Ethics – 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 7 AI Policy Issues to Watch in 2023 and Beyond https://techliberation.com/2023/02/10/7-ai-policy-issues-to-watch-in-2023-and-beyond/ https://techliberation.com/2023/02/10/7-ai-policy-issues-to-watch-in-2023-and-beyond/#respond Fri, 10 Feb 2023 13:33:58 +0000 https://techliberation.com/?p=77088

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

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

1) Privacy and Data Collection

2) Bias and Discrimination

3) Free Speech and Disinformation

4) Kids’ Safety

5) Physical Safety and Cybersecurity

6) Industrial Policy and Workforce Issues

7) National Security and Law Enforcement Issues

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

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

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

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

Additional Reading

]]> https://techliberation.com/2023/02/10/7-ai-policy-issues-to-watch-in-2023-and-beyond/feed/ 0 77088 Tech Regulation Will Increasingly Be Driven Through the Prism of “Algorithmic Fairness” https://techliberation.com/2022/11/06/tech-regulation-will-increasingly-be-driven-through-the-prism-of-algorithmic-fairness/ https://techliberation.com/2022/11/06/tech-regulation-will-increasingly-be-driven-through-the-prism-of-algorithmic-fairness/#comments Sun, 06 Nov 2022 18:51:21 +0000 https://techliberation.com/?p=77056

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

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

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

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

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

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

Additional Reading :

 

]]> https://techliberation.com/2022/11/06/tech-regulation-will-increasingly-be-driven-through-the-prism-of-algorithmic-fairness/feed/ 4 77056 We Need to Get All the Smart People in a Room & Have a Conversation https://techliberation.com/2022/10/16/we-need-to-get-all-the-smart-people-in-a-room-have-a-conversation/ https://techliberation.com/2022/10/16/we-need-to-get-all-the-smart-people-in-a-room-have-a-conversation/#comments Sun, 16 Oct 2022 12:51:13 +0000 https://techliberation.com/?p=77052

For my latest Discourse column (“We Really Need To ‘Have a Conversation’ About AI … or Do We?”), I discuss two commonly heard lines in tech policy circles.

1) “We need to have conversation about the future of AI and the risks that it poses.”

2) “We should get a bunch of smart people in a room and figure this out.”

I note that, if you’ve read enough essays, books or social media posts about artificial intelligence (AI) and robotics—among other emerging technologies—then chances are you’ve stumbled on variants of these two arguments many times over. They are almost impossible to disagree with in theory, but when you start to investigate what they actually mean in practice, they are revealed to be largely meaningless rhetorical flourishes which threaten to hold up meaningful progress on the AI front. I continue on to argue in my essay that:

I’m not at all opposed to people having serious discussions about the potential risks associated with AI, algorithms, robotics or smart machines. But I do have an issue with: (a) the astonishing degree of ambiguity at work in the world of AI punditry regarding the nature of these “conversations,” and, (b) the fact that people who are making such statements apparently have not spent much time investigating the remarkable number of very serious conversations that have already taken place, or which are ongoing, about AI issues. In fact, it very well could be the case that we have  too many conversations going on currently about AI issues and that the bigger problem is instead one of better coordinating the important lessons and best practices that we have already learned from those conversations.

I then unpack each of those lines and explain what is wrong with them in more detail. One thing that always bugs be about the “we need to have a conversation” aphorism is that those uttering it absolutely refuse to be nailed down on the specifics, like:

  1. What is the nature or goal of that conversation?
  2. Who is the “we” in this conversation?
  3. How is this conversation to be organized and managed?
  4. How do we know when the conversation is going on, or when it is sufficiently complete such that we can get on with things?
  5. And, most importantly, aren’t you implicitly suggesting that we should ban or limit the use of that technology until you (or the royal “we”) is somehow satisfied that the conversation is over or yielded satisfactory answers?

The other commonly heard line — “We need to get a bunch of smart people in a room and figure this out” — can be equally infuriating due to both a lack of specifics (which people? what room? where and when? etc) but also because of the fact that we already have had tons of the Very Smartest People on these issues meeting in countless rooms across the globe for many years. In an earlier essay, I documented the astonishing growth of AI governance frameworks, ethical best practices and professional codes of conduct: “The amount of interest surrounding AI ethics and safety dwarfs all other fields and issues. I sincerely doubt that ever in human history has so much attention been devoted to any technology as early in its lifecycle as AI.”

I also note that, practically speaking, “the most important conversations society has about new technologies are those we have every day when we all interact with those new technologies and with one another. Wisdom is born from experiences, including activities and interactions involving risk and the possibility of mistakes. This is how progress happens.” And I conclude by noting how:

We won’t ever be able to “have a conversation” about a new technology that yields satisfactory answers for some critics precisely because the questions just multiply and evolve endlessly over time, and they can only be answered through ongoing societal interactions and problem-solving. But we shouldn’t stop life-enriching innovations from happening just because we don’t have all the answers beforehand.

Anyway, I invite you to head over to  Discourse and read the entire essay. In the meantime, I propose we get all the smart people in a room and have a conversation about how these two lines came to dominate tech policy discussions before they end up doing real damage to human prosperity! It’s the ethical thing to do if you really care about the future.

]]> https://techliberation.com/2022/10/16/we-need-to-get-all-the-smart-people-in-a-room-have-a-conversation/feed/ 2 77052 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 DIY-Bio, Biohacking & Evasive Entrepreneurialism https://techliberation.com/2020/05/26/diy-bio-biohacking-evasive-entrepreneurialism/ https://techliberation.com/2020/05/26/diy-bio-biohacking-evasive-entrepreneurialism/#comments Tue, 26 May 2020 15:08:28 +0000 https://techliberation.com/?p=76740

DIY medicineMargaret Talbot has written an excellent New Yorker essay entitled, “The Rogue Experimenters,” which documents the growth of the D.I.Y.-bio movement. This refers to the organic, bottom-up, citizen science movement, or “leaderless do-ocracy” of tinkerers, as she notes. I highly recommend you check it out.

