[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.

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.

I’ve always been perplexed by tech critiques that seek to pit “humanist” values against technology or technological processes, or that even suggest a bright demarcation exists between these things. Properly understood, “technology” and technological innovation are simply extensions of our humanity and represent efforts to continuously improve the human condition. In that sense, humanism and technology are compliments, not opposites.

I started thinking about this again after reading a recent article by Christopher Mims of The Wall Street Journal , which introduced me to the term “techno-chauvinism.” Techno-chauvinism is a new term that some social critics are using to identify when technologies or innovators are apparently not behaving in a “humanist” fashion. Mims attributes the term techno-chauvinism to Meredith Broussard of New York University, who defines it as “the idea that technology is always the highest and best solution, and is superior to the people-based solution .” [Italics added.] Later on Twitter, Mims defined and critiqued techno-chauvinism as “the belief that the best solution to any problem is technology, not changing our culture, habits or mindset.”

Everything Old is New Again

There are other terms critics have used to describe the same notion, including: “ techno-fundamentalism ” (Siva Vaidhyanathan), “cyber-utopianism,” and “ technological solutionism ” (Evgeny Morozov). In a sense, all these terms are really just variants of what scholars in the field of Science and Technology Studies (STS) have long referred to as “technological determinism.”

As I noted in a recent essay about determinism, the traditional “hard” variant of technological determinism refers to the notion that technology almost has a mind of its own and that it will plow forward without much resistance from society or governments. Critics argue that determinist thinking denies or ignores the importance of the human element in moving history forward, or what Broussard would refer to as “people-based solutions.”

The first problem with this thinking is there are no bright lines in these debates and many “softer” variants of determinism exist. The same problem is at work when we turn to discussions about both “humanism” and “technology.” Things get definitionally murky quite quickly, and everyone seemingly has a preferred conception of these terms to fit their own ideological dispositions. “Humanism is a rather vague and contested term with a convoluted history,” observes tech philosopher Michael Sacasas. And here’s an essay that I have updated many times over the years to catalog the dozens of different definitions of “technology” I have unearthed in my ongoing research.

Thus, when we hear “humanist” critiques of “technology,” I can’t help but think that many of them begin with an unclear explanation of what both those terms mean and how they are related. Here’s how I think about them.

“Technology” is not some magical force or shiny device that appeared out of thin air. All technology is the product of human design . The most straightforward definition of “technology” is simply the application of knowledge to a task. When critics claim that innovators or their defenders are “chauvinists” who think that technological solutions are “superior to the people-based solution,” they are creating a nonsensical dichotomy because technological solutions are the same thing as “people-based solution.” People create technologies to solve problems. We can imagine the first person who struck two stones together to make a spark and light a fire, or the first humans who fashioned knives or bows and arrows to hunt game. Were they not being “humanist” by pursuing a better way to feed themselves and others? Personally, I cannot think of anything more “humanist” than creating or using whatever tools one can to put the next meal on the table! Eventually, most tools and processes like these become so ordinary that we no longer even consider them “technology” at all. They just become part of the fabric of our lives and we come to take them for granted.

What some critics mean by “humanism” is also confusing for reasons that were nicely identified by Andrew McAfee in his 2015 Financial Times essay , “Who are the humanists, and why do they dislike technology so much?” McAfee pointed out that some “humanist” critiques of technological innovation are relatively banal to the extent they are simply reminding us that all people are important, or that all technological process involve trade-offs that we should be aware of.

Of course these things are true, McAfee noted. But it is also true that technological advancement solves far more problems than it creates by helping to reduce hunger and disease, travel further, communicate more widely, gain leisure time, and so on. Moreover, there are trade-offs associated with all human actions. Limiting ongoing innovations and improvements that could better the human condition gives rise to equally significant trade-offs. In any event, to the extent “humanism” can be reduced to UP WITH PEOPLE! and TRADE-OFFS MATTER!, I think all of us would consider ourselves to be “humanists.”

The Vision of the Anointed

But there’s a third conception of “humanism” McAfee identified that he regarded as far more problematic. I will label it the “ Vision of the Anointed ,” to borrow a phrase Thomas Sowell used in his book about the way some elites allow rhetorical flourishes and good intentions to trump actual real-world evidence and results. McAfee summarized this humanist version of the Vision of the Anointed as follows: “Because I am for the people I should be free from having to support my contentions with anything more than rhetoric.” Or, more simply: “You can trust what I say, because I am on the side of people instead of the cold, hard machines.”

