design – Technology Liberation Front https://techliberation.com Keeping politicians' hands off the Net & everything else related to technology Thu, 03 Apr 2025 23:20:10 +0000 en-US hourly 1 6772528 AI Eats the World: Preparing for the Computational Revolution and the Policy Debates Ahead https://techliberation.com/2022/09/12/ai-eats-the-world-preparing-for-the-computational-revolution-and-the-policy-debates-ahead/ https://techliberation.com/2022/09/12/ai-eats-the-world-preparing-for-the-computational-revolution-and-the-policy-debates-ahead/#comments Mon, 12 Sep 2022 23:52:26 +0000 https://techliberation.com/?p=77039

[Cross-posted from Medium.]

The Coming Computational Revolution

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

Expanding Our Skillset

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

Mapping the AI Policy Terrain: Broad vs. Narrow

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

Confronting the Formidable Resistance to Change

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

]]> https://techliberation.com/2022/09/12/ai-eats-the-world-preparing-for-the-computational-revolution-and-the-policy-debates-ahead/feed/ 3 77039 Running List of My Research on AI, ML & Robotics Policy https://techliberation.com/2022/07/29/running-list-of-my-research-on-ai-ml-robotics-policy/ https://techliberation.com/2022/07/29/running-list-of-my-research-on-ai-ml-robotics-policy/#respond Fri, 29 Jul 2022 12:51:54 +0000 https://techliberation.com/?p=77020

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

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

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

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

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

2025

2024

2023

2022

2021 (and earlier)

]]> https://techliberation.com/2022/07/29/running-list-of-my-research-on-ai-ml-robotics-policy/feed/ 0 77020 The Proper Governance Default for AI https://techliberation.com/2022/05/26/the-proper-governance-default-for-ai/ https://techliberation.com/2022/05/26/the-proper-governance-default-for-ai/#comments Thu, 26 May 2022 20:15:21 +0000 https://techliberation.com/?p=76994

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Endnotes:

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

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

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

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

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

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

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

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

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

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

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

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

[13]    Ibid.

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

[15]    Thierer, Permissionless Innovation, at 2.

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

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

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

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

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

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

[22]    Ibid., 27,

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

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

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

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

[27]    Thierer, Permissionless Innovation.

[28]    Thierer, “Failing Better.”

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

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

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

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

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

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

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

[36]    Ibid.

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

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

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

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

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

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

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

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

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

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

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

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

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

[50]    Ibid., at 5.

]]> https://techliberation.com/2022/05/26/the-proper-governance-default-for-ai/feed/ 4 76994 The Internet’s philosopher-king https://techliberation.com/2012/03/15/the-internets-philosopher-king/ https://techliberation.com/2012/03/15/the-internets-philosopher-king/#respond Thu, 15 Mar 2012 15:38:31 +0000 http://techliberation.com/?p=40341

tumblr_m04g8byWGw1qdu5t4o1_500The cover story of this week’s The New Republic is a review by Evgeny Morozov of Walter Isaacson’s biography of Steve Jobs. In 10,000 words it is more illuminating about what made Steve Jobs tick than Isaacson’s 656 pages of warmed-over anecdotes and Wikipedia glosses. Morozov gets it right when he draws the connection between Bauhaus and Apple–functionalism and simplicity über alles. But he doesn’t seem to like where this takes Apple or Jobs.

He calls Jobs’s adherence to the Bauhaus ideal “a kind of industrial Platonism” in which products have a true form or essence that must be discovered and revealed by a designer. What consumers think they want is irrelevant; they will know what they want when it is presented to them. That’s true as far as it goes, but Morozov is the real Platonist here.

Morozov’s ultimate indictment of Apple is that it refuses to consider the externalities its technologies impose on “society.” One may love one’s Apple products and how they have improved one’s life, but, Morozov says,

We need to identify the other moral instructions that may be embedded in a technology, which it promotes directly or indirectly. And this fuller analysis requires going beyond studying the immediate impact on the user and engaging with the broader–let us call it the “ecological”–impact of a device. (“Ecological” here has no environmental connotations; it simply indicates that a technology may affect not only its producer and its user, but also the values and the habits of the community in which they live.)