As I noted in my new book on Evasive Entrepreneurs and the Future of Governance, “DIY health services and medical devices are on the rise thanks to the combined power of open-source software, 3D printers, cloud computing, and digital platforms that allow information sharing between individuals with specific health needs. Average citizens are using these new technologies to modify their bodies and abilities, often beyond the confines of the law.”

Talbot discusses many of the same examples I discuss in my book, including:

  • the Four Thieves Vinegar collective, which devised instructions for building its own version of the EpiPen;
  • e-nable, an international collective of thirty thousand volunteers, designs and 3-D-prints prosthetic hands and arms (and which has, more recently, distributed more than fifty thousand face shields in more than twenty-five countries.);
  • GenSpace and other community biohacking labs; and
  • Open Insulin and Open Artificial Pancreas System.

I like the way Talbot compares these movements to the hacker and start-up culture of the Digital Revolution:

The D.I.Y.-bio movement, which emerged in the early two-thousands, seems almost evolutionarily adapted to its historical moment,” she argues. “It echoes aspects of startup culture, especially the early days of personal computing, with its garage-based origin stories. First came the hardware, then the software; now even the wetware of life can be created in people’s homes. D.I.Y. bio reflects popular skepticism about professional authority and gatekeeping, but it is not skeptical about learning or expertise.

She also quotes others on this point, like John Wilbanks, a health technologist at the research nonprofit Sage Bionetworks:

when new biotech companies fail, they tend to sell off their equipment for a discount, and community labs and biohackers scoop it up. Wilbanks told me, “D.I.Y. bio is very similar to the home-brew, hacker-club culture of the late seventies in Silicon Valley. If you’ve not gone on eBay to shop for a DNA sequencer that they can ship to you in twenty-four hours, check it out—there’s a massive secondary market.”

Perhaps the most interesting thing about this bottom-up citizen-science movement is that it run the political gamut. It includes “anarcho-libertarians” to those “steeped in social-justice activism,” Talbot says. But they are all generally unified by a commitment to the widespread dissemination of scientific knowledge and transparency in health-related matters. “D.I.Y. biologists often have a greater commitment than their professional counterparts do to making their work open to scrutiny—and available for free on the Internet,” Talbot notes.

“The D.I.Y.-bio ecosystem includes a lot of do-gooders, and many of them have been galvanized by the covid-19 crisis,” she also observes. Quite right. I discussed that fact in the launch essay for my book, “Evasive Entrepreneurialism and Technological Civil Disobedience in the Midst of a Pandemic.” I documented dozens of examples of various individuals and organizations rising up to meet the challenges posed by the pandemic. “Eventually, people take notice of how regulators and their rules encumber entrepreneurial activities, and they act to evade them when public welfare is undermined,” I argued. “Working around the system becomes inevitable when the permission society becomes so completely dysfunctional and counterproductive.” DIY health innovation has gone mainstream out of necessity.

Importantly, Talbot notes that when it comes to what counts as success for DIY health and biohacking, sometimes good enough is, well, good enough. On this point, she quotes Jon Schull, an e-nable (non-commercial 3D-printed prosthetics) co-founder, who says, “it doesn’t matter that e-nable hands aren’t state-of-the-art. The job of professional prostheses-makers, he said, is “to produce something really good, and if it’s merely better than nothing it’s not good enough”—but, in some circumstances, something is better than nothing.”

That is a crucial point understanding why this movement is so important: Working together in a spontaneous, bottom-up fashion, citizen scientists and tinkerers can act quickly to fill pressing public health needs. Of course, that is exactly what makes these same innovations potentially risky and has some people wondering about the wisdom of such efforts—and the potential need for more regulation.

I wish Talbott would have spent a bit more time diving into these ethical and legal questions. I really struggled with them when writing about all this stuff in my new book on evasive entrepreneurialism and technological civil disobedience. She does briefly discuss how some FDA regs might affect DIY bio movement, including efforts like Open Insulin.  “Even if Open Insulin begins producing a consistent product, it will have to overcome all kinds of regulatory obstacles to demonstrate safety and purity before taking it to market,” she notes. “Manufacturers of pharmacy-grade medications must provide the F.D.A. with reams of evidence that they can produce the substances with complete consistency, in sterile environments. Proving this level of proficiency can cost millions of dollars.” But Talbot does not spend much more time exploring what might happen next on this front if DIY efforts continue to expand.

“But what should the law say about people… who are creating their own specialized medical devices in an open-source, noncommercial fashion?” I ask in my new book.

I outlined three potential future scenarios for the movement:

  1. DIY technologies go mainstream and become more commercialized.
  2. biohacking remains decentralized but becomes more mainstream and professional without becoming fully commercial.
  3. biohacking turn even more rogue or underground in nature as a form of guerrilla innovation that sometimes borders on neo-anarchism.

Regardless of the outcome, the ethical and regulatory issues will persist and grow as technological capabilities continue to grow more sophisticated, decentralized, and inexpensive. I argue in the book that it would be foolish for policymakers to think they can (or should) bottle up this movement altogether:

biohacking and decentralized medicine will expand for a simple reason: People care deeply about improving their health and abilities. They will take advantage of new technological capabilities that let them do so—especially when those capabilities are significantly cheaper than other options. To reiterate, that does not make these technologies safe or smart, but it does mean we will need a new approach to governance as evasive entrepreneurialism expands in this arena.

And then I continue on to note how improved risk education and awareness efforts might be one solution to the growing DIY bio movement.

Anyway, for more discussion on this, see pages 79-87 of my new book. I’ve also listed a few other essays down below that you might find interesting, including several penned by my former colleague Jordan Reimschisel.