That sort of vision is at work in a great deal of STS scholarship, and has been for a long, long time. Indeed, modern conceptions of “humanism” and critiques of “techno-chauvinism” or “solutionism” are just restatements of the lamentations of countless previous media critics or technology critics from the past, including Jacques Ellul, Lewis Mumford, Neil Postman, Langdon Winner, Christopher Lasch, and many others. Much criticism of this sort ends up suggesting — either directly or implicitly — that technological innovation is anti-human or “de-humanizing” in some fashion and should, therefore, be rejected, reversed, or at least slowed down considerably.

For example, in Lasch’s 1991 book, The True and Only Heaven , the social critic lambasted what he called “progressive optimism” for its supposed “denial of the natural limits on human power and freedom.” Lasch desired a “populism for the twenty-first century” that “would find much of its moral inspiration in the popular radicalism of the past and most generally in the wide-ranging critique of progress, enlightenment, and unlimited ambition.”

This gets to the real irony associated with the Humanistic Vision of the Anointed: It doesn’t place a lot of faith in humans! In this highly pessimistic and often quite elitist worldview, the masses seemingly do not understand what is in their own best interests, and the material gains of modern civilization are, at once, both a fiction to be scoffed at and a reality to be scorned as counterproductive or “anti-human.” What is the alternative arrangement for society that is set forth by those subscribing to the Vision of the Anointed? As Lasch suggests, it comes down to acceptance of limits . In closing his book, Lasch called for the return of a humanistic “state of heart and mind” that “asserts the goodness of life in the face of its limits.” In other words, we should be happy with what we’ve got because progress ain’t so great.

Pastoral Myths & the “Good ‘Ol Days”

This also explains the enduring power of “pastoral myths” in the work of such critics. If you spend enough time reading through works of technology and media criticism, you often find allusions made to some supposedly better time  — the proverbial “good ‘ol days” — when life was supposed simplier or better in some way. Other times, it is just implied that life in the present isn’t as good as it was in the past.

The problem is that those good ‘ol days weren’t so great. “Demonizing innovation is often associated with campaigns to romanticize past products and practices,” Calestous Juma noted in his 2016 book, Innovation and Its Enemies: Why People Resist New Technologies . “Opponents of innovation hark back to traditions as if traditions themselves were not inventions at some point in the past.” That was especially the case in battles over new farming methods and technologies, when opponents of change were frequently “championing a moral cause to preserve a way of life,” as Juma discusses in several chapters of his book. New products or methods of production were repeatedly but wrongly characterized as dangerous or anti-human simply because they were not supposedly “natural” or “traditional” enough in character.

Of course, if all farming and other work was to remain frozen in some past “natural” state, we’d all still be hunters and gathers struggling to find the next meal to put in our bellies. Or, if we were all still on the farms of the “good ‘ol days,” then we’d still be stuck using an ox and plow in the name of preserving the “traditional” ways of doing things.

Humanity has made amazing strides—including being able to feed more people more easily and cheaply than ever before—precisely because we broke with those old, “natural” traditions. Alas, many vested interests, and even quite a few academics, still employ these same pastoral appeals and myths to oppose new forms of technological change. The case studies in Juma’s book powerfully illustrate why that dynamic continues to be a driving force in innovation policy debates and how it delays the diffusion of many important new life-enriching goods and services.

Trial and Error

When the opponents of change rest their case on pastoral myths and nostalgic arguments about the good ‘ol days, we should remind them that those days were, in reality, eras of abject misery. Widespread poverty, mass hunger, poor hygiene, short lifespans, and so on were the norm. What lifted humanity up and improved our lot as a species is that we learned how to apply knowledge to tasks in a better way through incessant trial and error experimentation. In other words, we flourished by innovating . And the results of our innovative activities were called technologies .

In this sense, humanism and technology have gone hand in hand throughout history. Steven Pinker put it best in his new book, Enlightenment Now: The Case for Reason, Science, Humanism, and Progress : “Progress consists of deploying knowledge to allow all of humankind to flourish in the same way that each of us seeks to flourish. The goal of maximizing human flourishing–life, happiness, freedom, knowledge, love, richness of experiences–may be called humanism.”

Our technologies are simply extensions of our knowledge and represent profoundly humanist efforts to improve our lives and the lives of others around us. “We will never have a perfect world, and it would be dangerous to seek one,” Pinker notes. “But there is no limit to the betterments we can attain if we continue to apply knowledge to enhance human flourishing,” he rightly concludes.

The Right Balance

Of course, as Pinker hints, we can go too far sometimes or place too much faith in our tools. Pursuing perfection through technological betterment can end in folly, or worse. In my previous essay, “ Deep Technologies & Moonshots: Should We Dare to Dream ,” I noted that over-exuberant tech boosters are sometimes guilty of the same rhetorical excesses and inflated claims that some humanist critics practice. Some tech evangelists go too far in suggesting that technological innovation can solve all the problems of the world. Other times, they ignore or ridicule the importance of other human values, traditions, or institutions to long-term human flourishing and over-value convenience or efficiency.

