types of platforms, standards, devices and the interoperability that exists among them.