Additional Reading:

]]> https://techliberation.com/2020/05/26/diy-bio-biohacking-evasive-entrepreneurialism/feed/ 2 76740 Biased AI is More Than a Technical Problem: Building a Process-oriented Policy Approach to AI Governance https://techliberation.com/2020/05/06/biased-ai-is-more-than-a-technical-problem-building-a-process-oriented-policy-approach-to-ai-governance/ https://techliberation.com/2020/05/06/biased-ai-is-more-than-a-technical-problem-building-a-process-oriented-policy-approach-to-ai-governance/#respond Wed, 06 May 2020 14:18:17 +0000 https://techliberation.com/?p=76711 Image Credit: Police Science Innovation

[Co-authored with Walter Stover]

Artificial Intelligence (AI) systems have grown more prominent in both their use and their unintended effects. Just last month, LAPD announced that they would end their use of a predicting policing system known as PredPol, which had sustained criticism for reinforcing policing practices that disproportionately affect minorities. Such incidents of machine learning algorithms producing unintentionally biased outcomes have prompted calls for ‘ethical AI’. However, this approach focuses on technical fixes to AI, and ignores two crucial components of undesired outcomes: the subjectivity of data fed into and out of AI systems, and the interaction between actors who must interpret that data. When considering regulation on artificial intelligence, policymakers, companies, and other organizations using AI should therefore focus less on the algorithms and more on data and how it flows between actors to reduce risk of misdiagnosing AI systems. To be sure, applying an ethical AI framework is better than discounting ethics all together, but an approach that focuses on the interaction between human and data processes is a better foundation for AI policy.

The fundamental mistake underlying the ethical AI framework is that it treats biased outcomes as a purely technical problem. If this was true, then fixing the algorithm is an effective solution, because the outcome is purely defined by the tools applied. In the case of landing a man on the moon, for instance, we can tweak the telemetry of the rocket with well-defined physical principles until the man is on the moon. In the case of biased social outcomes, the problem is not well-defined. Who decides what an appropriate level of policing is for minorities? What sentence lengths are appropriate for which groups of individuals? What is an acceptable level of bias? An AI is simply a tool that transforms input data into output data, but it’s people that give meaning to data at both steps in context of their understanding of these questions and what appropriate measures of such outcomes are.

The Austrian school of economics is well-suited to helping us grapple with these kinds of less well-defined problems. Austrian economists levied a similar critique against mainstream economics, which treated economic outcomes as a technical problem to be solved with specific technical decisions. The Austrians stressed a principle of methodological individualism, which holds that socioeconomic outcomes are ultimately the products of individual decisions, and cannot be acted on directly by technocratic policymakers. Methodological individualism involves the recognition that individuals drive outcomes in two primary aspects: subjective interpretation of their environment, and through interaction with each other and that same environment. We can sum up application of these two aspects to AI systems in two questions: who gets the data, and where does the data go?

It matters who gets the data because the necessity of subjective interpretation will lead different people to reach separate conclusions about the same data. As an example, a set of data on financial variables such as defaults and debt repayment frequency combined with personal characteristics such as race and geographic locations may lead one person to label African-Americans as larger credit risks. Other individuals reading the same data, however, may arrive at a different conclusion: the patterns in this data stem from structural racism that has suppressed income of African American households compared to other households, and do not indicate that they are inherently riskier. The first interpretation would result in biased outcomes from an AI system used to generate predictions of credit risk based on that data, whereas the second interpretation might actually result in beneficial outcomes; for instance, an agency might offer with more lenient terms to these individuals.

The second question of where data goes depends on the interaction of individuals with each other and their environment, which drives the flow of data and also determines how that data is acted upon. In her book Weapons of Math Destruction, Cathy O’Neil offers a perfect example of this when analyzing what went wrong with the LAPD’s use of PredPol, which took in data on past crimes and used it to predict the geographic location of new crimes. Police forces took this data and increased their presence in hot spots of predicted crime, which resulted in a positive feedback loop of more crime data originating in that area (because of increased interaction between police officers and residents of that neighborhood in the form of increased arrests) generating more predictions of crime, leading to over-policing of minority groups. Ultimately, the data went to a police department that unintentionally increased arrests of minority groups.

Together, the subjectivity of data and the importance of interaction get at a core insight of Austrian economics that directly follows the principle of methodological individualism: context matters. If how data is interpreted and used differs from person to person, then the flows of data matter in who gets the data first and how they use it, potentially transforming the data before sending it on. Thinking along these lines shifts us away from focusing on building better, more ethical AI, and more towards trying to better understand the dynamics of data within a system: who is selecting which data to feed into an AI, what data the AI then generates, and most importantly, how that data is then acted upon and by whom. If we don’t take these matters into consideration, we risk myopically focusing on fixes to the AI that will not change outcomes. In the case of PredPol, for example, the AI could have been completely transparent, but the outcome would have been the same because of how police officers were acting on the output data according to their institutional context.

Some experts are already calling for more process-oriented AI governance approaches, including the EU’s High-Level Expert Group on AI and professional services network KPMG. Carolyn Herzog, general counsel and chair of an ethics working group, comes close to the approach we are advocating in stressing that “…data is the lifeblood of AI,” and that we must pay attention to “…issues of how that data is being collected, how it is being used, and how it is being safeguarded.” However, at present, this data-oriented approach is not represented clearly in U.S. policy. Recent AI policy movements, including ethical principles released by the Department of Defense and the Office of Management and Budget’s AI Guidelines, are a good first step but still emphasize the technology more than the data flows, and are limited to the government’s use of AI. Principle 9 of the guidelines, for instance, notes the importance of having controls to ensure “…confidentiality, integrity, and availability of the information stored, processed, and transmitted by AI systems,” but does not extend this to explicitly consider how the data is used after being transmitted.

Moreover, these proposals do not coherently lay out the relationship between data and AI outcomes because they do not give enough emphasis on where data goes and how it is used in context after being transmitted from the AI system. Returning to our earlier point, interactions matter. Take PredPol as an example. Even if we know how data was being collected, stored, and used by PredPol, and by the police department, these two pieces in isolation are not enough to understand the emergent outcome that results from the interaction between these two organizations. The critical driver is the feedback loop that emerges because of the data flows back and forth between PredPol and the police department. Current policy proposals risk overlooking this class of emergent AI outcomes by narrowly focusing on the AI and data practices of just one organization, rather than explicitly drawing our attention to how data circulates in the wider data ecosystem.