When innovation advocates go overboard, they should be called out for it. But that doesn’t mean we should stop striving for a better future, and one in which technology is rightly viewed as the fundamental driver of human well-being. No matter what some critics say, technological solutions are people-based solutions. We craft tools to solve important problems and to better our lives and the lives of our loved ones. What could be more “humanist” than that?

Additional Reading :

• Adam Thierer, “ The Pacing Problem, the Collingridge Dilemma & Technological Determinism ,” Technology Liberation Front , August 16, 2018.
• Adam Thierer, “ Defining ‘Technology ’” Technology Liberation Front , originally published April 29, 2014, last updated July 2017.
• “ Evasive Entrepreneurs and Permissionless Innovation: An Interview with Adam Thierer ,” The Bridge , September 11, 2018.
• Adam Thierer, “ Deep Technologies & Moonshots: Should We Dare to Dream ?” Medium , September 7, 2018.
• Adam Thierer, “ Are “Permissionless Innovation” and “Responsible Innovation” Compatible ?” July 12, 2017.
• Adam Thierer, “ What Does It Mean to “Have a Conversation” about a New Technology ?,” Technology Liberation Front , May 23, 2013.
• Adam Thierer, “On the Line between Technology Ethics vs. Technology Policy,” August 23, 2013.

“The quickest way to find out who your enemies are is to try doing something new.” Thus begins Innovation and Its Enemies, an ambitious new book by Calestous Juma that will go down as one of the decade’s most important works on innovation policy.

Juma, who is affiliated with the Harvard Kennedy School’s Belfer Center for Science and International Affairs, has written a book that is rich in history and insights about the social and economic forces and factors that have, again and again, lead various groups and individuals to oppose technological change. Juma’s extensive research documents how “technological controversies often arise from tensions between the need to innovate and the pressure to maintain continuity, social order, and stability” (p. 5) and how this tension is “one of today’s biggest policy challenges.” (p. 8)

What Juma does better than any other technology policy scholar to date is that he identifies how these tensions develop out of deep-seated psychological biases that eventually come to affect attitudes about innovations among individuals, groups, corporations, and governments. “Public perceptions about the benefits and risks of new technologies cannot be fully understood without paying attention to intuitive aspects of human psychology,” he correctly observes. (p. 24)

Opposition to Change: It’s All in Your Head

Juma documents, for example, how “status quo bias,” loss aversion, and other psychological tendencies tend to encourage resistance to technological change. [Note: I discussed these and other “root-cause” explanations of opposition to technological change in Chapter 2 of my book, Permissionless Innovation: The Continuing Case for Comprehensive Technological Freedom, as well as in my 2012 law review article on “Technopanics, Threat Inflation, and the Danger of an Information Technology Precautionary Principle.”]  Juma notes, for example, that “society is most likely to oppose a new technology if it perceives that the risks are likely to occur in the short run and the benefits will only accrue in the long run.” (p. 5) Moreover, “much of the concern is driven by perception of loss, not necessarily by concrete evidence of loss.” (p. 11)

Juma’s approach to innovation policy studies is strongly influenced by the path-breaking work of Austrian economist Joseph Schumpeter, who long ago documented how entrepreneurial activity and the “perennial gales of creative destruction” were the prime forces that spurred innovation and propelled society forward. But Schumpeter was also one of the first scholars to realize that psychological fears about such turbulent change was what ultimately lead to much of the short-term opposition to new technologies that, in due time, we eventually come to see as life-enriching or even life-essential innovations.  Juma uses Schumpeter’s insight as the launching point for his exploration and he successfully verifies it using meticulously-detailed case studies.

Case Study-Driven Analysis

My favorite case study in the book discusses how the dairy industry fought the creation and spread of margarine (excuse the pun!). I had no idea how ugly that situation got, but Juma provides all the gory details in what I consider one of the very best crony capitalist case studies ever penned.

In particular, in a subsection of that chapter entitled “The Laws against Margarine,” he provides a litany of examples of how effective the dairy industry was in convincing lawmakers to enact ridiculous anti-consumer regulations to stop margarine, even though the product offered the public a much-needed, and much more affordable, substitute for traditional butter. At one point, the daily industry successfully lobbied five states to adopt rules mandating that any imitation butter product had to be dyed pink! Other states enacted labelling laws that required butter substitutes to come in ominous-looking black packaging. Again, all this was done at the request of the incumbent dairy industry and the National Dairy Council, which would resort to almost any sort of deceptive tactic to keep a cheaper competing product out of the hands of consumers.