What is this negative externality Apple’s technology is inflicting on the value and habits of our communities? It’s that apps will kill the open Internet, except not for the reasons we think. Morozov cites and dismisses Jonathan Zittrain’s “generativity” critique saying that Zittrain is concerned only with the threat to innovation. Morozov, on the other hand, is concerned with loftier “ethical and aesthetic considerations.” Namely, that Apple’s app paradigm “may be destroying the Internet in much the same way that the automobile destroyed the sidewalks and the playgrounds.”

The point is not that we should forever cling to the shape and the format of the Internet as it exists today. It is that we should (to borrow Apple’s favorite phrase) “think different” and pay attention to the aesthetic and civic externalities of the app economy. Our choice is between erecting a virtual Portland or sleepwalking into a virtual Dallas. But Apple under Steve Jobs consistently refused to recognize that there is something valuable to the Web that it may be destroying.

After reading a competing cover story about Portland in another newsweekly, I’m not sure the choice is as clear as Morozov thinks it is. But the message is clear: like Portland’s planners do about a “livable city,” Morozov has a vision of what is the Internet’s pure form, and it’s not one left to messy markets.

Morozov quotes a Newsweek interview with Jobs just a few years after the Web was invented. Jobs sees it as “the ultimate direct-to-customer distribution channel.” He essentially predicts that you’ll be able to buy books online and that the bookstore will know what you like.

That the Web did become a shopping mall fifteen years after Jobs made his remark does not mean that he got the Web right. It means only that a powerful technology company that wants to change the Web as it pleases can currently do so with little or no resistance from anyone. If one day Apple decides to remove a built-in browser from the iPad, as the Web becomes less necessary in an apped world, it will not be because things took on a life of their own, but because Apple refused to investigate what other possible directions—or forms of life—“things” might have taken. For Jobs, with his pre-political mind, there was no other way to think about the Internet than to rely on the tired binary poles of supply and demand.

The notion that Apple turned the web into what it is today singlehandedly is laughable. Apple was moribund until 2000, didn’t introduce the iTunes Store until 2003, and has never had a strong presence on the web. The web has become what it is today because the convenience of getting any book you want, whenever you want it, and cheaply beats little bookstores stocked by proprietor’s whims, however aesthetically pleasing they may be–which they’re often not. And for the record, I hope we can all agree the web is more than a shopping mall.

More to the point, though, Jobs was not as much a Pied Piper as we’d like to think he was. Depite all his marketing moxie, he was constrained by the market. If Jobs ever thought there was a true essence of a computer, it was the Power Mac G4 Cube. As Isaacson says, “it was the pure expression of Jobs’s aesthetic.” And it was a flop. “Jobs later admitted that he had overdesigned and overpriced the Cube, just as he had the NeXT computer.” Remember the NeXT cube? How about the iPod Hi-Fi? The buttonless iPod shuffle? Ping? Those tired poles of supply and demand told Jobs “no” time after time, but we might just as easily dismiss gravity or entropy as tired.

If Apple were to remove the browser from the iPad today, there would be, shall we say, less demand for the tablet. If at some future date there is no more demand for a web browser, and Apple removes it to little fanfare, then what is the harm?

I guess it is some Platonic Internet that we’d lose. A pure internet that we don’t know we want. One that only philosopher-kings can see. One they will discuss at “Berlin-based think tanks” and in the pages of “quarterly magazines,” as Morozov praises Google for sponsoring. And it’s an Internet the philosopher-kings would plan for us the same way Neil Goldschmidt and his friends planned Portland.

No thanks. I prefer a Steve Jobs, pursuing a functionalist ideal with little care for the consequences, yet checked by those tired poles and the “perennial gale of creative destruction” that will someday catch up with Apple.