What’s needed is a process-oriented, systemic policy approach focused not just on AI, but how data is interpreted and used in context by individuals and organizations on the ground, and how these parties interact with each other. The NTIA would be a good convener for drafting this framework given their success in leading a multi-stakeholder process to build a framework for enhancing cybersecurity. NTIA can use the AI Now Institute’s algorithmic impact assessment as a blueprint. By building a voluntary framework for AI outcomes, the NTIA can serve a dual purpose. First, it can help ease worries over how to stay compliant with best practices; Second, it can help organizations safeguard against unwanted outcomes of AI systems, and more effectively identify and correct problems that do arise instead of depending on outside forensic data analysis after the fact. NTIA can help establish a common language of AI systems between public and private entities that gives concrete steps organizations can take to avoid these outcomes.

]]> https://techliberation.com/2020/05/06/biased-ai-is-more-than-a-technical-problem-building-a-process-oriented-policy-approach-to-ai-governance/feed/ 0 76711 Is It “Techno-Chauvinist” & “Anti-Humanist” to Believe in the Transformative Potential of Technology? https://techliberation.com/2018/09/18/is-it-techno-chauvinist-anti-humanist-to-believe-in-the-transformative-potential-of-technology/ https://techliberation.com/2018/09/18/is-it-techno-chauvinist-anti-humanist-to-believe-in-the-transformative-potential-of-technology/#comments Tue, 18 Sep 2018 14:56:25 +0000 https://techliberation.com/?p=76379

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 :

]]> https://techliberation.com/2018/09/18/is-it-techno-chauvinist-anti-humanist-to-believe-in-the-transformative-potential-of-technology/feed/ 2 76379 Jordan Reimschisel on the Future of Advanced Medical Innovation & Its Regulation https://techliberation.com/2017/08/14/jordan-reimschisel-on-the-future-of-advanced-medical-innovation-its-regulation/ https://techliberation.com/2017/08/14/jordan-reimschisel-on-the-future-of-advanced-medical-innovation-its-regulation/#comments Mon, 14 Aug 2017 17:42:36 +0000 https://techliberation.com/?p=76174

My professional life is dedicated to researching the public policy implications of various emerging technologies. Of the many issues and sectors that I cover, none are more interesting or important than advanced medical innovation. After all, new health care technologies offer the greatest hope for improving human welfare and longevity. Consequently, the public policies that govern these technologies and sectors will have an important bearing on just how much life-enriching or life-saving medical innovation we actually get going forward.

Few people are doing better reporting on the intersection of advanced technology and medicine — as well as the effects of regulation on those fields — than my Mercatus Center colleague Jordan Reimschisel. In a very short period of time, Jordan has completely immersed himself in these complex, cutting-edge topics and produced a remarkable body of work discussing how, in his words, “technology can merge with medicine to democratize medical decision making, empower patients to participate in the treatment process, and promote better health outcomes for more patients at lower and lower costs.” He gets deep into the weeds of the various technologies he writes about as well as the legal, ethical, and economic issues surrounding each topic.

I encouraged him to start an ongoing compendium of his work on these topics so that we could continue to highlight his research, some of which I have been honored to co-author with him. I have listed his current catalog down below, but jump over to this Medium page he set up and bookmark it for future reference. This is some truly outstanding work and I am excited to see where he goes next with topics as wide-ranging as “biohackerspaces,” democratized or “personalized” medicine, advanced genetic testing and editing techniques, and the future of the FDA in an age of rapid change.

Give Jordan a follow on Twitter (@jtreimschisel) and make sure to follow his Medium page for his dispatches from the front lines of the debate over advanced medical innovation and its regulation.

Artificial Intelligence

“Artificial Intelligence Advances”

“That AI You Hate, You Really Love” Co-written with Adam Thierer

“That Robot Saved My Life”

Biohackerspaces

“Biohackerspaces”

“Safe Enough”

Food and Drug Administration

“FDA Needs a Fresh Approach, and Fast” Co-written with Adam Thierer

“Insurance costs just the tip of the iceberg. Time to reform the FDA.” Co-written with Dr. Robert Graboyes

“Opening the Door for Medical Innovation” Co-written with Dr. Robert Graboyes

“The True Goal of the FDA Should Be Drug Innovation”

“Toward Patient-Centered Policy”

“When it comes to tobacco and cigarettes, people are smarter than you think”

Genetics

“Will Genetic Editing Advance Faster Than Our Ability to Regulate It?” Co-written with Adam Thierer

Personalized Medicine

“The Creative Destruction of Medicine: A Book Review”

“Technology Could Enable Personal Medicine Whether We Like It Or Not”

]]> https://techliberation.com/2017/08/14/jordan-reimschisel-on-the-future-of-advanced-medical-innovation-its-regulation/feed/ 1 76174 Are “Permissionless Innovation” and “Responsible Innovation” Compatible? https://techliberation.com/2017/07/12/are-permissionless-innovation-and-responsible-innovation-compatible/ https://techliberation.com/2017/07/12/are-permissionless-innovation-and-responsible-innovation-compatible/#respond Wed, 12 Jul 2017 18:28:55 +0000 https://techliberation.com/?p=76164

“Responsible research and innovation,” or “RRI,” has become a major theme in academic writing and conferences about the governance of emerging technologies. RRI might be considered just another variant of corporate social responsibility (CSR), and it indeed borrows from that heritage. What makes RRI unique, however, is that it is more squarely focused on mitigating the potential risks that could be associated with various technologies or technological processes. RRI is particularly concerned with “baking-in” certain values and design choices into the product lifecycle before new technologies are released into the wild.

In this essay, I want to consider how RRI lines up with the opposing technological governance regimes of “permissionless innovation” and the “precautionary principle.” More specifically, I want to address the question of whether “permissionless innovation” and “responsible innovation” are even compatible. While participating in recent university seminars and other tech policy events, I have encountered a certain degree of skepticism—and sometimes outright hostility—after suggesting that, properly understood, “permissionless innovation” and “responsible innovation” are not warring concepts and that RRI can co-exist peacefully with a legal regime that adopts permissionless innovation as its general tech policy default. Indeed, the application of RRI lessons and recommendations can strengthen the case for adopting a more “permissionless” approach to innovation policy in the United States and elsewhere.