And so it goes in chapter after chapter of Juma’s book. The amount of detail in each of these unique case studies is absolutely stunning, but they nonetheless remain highly readable accounts of sectoral protectionism, special interest rent-seeking, and regulatory capture. In this way, Juma is plowing some familiar ground already covered by other economic historians and political scientists, such as Joel Mokyr and Mancur Olson, both of whom are mentioned in the book, as well as a long line of public choice scholars who are, somewhat surprisingly, not discussed in the text. Nonetheless, Juma’s approach is still fresh, unique, and highly informative. In fact, I don’t think I’ve ever seen so many distinct and highly detailed case studies assembled in one place by a single scholar.  What Juma has done here is truly impressive.

Related Innovation Policy Paradigms

Beyond Schumpeter’s clear influence, Juma’s approach to studying innovation policy also shares a great deal in common with two other unmentioned innovation policy scholars, Virginia Postrel and Robert D. Atkinson.

Postrel’s 1998 book, The Future and Its Enemies, contrasted the conflicting worldviews of “dynamism” and “stasis” and showed how the tensions between these two visions would affect the course of human affairs. She made the case for embracing dynamism — “a world of constant creation, discovery, and competition” — over the “regulated, engineered world” of the stasis mentality. Similarly, in his 2004 book, The Past and Future of America’s Economy, Atkinson documented how “American history is rife with resistance to change,” and in recounting some of the heated battles over previous technological revolutions he showed how two camps were always evident: “preservationists” and “modernizers.”

When Juma repeatedly recounts the fight between “innovation and incumbency” in his case studies, he is essentially describing the same paradigmatic divide that Postrel and Atkinson highlight in their works when they discuss “dynamist” vs. “stasis” tensions and the “modernizers” vs. “preservationists” battles that we have seen throughout history. [Note: In my 2014 essay on, “Thinking about Innovation Policy Debates: 4 Related Paradigms,” I discussed Postrel and Atkinson’s books and other approaches to understanding tech policy divisions and then related them to the paradigms I contrast in my work: the so-called “precautionary principle” vs. “permissionless Innovation” mindsets.]

Finally, Juma’s book could also be compared to another freshly released book, The Politics of Innovation, by Mark Zachary Taylor. Taylor’s book is also essential reading on this lamentable history of industrial protectionism and the resulting political opposition to change we have seen over time. [Note: Brent Skorup and provided many other high-tech cronyist case studies like these in our 2013 law review article, “A History of Cronyism and Capture in the Information Technology Sector.”]

To counter the prevalence of special interest influence and poor policymaking more generally, Juma stresses the need for evidence-based analysis and a corresponding rejection of fear-mongering and deceptive tactics by public officials and activist groups. He’s particularly concerned with “the use of demonization and false analogies to amplify the perception of risks associated with a new product.”

Accordingly, he would like to see improved educational and risk communication efforts aimed at better informing the public about risk trade-offs and the many potential future benefits of emerging technologies. “Learning how to communicate to the general public is an important aspect of reducing distrust [in new technologies],” Juma argues. (p. 312)

On the Pacing Problem

But Juma never really adequately squares that recommendation with another point he makes throughout the text about how “the pace of technological innovation is discernibly fast,” (p. 5) and how it is accelerating in an exponential fashion. “The implications of exponential growth will continue to elude political leaders if they persist in operating with linear worldviews.” (p. 14) But if it is indeed the case that things are moving that fast, then are we not potentially doomed to live in never-ending cycles of technopanics and misinformation campaigns about new technologies no matter how much education we try to do?

Regardless, Juma’s argument about the speed of modern technological change is quite valid and shared by many other scholars. He is essentially making the same case that Larry Downes did in his excellent 2009 book, The Laws of Disruption: Harnessing the New Forces That Govern Life and Business in the Digital Age. Downes argued that lawmaking in the information age is inexorably governed by the “law of disruption” or the fact that “technology changes exponentially, but social, economic, and legal systems change incrementally.”  This law, Downes said, is “a simple but unavoidable principle of modern life,” and it will have profound implications for the way businesses, government, and culture evolve going forward.  “As the gap between the old world and the new gets wider,” he argued, “conflicts between social, economic, political, and legal systems” will intensify and “nothing can stop the chaos that will follow.”