]]> https://techliberation.com/2012/03/15/the-internets-philosopher-king/feed/ 0 40341 Can Design Innovation Save Newspapers? No, but… https://techliberation.com/2009/09/04/can-design-innovation-save-newspapers-no-but/ https://techliberation.com/2009/09/04/can-design-innovation-save-newspapers-no-but/#comments Fri, 04 Sep 2009 13:46:15 +0000 http://techliberation.com/?p=21032

Polish designer Jacek Utko acknowledged that, in the long-run, nothing can save the newspaper as a print medium, but makes a pretty good case newspapers’ ability to  stay afloat while figuring out how to make the transition to digital media depends heavily on shaking up the graphic design and layout of papers.

http://video.ted.com/assets/player/swf/EmbedPlayer.swf If nothing else, this should remind us all that innovation and entrepreneurship aren’t just about technical improvements or better business savvy, but aesthetics, too! The art of commercial culture is like the oxygen we breath: all around us but something we scarcely notice.

]]> https://techliberation.com/2009/09/04/can-design-innovation-save-newspapers-no-but/feed/ 4 21032 Internet Security Concerns, Online Anonymity, and Splinternets https://techliberation.com/2009/02/15/internet-security-concerns-online-anonymity-and-splinternets/ https://techliberation.com/2009/02/15/internet-security-concerns-online-anonymity-and-splinternets/#comments Sun, 15 Feb 2009 17:55:03 +0000 http://techliberation.com/?p=16703

What would it take to create a more secure Internet?  That’s what John Markoff explores in his latest New York Times article, “Do We Need a New Internet?”  Echoing some of the same fears Jonathan Zittrain articulates in his new book The Future of the Internet, Markoff wonders if online viruses and other forms of malware have gotten so out-of-control that extreme measures may be necessary to save the Net.  Compared to when cyber-security attacks first started growing over 20 years ago, Markoff argues that:

[T]hings have gotten much, much worse. Bad enough that there is a growing belief among engineers and security experts that Internet security and privacy have become so maddeningly elusive that the only way to fix the problem is to start over.

Like many others, Markoff fingers anonymity as one potential culprit:

The Internet’s current design virtually guarantees anonymity to its users. (As a New Yorker cartoon noted some years ago, “On the Internet, nobody knows that you’re a dog.”) But that anonymity is now the most vexing challenge for law enforcement. An Internet attacker can route a connection through many countries to hide his location, which may be from an account in an Internet cafe purchased with a stolen credit card. “As soon as you start dealing with the public Internet, the whole notion of trust becomes a quagmire,” said Stefan Savage, an expert on computer security at the University of California, San Diego.

Consequently, Markoff suggests that:

A more secure network is one that would almost certainly offer less anonymity and privacy. That is likely to be the great tradeoff for the designers of the next Internet. One idea, for example, would be to require the equivalent of drivers’ licenses to permit someone to connect to a public computer network. But that runs against the deeply held libertarian ethos of the Internet.

Indeed, not only does it run counter to the ethos of the Net, but as Markoff rightly notes, “Proving identity is likely to remain remarkably difficult in a world where it is trivial to take over someone’s computer from half a world away and operate it as your own. As long as that remains true, building a completely trustable system will remain virtually impossible.”  I’ve spent a lot of time writing about that fact here and won’t belabor the point other than to say that efforts to eliminate anonymity for the entire Internet would prove extraordinarily intrusive and destructive — of both the Internet’s current architecture and the rights of its users.  There’s just something about a “show-us-you-papers,” national ID card-esque system of online identification that creeps most of us out. That’s why I spend so much time fighting age verification mandates for social networking sites and other websites; it’s the first step down a very dangerous road.

But what if we could apply such solutions in a narrower sense?  That is, could we create more secure communities within the overarching Internet superstructure that might provide greater security?  Markoff starts thinking along those lines when he suggests…

What a new Internet might look like is still widely debated, but one alternative would, in effect, create a “gated community” where users would give up their anonymity and certain freedoms in return for safety.

… but he is still thinking in terms of a replacement model for the entire Internet, which would be misguided for the reasons I stated above.  We don’t want to force a single, intrusive, anonymity-killing replacement model on the entire online universe.  Starting over isn’t even possible in a practical sense.