Definitional Ambiguities, Part 1: “Governance”

Before we can have a constructive conversation about these issues, however, we need to agree upon how narrowly or broadly we are defining some relevant terms, beginning with the word “governance.” When some hear the term “governance” their first reaction might be to think “government,” and formal legal and regulatory processes in particular. That is certainly one form of governance, but it is hardly the only one.

We often speak of the “governance” of corporations, schools, churches, other institutions, and even households. When we do, we usually do not mean government administration of these things; we are instead thinking of some other, more amorphous form of governance by a variety of individuals or groups. The “governance” of a company, for example, includes the interaction of shareholders, board members, corporate officials, workers, and so on. The “governance” of a church might involve clergy, the congregation, and sacred scriptures or traditions.  Household “governance” comes down to decisions made by parents and caretakers. And so on.

Thus, “governance” can certainly have the narrow connotation of being associated with formal regulatory enactments by governments, but it can also describe a much broader universe of norms and rules that are established and enforced by a wide variety of people (or groups of people) in a wide variety of ways.

When we consider questions of technological governance—and specifically the notion of “anticipatory governance,” which is prominent feature of RRI discussions—it helps to specify whether we are speaking of governance in a broad or narrow sense. Whether it is done consciously or not, in much of the literature, RRI scholars and advocates fail to make it clear what type of “governance” they are thinking of when proposing new forms of anticipatory technological governance.

Definitional Ambiguities, Part 2: “Precautionary Principle” & “Permissionless Innovation”

These distinctions are particularly important when we compare and contrast the “precautionary principle” and “permissionless innovation.” These concepts are most useful when viewed as governance dispositions or policy postures and they are usually—although not always—used in the narrow “governance” sense to describe one’s perspective on where legal and regulatory defaults should be set.

Even when applied narrowly, however, both terms are open to interpretation as applied in various policy contexts. For example, precaution could mean an outright prohibition on an innovative activity until such time as it had been proven safe (this is the way many FDA or FAA regulations work). But precaution might be imposed through somewhat less restrictive approaches, such as a set of government-established safety standards buttressed by a recall regime (think NHTSA or CPSC). Even less restrictive but still precautionary in orientation would be a mandatory labeling law or a government-led risk reduction educational campaign. In other words, there are probably as many flavors of the precautionary principle as there are flavors of ice cream.

For the longest time, both proponents and critics of the precautionary principle have failed to put a name on its opposing worldview or governance disposition. I have argued that, despite its uncertain origin and imprecise meaning, “permissionless innovation” provides a useful name for the antithesis of the precautionary principle.

As I noted in a recent speech at an Arizona State University law school conference on technological governance, critics of permissionless innovation sometimes like to imply that it is synonymous with anarchy. (In fact, a few people at that event leveled that accusation at me.) But I’ve written an entire book on this notion and surveyed countless essays and articles that cite the term, and I have never once seen any advocate of permissionless innovation going to such an extreme. In fact, those advocates often don’t even bother calling for the abolition of any laws, programs, or agencies. As I noted in my ASU talk, “most of those defenders of permissionless innovation are using the term as a sort of shorthand when what they really mean to say is something like: ‘give innovators a bit more breathing room,’ or, ‘don’t rush to regulate.’”

And so, as a policy posture, permissionless innovation really comes down to a preference for setting public policy defaults closer to green lights rather than red ones. In my own book on the subject, I defined the term as follows:

“Permissionless innovation refers to the notion that experimentation with new technologies and business models should generally be permitted by default. Unless a compelling case can be made that a new invention will bring serious harm to society, innovation should be allowed to continue unabated and problems, if any develop, can be addressed later.”

By contrast, the precautionary principle posture generally recommends keeping the light red until innovators can prove their new products and services are “safe,” however that is defined. But there are many points along the spectrum between these two policy postures. And if we can accept the idea that the “precautionary principle” and “permissionless innovation” act more as general governance dispositions instead of fixed and rigid edicts, then it is also easier to imagine how both of those dispositions can incorporate “responsible innovation” notions into their governance visions.

Definitional Ambiguities, Part 3: “Responsible Innovation”

But what exactly constitutes “responsible innovation”? Definitions of responsible research and innovation are still evolving, but a leading article on the subject by René von Schomberg from 2011 argues that it can be defined as:

“A transparent, interactive process by which societal actors and innovators become mutually responsive to each other with a view to the (ethical) acceptability, sustainability and societal desirability of the innovation process and its marketable products (in order to allow a proper embedding of scientific and technological advances in our society).”

A more streamlined definition was offered by Jack Stigloe, Richard Owen, and Phil Macnaghten in a 2013 article: “Responsible innovation means taking care of the future through collective stewardship of science and innovation in the present.” They also proposed four dimensions of responsible innovation—anticipation, reflexivity, inclusion and responsiveness—which they say “provide a framework for raising, discussing and responding to such questions.”

RRI Tools, a European consortium focused on promoting responsible innovation strategies, identifies the six core goals of RRI as: open access, gender equality in science, ethics, science education, governance, and public engagement. Other groups and individuals promoting RRI focus on privacy, safety, and security as crucial values that they hope to work into more product development processes early on.

As with “corporate social responsibility” before it, “responsible innovation” will remain a term that is open to varying interpretations and which can incorporate many distinct values that are context-dependent. What Milton Friedman said of CSR discussions in 1970—that they “are notable for their analytical looseness and lack of rigor”—continues to be somewhat true for both CSR and RRI circa 2017. Nonetheless, what both concepts hold in common is the belief that, whatever those “responsible” values are, they can be “baked in” to corporate decision-making and product design processes in an anticipatory fashion.

And while not everyone will agree on the contours of these concepts, practically speaking, I think we can expect both the CSR and RRI movement will continue to grow in coming years. That will be the case not only because of the pressures applied by various activists, stakeholders, and governments, but also because many companies and their consumers will demand more than just better products and greater profitability.