Again, Juma makes that same point repeatedly throughout the chapters of his book. This is also a restatement of the so-called “pacing problem,” as it is called in the field of the philosophy of technology. I discussed the pacing problem at length in my recent review of Wendell Wallach’s important new book, A Dangerous Master: How to Keep Technology from Slipping beyond Our Control. Wallach nicely defined the pacing problem as “the gap between the introduction of a new technology and the establishment of laws, regulations, and oversight mechanisms for shaping its safe development.” “There has always been a pacing problem,” he noted but, like Juma, Wallach believes that modern technological innovation is occurring at an unprecedented pace, making it harder than ever to “govern” using traditional legal and regulatory mechanisms.

New Approaches to Technological Governance Needed

Both Wallach in A Dangerous Master and Juma in Innovation and Its Enemies struggle with how to solve this problem. Wallach advocates “soft law” mechanisms or even informal “Governance Coordinating Committees,” which would oversee the development of new technology policies and advise existing governmental institutions. Juma is somewhat ambiguous regarding potential solutions, but he does stress the general need for a flexible approach to policy, as he notes on pg. 252:

It is important to make clear distinctions between hazards and risks. It is necessary to find a legal framework for addressing hazards. But such a framework should not take the form of rigid laws whose adoption needs to be guided by evidence of harm. More flexible standards that allow continuous assessment of emerging safety issues related to a new product are another way to address hazards. This approach would allow for evidence-based regulation.

Beyond that Juma wants to see “entrepreneurialism exercised in the public arena” (p. 282) and calls for “decisive leaders to champion the application of new technologies.” (p. 283) He argues such leadership is needed to ensure that life-enriching technologies are not derailed by opponents of change.

On the other hand, Juma sees a broader role for policymakers in helping to counter some of the potential side effects associated with many emerging technologies. He highlights three primary areas of concern. First, he suggests political leaders might need to find ways “to help balance the benefits and risks of automation” due to the rapid rise of robotics and artificial intelligence. Second, he notes that synthetic biology and gene-editing will give rise to many thorny issues that require policymakers to balance “potentially extraordinary benefits and the risk of catastrophic consequences.” (p. 284)  Finally, he points out that medicine and healthcare are set to be radically transformed by emerging technologies, but they are also threatened by archaic policies and practices in many countries.

In each case, Juma hopes that “decisive,” “adaptive” and “flexible” leaders will steer a sensible policy course with an eye toward limiting “the spread of political unrest and resentment toward technological innovation.” (p. 284)  That’s a noble goal, but Juma remains a bit vague on the steps needed to accomplish that balancing act without tipping public policy in favor a full-blown precautionary principle-based regime for new technologies. Juma clearly wants to avoid that result, but it remains unclear how or where he would draw clear lines in the sand to prevent it from occurring while at the same time achieving “decisive leadership” aimed at balancing potential risks and benefits.

Similarly, his repeated calls in the closing chapter for “inclusive innovation” efforts and strategies sounds sensible in theory, but Juma speaks in abstract generalities about what the term means and doesn’t provide a clear vision for how that would translate into concrete actions that would not end up giving vested interests a veto over new forms of technological innovation that they disfavor.

Nothing Ventured, Nothing Gained

Generally speaking, however, Juma wants this balance struck in favor of greater openness to change and an ongoing freedom to experiment with new technological capabilities. As he notes in his concluding chapter:

The biggest risk that society faces by adopting approaches that suppress innovation is that they amplify the activities of those who want to preserve the status quo by silencing those arguing for a more open future. […] Keeping the future open and experimenting in an inclusive and transparent way is more rewarding that imposing the dictum of old patterns. (pgs. 289, 316)

In that regard, the thing I liked most about Innovation and Its Enemies is the way throughout the text that Juma stressed the symbiotic relationship between risk-taking and progress. One of the ways he does so is by kicking off every chapter with a fun quote on that theme from some notable figure. He includes gems like these:

• “Nothing will ever be attempted if all possible objections must be first overcome.” – Samuel Johnson
• “Only those will risk going too far can possibly find out how far one can go.” – T.S. Eliot
• “If you risk nothing, then you risk everything.” – Geena Davis
• “Test fast, fail fast, adjust fast.” – Tom Peters

Of course, I was bound to enjoy his repeated discussion of this theme because that was the central thesis of my latest book, in which I made the argument that, “if we spend all our time living in constant fear of worst-case scenarios—and premising public policy upon such fears—then many best-case scenarios will never come about.” Or more simply, as the old saying goes: “nothing ventured, nothing gained.”

On Pastoral Myths

I also liked the way that Juma used his case studies to remind us how “the topics may have changed, but the tactics have not.” (p. 143) For example, much of the fear-mongering and deceptive tactics we have seen through the years are based on “pastoral ideals,” i.e., appeals to nature, farm life, old traditions, of just the proverbial “good old days,” whenever those supposedly were! “Demonizing innovation is often associated with campaigns to romanticize past products and practices,” Juma notes. “Opponents of innovation hark back to traditions as if traditions themselves were not inventions at some point in the past.” (p. 309)  So very true!