It’s a shame that Markoff didn’t interview my old colleague Wayne Crews for his story because Wayne has outlined an alternative framework worth considering. For many years, Wayne has been preaching about “spinternets,” or the notion that we need to start thinking about how develop not just one better Internet, but many better Internets. In a visionary piece for Forbes back in early 2001, Wayne argued that the solution to the growth of various online concerns “is more Internets, not more regulations”:

The Internet needs borders beyond which users can escape damaging political resolutions of these battles, which are rooted in the Internet’s nonowned, common-property status. Conflicting legislative visions in a cyberspace populated by exhibitionists at one extreme and would-be inhabitants of gated communities on the other, reveal the basic truth that not everybody wants or needs to be connected to everybody else.

Again, there’s that notion of “gated communities” that Markoff brought up. It’s not for everybody, but those seeking greater security could perhaps find it inside such online communities. Of course, others who wanted a different experience could start a completely different gated community under Wayne’s model.

But the problem with this notion, quite obviously, is that very few people want to stay inside their gated communities all the time. In the physical world of gated communities, for example, members of it still like to get out of there once and awhile to visit shops, events, parks, friends and family, etc.  The same goes for the Internet.  Just ask all those former denizens of AOL’s gated community.  For awhile, many of them — over 25 million strong at the zenith of its popularity — were content to spend most of their digital day inside the walls of Case’s Castle.  Gradually, however, they felt the need to explore outside those walls.  And so they did.  A mass exodus ensued and the walls came crumbling down around AOL’s gated community.

But that doesn’t necessarily mean the idea of online gated communities is entirely dead. There are certainly many closed, tightly-controlled networks out there already — mostly in corporate or government environments — that offer a glimpse of how such a model might work in practice.  Also, smaller social networking sites aimed at kids provide another example since they are usually tightly-controlled walled gardens that offer much greater security.

But Wayne was always thinking of something bigger — much bigger — than just closed corporate / government networks. He was thinking about a world of many different Internet s that didn’t necessarily have a back door to the broader Internet. Think of it as many parallel, but unconnected digital systems and networks, each serving a different set of values and cultures with unique rules.

Wayne envisioned the primary critique of this model in his original piece, noting that “it will be criticized as Balkanization.”  Indeed, Sonia Arrison called it “techno-isolationism, which goes against the very spirit that makes the Internet great.”  Indeed, it certainly would destroy something very precious about the current Internet — universal connectivity and openness.  But that’s sort of the point, isn’t it!  Universal connectivity and openness have given us many wonderful things, but some troubling things, too.  That’s what Markoff was getting at in his NYT piece, and it’s part of what Wayne was aiming to address with his splinternets idea.

But do we really want to encourage a world of multiple Internets where, presumably, they are split right down to the root? In other words, there wouldn’t be a common language for networks to communicate or a way to access many sites and services outside the particular Net you are on at any given time. It would be the equivalent of living on different digital planets that never linked or communicated.

I think it’s unlikely we’ll ever get there, and if we did it would likely be driven by global governments challenging ICANN and existing Internet governance structures. In other words, the DNS root would be completely split by some countries (China?) who didn’t want to play by the same rules as the rest of the interconnected world, or who wanted to try to impose a different vision upon a new, competing global network.

But might there be a way to find a happy middle ground between the Wild West commons of the current Net and the “techno-isolationism” of Wayne’s splinternet model?  Perhaps “Splinternet-lite” is the solution.  Within the confines of the existing Internet superstructure, there are ways to create walled gardens today and limit the number of back doors to the broader Net.  Again, the smaller social networking sites and virtual worlds aimed at kids already do that. Once you’re in there, you’re in a very different world. You have to be fully verified before you’re even let in the door, and once you’re inside their are tight limits on what you say, do, and explore. And you’ll get booted out pretty quickly if you break the rules.  The result is greater safety and peace-of-mind for kids and parents alike. It’s a less clear, however, how that model would “scale up” and apply to the entire universe of online networks.  I think we’ll have to be content with small patches of security within a world of insecurity. That’s the cost of the openness and interconnectivity that the Net current gives us.

In sum, there is no clear answer to John Markoff’s question, “Do we need a new Internet?”  We certainly could do more to address the problems with the current Net, but upending it and starting over isn’t likely an option.  More micro-splinternets within the overarching Net superstructure, however, might help those who are particularly risk-conscious find safe haven from various cyber-security fears. But it won’t shelter them from those problems completely.

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