But Doesn’t RRI Necessitate the Precautionary Principle as a Policy Prerequisite?

But how precisely should RRI notions and recommendations influence policy deliberations over the future course of technological governance in the narrow sense of the term (i.e., more legalistic sense)? Here’s where things get more interesting.

The problem is that many of the advocates of RRI are seemingly more sympathetic to precautionary policy regimes and skeptical of the wisdom of permissionless innovation as a policy default. This is not always well-articulated in their writing. Instead, it is the attitude seemingly on display when I speak with RRI advocates or hear them deliver speeches.  Yet, most of these advocates just won’t ever let you nail them down on the point.

Some RRI advocates do come close to making that connection. In his seminal article, Rene von Schomberg argues that RRI, “can reduce the human cost of trial and error and make advantage of a societal learning process of stakeholders and technical innovators. It creates a possibility for anticipatory governance,” he says. “This should ultimately lead to products which are (more) societal robust.”

He then briefly raises the possibility of RRI informing the application of the precautionary principle in public policy debates:

“The precautionary principle works as an incentive to make safe and sustainable products and allow governmental bodies to intervene with Risk Management decisions (such as temporary licensing, case by case decision making etc) whenever necessary in order to avoid negative impacts.”

Yet, von Schomberg never really spells out the exact relationship between RRI and the precautionary principle as a matter of public policy .

Another leading article on the meaning of RRI by Grace Eden, Marina Jirotka, and Bernd Stahl, says that, “The RRI focus is more on mitigating wider societal long-term risks and so favors incremental rather than radical innovation.” That seems to suggest a closer connection between RRI and a formal application of the precautionary principle in policy deliberations about emerging technologies. They also speak of the “two very different approaches to problem solving (anticipatory vs. evidence-based),” which I have argued gets to the heart of the divergence between the precautionary principle and permissionless innovation policy paradigms. Yet, these authors do not dwell on this connection at length, and most of the rest of their article is focused on the ways in which RRI can (and already does) infuse product and service development processes outside of the realm of public policy.

In a 2015 Brookings Institution white paper about RRI, Walter D. Valdivia and David H. Guston offer a more concrete answer to this question when they insist that responsible innovation “is not a doctrine of regulation and much less an instantiation of the precautionary principle; the actions it recommends do not seek to slow down innovation because they do not constrain the set of options for researchers and businesses, they expand it.” They continue on to note that:

“[responsible innovation] considers innovation inherent to democratic life and recognizes the role of innovation in the social order and prosperity. It also recognizes that at any point in time, innovation and society can evolve down several paths and the path forward is to some extent open to collective choice. What RI pursues is a governance of innovation where that choice is more consonant with democratic principles.”

Here, finally, we have a better demarcation between the general notion of RRI and the formal application of the precautionary principle. But is that line really so bright? Do other RRI scholars agree with Valdivia and Guston about this separation between the “responsible innovation” movement and the formal application of the precautionary principle in the policy realm? And, finally, what is meant by “democratic life” and “democratic principles” in this context?

I suspect that many RRI advocates would read that last line from Valdivia and Guston above (“What RI pursues is a governance of innovation where that choice is more consonant with democratic principles.”) and suggest that it favors an embrace of the precautionary principle as the default position in emerging technology policy discussions. But, again, that remains open to debate because so much of the RRI literature lacks precision regarding the connection between these concepts.

How RRI Can be Compatible with Both Visions

Regardless, I would like to suggest that parties on both sides of this debate would be wise to divorce the concept of responsible innovation from their priors regarding optimal regulatory policy toward emerging technology. Properly understood, “responsible innovation” could be a feature of the “precautionary” vision, but it could also be compatible with the “permissionless” governance vision and resulting policy regimes. To reach that understanding, both sides will need to be open to learning from the other and willing to take their concerns seriously.

Advocates of RRI should understand that, just as CSR can do a great deal of good even in the absence of formal regulatory action, the same can be true of RRI, even in a policy regime in which permissionless innovation is the general default.

If, however, the first instinct among the RRI community is to consider advocates of permissionless innovation nothing more than a bunch of uncaring anarchists, they relinquish the opportunity to work with diverse parties to instill wise guidelines into technological development processes. This would be particularly misguided in an age when the so-called “Pacing Problem”—i.e., the growing gap between the introduction of new technologies and time it takes laws and regulations to adjust or be formulated in response—has become an ever-accelerating reality, making traditional “hard law” regulatory enactment increasingly difficult. If the RRI community wants to get any of the values that they care about incorporated into technological development processes, then they will need to be open to the idea that perhaps the only way to do so will be through less formal procedures precisely because law will likely lag so far behind marketplace developments.

Likewise, if the first instinct among the permissionless innovation advocates is to regard the RRI movement as little more than repackaged Ludditism, hell-bent on derailing all the great inventions of the future, then they are foolishly forgoing the chance to work with a diverse group of well-intentioned scholars and stakeholders who could ensure that new products and services gain more widespread acceptance and public trust. More practically, permissionless innovation advocates would be wise to accept the fact that, although technological innovation is generally outpacing the ability of government to keep up, that doesn’t mean most of the traditional regulatory regimes or agencies are going away any time soon. After all, can you name a technocratic law or regulatory body that has been liberalized or eliminated in recent memory? RRI offers a chance to forge a rough peace with agencies and officials who often just want to have a small say in how innovative processes are unfolding. Of course, if regulators seek to have a BIG say in those matters, then policy fights will no doubt ensue. But in my experience, this is less often the case than some defenders of permissionless innovation suggest.

Thus, advocates of permissionless innovation should understand that RRI is not synonymous with a formal precautionary principle-focused policy prescription and that “anticipatory governance” can mean something more generic and beneficial, so long as it does not come to mean the formal application of the precautionary principle as the public policy default.

We Are Already Going Down This Path

Perhaps I am being naïve to think this sort of common ground might exist. But the funny thing is that I know for a fact that it already does! RRI principles have been infusing various multistakeholder processes in the United States for many years now.