That was especially the case in battles over new farming methods and technologies, when opponents of change were frequently “championing a moral cause to preserve a way of life,” as Juma discusses in several chapters. (p. 129) New products or methods of production were repeatedly but wrongly characterized as dangerous simply because they were not supposedly “natural” or “traditional” enough in character.

Of course, if all farming and other work was to remain frozen in some past “natural” state, we’d all still be hunters and gathers struggling to find the next meal to put in our bellies. Or, if we were all still on the farms of the “good old days,” then we’d still be stuck using an ox and plow in the name of preserving the “traditional” ways of doing things.

Humanity has made amazing strides—including being able to feed more people more easily and cheaply than ever before—precisely because we broke with those old, “natural” traditions. Alas, many vested interests and even quite a few academics today still employ these same pastoral appeals and myths to oppose new forms of technological change. Juma’s case studies powerfully illustrate why that dynamic continues to be a driving force in innovation policy debates and how it has delayed the diffusion of many important new goods and services throughout history. When the opponents of change rest their case on pastoral myths and nostalgic arguments about the good old days we should remind them that the good old days weren’t really that great after all.

Conclusion

In closing, Innovation and Its Enemies earns my highest recommendation. Even though 2016 is only half done as I write this, Professor Juma’s book is probably already a shoo-in as my choice for best innovation policy book of the year. And I am certain that it will also go down as one of the decade’s most important innovation policy books. Buy the book now and read every word of it. It is well worth your time.

Additional material related to Juma’s book:

• Calestous Juma’s website at the Harvard Kennedy School
• Official book page for Innovation and Its Enemies
• Concise summary of the book from AAAS: “Why important innovations stall; understanding obstacles to change is key to future”
• Steven Overly, “Humans once opposed coffee and refrigeration. Here’s why we often hate new stuff,” Washington Post, July 21, 2016.
• Matt Ridley’s review of the book for The Times of London.

Other Related Books

In addition to the books that I already mentioned throughout this review, readers who find Juma’s book and the issues he discusses in it of interest should also consider reading these other books on innovation policy, technological governance, and regulatory capture.  Although many of them are more squarely focused on the information technology sector or other emerging technology fields, they all relate to the general subject matter and approach found throughout Juma’s book. [NOTE: Links, where provided, are to my reviews of these books.]

• The Inevitable: Understanding the 12 Technological Forces That Will Shape Our Future, by Kevin Kelly (2016)
• Innovative Governance Models for Emerging Technologies, Gary E. Marchant, Kenneth W. Abbott & Braden Allenby (eds.), (2013)
• Consent of the Networked: The Worldwide Struggle for Internet Freedom ,by Rebecca MacKinnon (2012)
• Networks and States: The Global Politics of Internet Governance, by Milton Mueller (2010)
• The Master Switch: The Rise and Fall of Information Empires, by Tim Wu (2010)
• The Rational Optimist: How Prosperity Evolves, by Matt Ridley (2010)
• Blown to Bits: Your Life, Liberty, and Happiness After the Digital Explosion, by Hal Abelson, Ken Ledeen, and Harry Lewis (2008)
• Radical Evolution: The Promise and Peril of Enhancing Our Minds, Our Bodies — and What It Means to Be Human, by Joel Garreau (2005)
• The Creation of Media, by Paul Starr (2005)
• Ruling the Waves: Cycles of Discovery, Chaos, and Wealth from the Compass to the Internet, by Debora Spar (2004)
• Questioning Technology, by Andrew Feenberg (1999)
• Thinking through Technology: The Path between Engineering and Philosophy, by Carl Mitcham (1994)
• Technologies of Freedom: On Free Speech in an Electronic Age, by Ithiel de Sola Pool (1983)

I was honored to be asked by the editors at Reason magazine to be a part of their “Revolutionary Reading” roundup of “The 9 Most Transformative Books of the Last 45 Years.”  Reason is celebrating its 45th anniversary and running a wide variety of essays looking back at how liberty has fared over the past half-century. The magazine notes that “Statism has hardly gone away, but the movement to roll it back is stronger than ever.” For this particular feature, Reason’s editors “asked seven libertarians to recommend some of the books in different fields that made [the anti-statist] cultural and intellectual revolution possible.”

When Jesse Walker of Reason first contacted me about contributing my thoughts about which technology policy books made the biggest difference, I told him I knew exactly what my choices would be: Ithiel de Sola Pool’s Technologies of Freedom (1983) and Virginia Postrel’s The Future and Its Enemies (1998). Faithful readers of this blog know all too well how much I love these two books and how I am constantly reminding people of their intellectual importance all these years later. (See, for example, this and this.) All my thinking and writing about tech policy over the past two decades has been shaped by the bold vision and recommendations set forth by Pool and Postrel in these beautiful books.

As I note in my Reason write-up of the books:

The past 45 years have seen remarkable advances in information technology: the Internet, mobile communications, ubiquitous news and entertainment options, and much more. What made these and other innovations possible was a general openness to the unplanned, the unpredictable, and even the uncontrollable. In our willingness to embrace a world of uncertainty and incessant change, we found unparalleled technological abundance. No two books more eloquently captured and celebrated the information age than Ithiel de Sola Pool’s Technologies of Freedom and Virginia Postrel’s The Future and Its Enemies.

And I conclude by noting that “While plenty of tech pundits and academics cling to… stasist thinking today, Pool and Postrel’s books continue to provide beacons for a better world, free from the top-down, technocratic mentality and prescriptions of the past. At least thus far, permissionless innovation has largely trumped the precautionary principle in tech policy. Let’s hope the dynamist vision can hold the line for another 45 years.”

Head over to Reason to read the rest of my essay as well as all the other excellent books that contributors have recommended as part of the symposium.  There are some really great selections in there.

And if you care about the future of technological freedom and human liberty and progress more generally, please do read (or re-read) both Pool and Postrel’s books when you have a chance.  They changed my life and they will change yours, too.

I finally got around to reading Planet Google: One Company’s Audacious Plan to Organize Everything We Know, by Randall Stross. It’s very well done. Stross is a frequently contributor to the New York Times and the author of several other interesting books on the technology industry. He knows how to weave a story together, and it helps that Google’s story is a pretty amazing one.

Each chapter discusses a different part of Google’s growing family of services — GMail, Google Maps, Google Earth, Book Search, and YouTube. Of course, it all started with search and Stross does a good job explaining how the ingenious Google search algorithm has grown from dorm room project to the greatest aggregator of human knowledge that the world has ever known. This, in turn, has powered Google’s hugely successful online advertising system. The real secret of their success with online advertising, Stross argues, is that “Google’s impersonal, mathematical approach search also provides you with the ability to serve advertisements that are tailored to a search, rather than to the person submitting the search request, whose identity would have to be known.”

Despite the benefits of such generally anonymous searching, as Google has grown and added new services and capabilities, concerns about the sheer volume of data that the company collects have led to heightened privacy concerns. Indeed, privacy is a core theme that Stross uses in the book to tie many of the chapters and issues together. Google is constantly struggling to strike the right balance between providing more access to the world’s information while also being careful not to raise privacy concerns. But it’s unclear exactly how much more information collection that users (or public officials) will tolerate before advocating stricter limits on Google’s reach.  As Stross points out:

Guided by its founding mission, to organize all the world’s information, Google has created storage capacity that allows it to gain control of what its users are you doing in a comprehensive way that no other company has done, and to preserve those records indefinitely, without the need to clear out old records to make way for new ones. Moreover, Google differentiates its service by refining its own proprietary software formula to mine and massage the data, technology that it zealously protects from the sight of rivals. This sets up a conflict between Google’s wish to operate a “black box” (completely opaque to the outside) and its users’ wish for transparency.

At the very least, users would like Google to disclose what protections are in place to safeguard their privacy. It is also natural that users would be curious about the machines that hold their personal data, as well as about which employees within Google have access to that data, and about the risks that it might be leaked, stolen, or transferred, for example, to a government agency that requests it. (p. 62)

Personally, I think most of these privacy fears are overblown. The mundane, trivial aspects of our daily lives aren’t really of much interest to Google. And to the extent users are concerned about their privacy, there are plenty of ways they can take steps to better protect their personal information or web-surfing habits.  Blocking ads, rejecting cookies, and using encryption are three steps that privacy-sensitive users can take to better shield the personal info or surfing habits. Finally, the concern about government access to data is best remedied by limits on what government can access in the first place. We shouldn’t be regulating Google or other companies to limit information collection based on a fear of government access; we just need to tightly limit the government’s ability to enlist private companies as agents of the state.