For example, here’s a paper I wrote back in 2009 about the various online safety task forces, blue ribbon commissions, and other collaborative efforts that were instilling “safety by design” principles into various online services and digital products. Meanwhile, “privacy by design” and “security by design” efforts are all the rage these days and a wide variety of best practices and codes of conduct have been established to make sure privacy and security values are baked-in to the product design process from the start.

Meanwhile, safety, security, and privacy best practices have increasingly been formulated by the U.S. Department of Commerce (the National Telecommunications and Information Administration in particular), the Federal Trade Commission, FDA, FCC, and the White House Office of Science and Technology Policy. These multistakeholder efforts and agency best practice reports have contained assorted “responsible innovation” principles for technologies as wide-ranging as: big data, artificial intelligence, the Internet of Things, facial recognition, online advertising, mobile phone privacy, mobile apps for kids, driverless cars, commercial drones, genetic testing, medical advertising on social media, 3D printed medical devices, medical device cybersecurity, nanotech, and much more. (I have a forthcoming paper in the works with Ryan Hagemann of the Niskanen Center in which we attempt to document many of these new “soft law” technological governance efforts. There have been so many of these efforts – many of which are still underway – that we are having a hard time cataloging them all!)

I am utterly perplexed why more RRI scholarship has not identified the many ways in which the principles they advocate already infuse multistakeholder processes such as these. Perhaps it is because those scholars feel that some of these multistakeholder processes fail to address the full range of issues or values that they feel are in play. But if you examine recent reports from these agencies and government bodies, I think you will come away quite impressed by the breadth of issues and concerns that they cover. Likewise, the values and best practices they discuss and/or recommend are exactly the sort of responsible innovation principles that the RRI movement cares about.

To some extent, therefore, RRI is already well-entrenched in the technology governance process, it’s just a bit messy. I think some RRI scholars probably fall prey to the old “Goldilocks myth” that we can get these principles just right with enough consideration and oversight. The reality on the ground is that instilling RRI values into the technological design process is a dynamic, iterative, and quite imprecise art.

In closing, there’s still more to the technological governance story that RRI advocates fail to incorporate into their work. To fully appreciate the many ways technological processes are constrained and corrected, they must take into account other governance forces and factors, including the role of:

  • social norms and reputational effects (especially the growing importance of reputational feedback mechanisms);
  • third-party accreditation and standards-setting bodies;
  • courts and common law (including legal solutions like product liability, negligence, design defects law, failure to warn, breach of warranty, and other assorted torts and class action claims);
  • insurance markets as risk calibrators and correctional mechanisms;
  • federal and state consumer protection agencies (such as the FTC), which police “unfair and deceptive practices” and other harms; and
  • media, academic institutions, non-profit advocacy groups, and the general public more generally, all of which can put pressure on technology developers.

Only by taking into account the full range of players and activities at work can we develop a more robust understanding of how technology is actually “governed” in our modern world. I suspect that many in the RRI community of scholars do appreciate these other factors, even though they don’t always account for all of them in their writing and advocacy. Then again, many of those advocates would perhaps decry the more remedial, ex post nature of these governance tools and insist that more ex ante anticipatory planning must be at the heart of technological design and development processes.

In reality, a mix of these two approaches is already at work today and will likely continue to dominate the governance process well into the future. So long as the anticipatory efforts don’t become formal regulatory proposals, there is no reason that this mix of “responsible innovation” governance tools and methods can’t be embraced by a diverse array of scholars and innovators.

Further Reading:

]]> https://techliberation.com/2017/07/12/are-permissionless-innovation-and-responsible-innovation-compatible/feed/ 0 76164 Permissionless Innovation: Book, Video, Slides, Podcast, Paper & More! https://techliberation.com/2016/04/19/permissionless-innovation-book-video-slides-podcast-paper-more/ https://techliberation.com/2016/04/19/permissionless-innovation-book-video-slides-podcast-paper-more/#comments Tue, 19 Apr 2016 14:25:09 +0000 https://techliberation.com/?p=76012

Permissionless Innovation 2nd edition book cover -1
I am pleased to announce the release of the second edition of my book, Permissionless Innovation: The Continuing Case for Comprehensive Technological Freedom. As with the first edition, the book represents a short manifesto that condenses — and attempts to make more accessible — arguments that I have developed in various law review articles, working papers, and blog posts over the past few years. The book attempts to accomplish two major goals.

First, I attempt to show how the central fault line in almost all modern technology policy debates revolves around “the permission question,” which asks: Must the creators of new technologies seek the blessing of public officials before they develop and deploy their innovations? How that question is answered depends on the disposition one adopts toward new inventions. Two conflicting attitudes are evident.

One disposition is known as the “precautionary principle.” Generally speaking, it refers to the belief that new innovations should be curtailed or disallowed until their developers can prove that they will not cause any harms to individuals, groups, specific entities, cultural norms, or various existing laws, norms, or traditions.

The other vision can be labeled “permissionless innovation.” It refers to the notion that experimentation with new technologies and business models should generally be permitted by default. Unless a compelling case can be made that a new invention will bring serious harm to society, innovation should be allowed to continue unabated and problems, if they develop at all, can be addressed later.

I argue that we are witnessing a grand clash of visions between these two mindsets today in almost all major technology policy discussions today.

The second major objective of the book, as is made clear by the title, is to make a forceful case in favor of the latter disposition of “permissionless innovation.” I argue that policymakers should unapologetically embrace and defend the permissionless innovation ethos — not just for the Internet but also for all new classes of networked technologies and platforms. Some of the specific case studies discussed in the book include: the “Internet of Things” and wearable technologies, smart cars and autonomous vehicles, commercial drones, 3D printing, and various other new technologies that are just now emerging.

I explain how precautionary principle thinking is increasingly creeping into policy discussions about these technologies. The urge to regulate preemptively in these sectors is driven by a variety of safety, security, and privacy concerns, which are discussed throughout the book. Many of these concerns are valid and deserve serious consideration. However, I argue that if precautionary-minded regulatory solutions are adopted in a preemptive attempt to head-off these concerns, the consequences will be profoundly deleterious.