Still, as Stross points out, privacy concerns persist:

How can users be certain that their personal information won’t be put to uses to which an individual would never willingly consent? Privacy concerns extend across all Internet companies, but those concerns of our greatest where personal information is gathered in the largest pool. This makes the stewardship of Google’s machine a subject of public interest. Whatever is behind a door that is intentionally kept closed will appear sinister, whether deservedly so or not. For the sake of improving its public image, it’s possible that Google may relent and open its doors, at least enough to afford a peek inside. (p. 62)

I think that’s a fair point and this is something Google is really going to struggle with in coming years, especially as its search algorithm and other applications grow more powerful and comprehensive.  A good example of that is already seen with Google’s amazing “Street View” technology, which provides panoramic street-level views of maps searched via Google Maps. “What neither Google nor its critics realized,” Stross says, “was that our anonymity while walking about in public space in the predigital age was protected not by law but by the crude state of technology–we felt invisible only because cameras were not in place to capture our images.” (p. 145)

As a society, we had better get used to this because Street View is just the beginning of what will eventually grow into a far more sophisticated set of technologies as geo-mapping, geo-location, and image retrieval are married to virtual reality technologies. We’re really not that far away from Star Trek “holodecks” being projected into our living rooms, and once those holodecks let us walk down any street in the world, things are going to get both really exciting and a little bit creepy at the same time. But even if Google abandoned Street View tomorrow, somebody else would pick it up and run with it. Innovation in this space cannot be frozen. (Microsoft’s recent launch of Photosynth shows us that).  Google has already taken steps to protect privacy on Street View by blurring facial images and letting users flag “inappropriate or sensitive imagery for blurring or removal.”  That’s about all we can ask for.

Another theme that Stross develops nicely in the book is the ongoing war between Google and Microsoft. He argues that “Google’s ascendance has been accompanied by Microsoft’s decline.” (p. 195)  But that does not mean Google will be able to hold their current lead. As Stross rightly points out:

No computer company has ever been able to enjoy pre-eminence that spans two successive technological eras. IBM in the mainframe era could not head off the ascent of Digital Equipment Corporation in the minicomputer era, which, in turn, could not head off the ascent of Microsoft in the personal computer era.

And now Google has “succeeded in pushing Microsoft into a defensive crouch” and made life very difficult for that supposed “monopolist” of the PC era.  As a result, some Google critics claim this latest King of the Tech Hill cannot be toppled and that Google is the new “monopoly” we need to worry about.  But these fears are also overblown. Google faces threats today from many different providers and doesn’t really even have its act together in other areas. For example, Stross points out how Facebook and other social networking sites have been a real pain for Google. Facebook, in particular, is creating a massive walled garden that is largely outside Google’s search and information retrieval capabilities. “In a twinkling,” Stross argues, “Facebook became a miniature Web universe–behind a wall, inaccessible to Google.” (p. 30)  Meanwhile, in recent months, Google has annouced layoffs and has scuttled a variety of programs and projects which haven’t panned out, including experiments in social networking, virtual worlds, and a Twitter competitor.

But it is tomorrow’s providers and technologies that will pose the most serious challenge to Google’s current hegemony. No one can predict what big application(s) or competitor(s) will emerge next, but it all could happen faster than you think.  After all, let’s not forget that most of us hadn’t even conducted our first Google search 10 years ago, and no one considered Google a serious threat to Microsoft back in 1999.  Just a decade later, Google has Microsoft wondering if they have a future at all. Things can change that rapidly in the digital world and it should make us question the wisdom of government intervention into such a fast-moving field.

Moreover, government micromanagement of the services Google provides–especially search–is troubling to imagine. I don’t even want to think about how a DOJ consent decree would seek to control Google’s algorithm or the search business in general. But some critics are already speaking of “Googleopoly” and calling for a “Federal Search Commission,” foreshadowing the fight to come.  Google’s rapid growth and sheer size may end up tilting both policymakers and public opinion against them more and more in coming years as such “Googlephobia” increases. Stross notes that:

Google’s future will be determined to no small degree by the view that its users hold of the company itself. Google has enjoyed mostly favorable public notice in its first ten years, but maintaining a cuddly, anticorporate image when it stands among the U.S. companies with the largest market capitalization may pose an increasingly difficult challenge. (p. 18)

Indeed, Google’s “Don’t Be Evil” motto is already wearing a little thin in some quarters. And some of us still aren’t even sure what it means. As Google grows bigger and makes buckets more money in coming years–and they likely will–I think Stross is correct in arguing that Google’s honeymoon with the public and policymakers will likely come to an end. That doesn’t mean they won’t still be a great company doing great things, it’s just that they’ll be antagonizing even more competitors, lawmakers, and other groups than they already do today. And that will likely spell serious trouble for them. It’s never good to have so many enemies. Just ask Microsoft!

In the meantime, we shouldn’t lose sight of what an amazing capitalist success story Google has been and how lucky we are that they have been at least a little bit successful in their mission “to organize the world’s information and make it universally accessible and useful.”  It’s an incredible story, and Planet Google is a fine early history of the company and the new era of computing it has ushered in.