Mye central thesis is this: Living in constant fear of hypothetical worst-case scenarios — and premising public policy upon them — means that best-case scenarios will never come about. When public policy is shaped by precautionary principle reasoning, it poses a serious threat to technological progress, economic entrepreneurialism, social adaptation, and long-run prosperity.

Again, that doesn’t mean we should ignore the various problems created by these highly disruptive technologies. But how we address these concerns matters greatly. If and when problems develop, there are many less burdensome ways to address them than through preemptive technological controls. The best solutions to complex social problems are almost always organic and “bottom-up” in nature. Luckily, there exists a wide variety of constructive approaches that can be tapped to address or alleviate concerns associated with new innovations. These include:

  • education and empowerment efforts (including media literacy, digital citizenship efforts);
  • social pressure from activists, academics, and the press and the public more generally.
  • voluntary self-regulation and adoption of best practices (including privacy and security “by design” efforts); and,
  • increased transparency and awareness-building efforts to enhance consumer knowledge about how new technologies work.

Such solutions are almost always superior to top-down, command-and-control regulatory edits and bureaucratic schemes of a “Mother, May I?” (i.e., permissioned) nature. The problem with “top-down” traditional regulatory systems is that they often tend to be overly-rigid, bureaucratic, inflexible, and slow to adapt to new realities. They focus on preemptive remedies that aim to predict the future, and future hypothetical problems that may not ever come about. Worse yet, administrative regulation generally preempts or prohibits the beneficial experiments that yield new and better ways of doing things. It raises the cost of starting or running a business or non-business venture, and generally discourages activities that benefit society.

To the extent that other public policies are needed to guide technological developments, simple legal principles are greatly preferable to technology-specific, micro-managed regulatory regimes. Again, ex ante (preemptive and precautionary) regulation is often highly inefficient, even dangerous. To the extent that any corrective legal action is needed to address harms, ex post measures, especially via the common law (torts, class actions, etc.), are typically superior. And the Federal Trade Commission will, of course, continue to play a backstop here by utilizing the broad consumer protection powers it possesses under Section 5 of the Federal Trade Commission Act, which prohibits “unfair or deceptive acts or practices in or affecting commerce.” In recent years, the FTC has already brought and settled many cases involving its Section 5 authority to address identity theft and data security matters. If still more is needed, enhanced disclosure and transparency requirements would certainly be superior to outright bans on new forms of experimentation or other forms of heavy-handed technological controls.

In the end, however, I argue that, to the maximum extent possible, our default position toward new forms of technological innovation must remain: “innovation allowed.” That is especially the case because, more often than not, citizens find ways to adapt to technological change by employing a variety of coping mechanisms, new norms, or other creative fixes. We should have a little more faith in the ability of humanity to adapt to the challenges new innovations create for our culture and economy. We have done it countless times before. We are creative, resilient creatures. That’s why I remain so optimistic about our collective ability to confront the challenges posed by these new technologies and prosper in the process.

If you’re interested in taking a look, you can find a free PDF of the book at the Mercatus Center website or you can find out how to order it from there as an eBook. Hardcopies are also available.

The Mercatus Center also recently hosted a book launch party for the release of the 2nd edition. The event was very well-attended and many of those present asked me to forward along specific slides or the entire deck. So, for those who asked, or others who may be interested in seeing the slides, here ya go!

And here’s the video from the event, which also incorporates these slides:

Also, back in September 2015, Sonal Chokshi was kind enough to invite me on the a16z podcast and we discussed, “Making the Case for Permissionless Innovation.” You can listen to that conversation here:

Finally, I put together a paper summarizing the major policy recommendations contained in the book. It’s entitled, “Permissionless Innovation and Public Policy: A 10-Point Blueprint.”  And then, along with Michael Wilt, I published condensed version of the paper as an essay over at  Medium. 

PI blueprint2.JPG

Materials mentioned in this post related to Permissionless Innovation project:

Related Essays:

Journal articles and book chapters:

Tech Policy Issue Matrix 2015

 

]]> https://techliberation.com/2016/04/19/permissionless-innovation-book-video-slides-podcast-paper-more/feed/ 1 76012 The Right to Try, 3D Printing, the Costs of Technological Control & the Future of the FDA https://techliberation.com/2015/08/10/the-right-to-try-3d-printing-the-costs-of-technological-control-the-future-of-the-fda/ https://techliberation.com/2015/08/10/the-right-to-try-3d-printing-the-costs-of-technological-control-the-future-of-the-fda/#comments Mon, 10 Aug 2015 13:28:37 +0000 http://techliberation.com/?p=75660

I’ve been thinking about the “right to try” movement a lot lately. It refers to the growing movement (especially at the state level here in the U.S.) to allow individuals to experiment with alternative medical treatments, therapies, and devices that are restricted or prohibited in some fashion (typically by the Food and Drug Administration). I think there are compelling ethical reasons for allowing citizens to determine their own course of treatment in terms of what they ingest into their bodies or what medical devices they use, especially when they are facing the possibility of death and have exhausted all other options.

But I also favor a more general “right to try” that allows citizens to make their own health decisions in other circumstances. Such a general freedom entails some risks, of course, but the better way to deal with those potential downsides is to educate citizens about the trade-offs associated with various treatments and devices, not to forbid them from seeking them out at all.

The Costs of Control

But this debate isn’t just about ethics. There’s also the question of the costs associated with regulatory control. Practically speaking, with each passing day it becomes harder and harder for governments to control unapproved medical devices, drugs, therapies, etc.  Correspondingly, that significantly raises the costs of enforcement and makes one wonder exactly how far the FDA or other regulators will go to stop or slow the advent of new technologies.

I have written about this “cost of control” problem in various law review articles as well as my little Permissionless Innovation book and pointed out that, when enforcement challenges and costs reach a certain threshold, the case for preemptive control grows far weaker simply because of (1) the massive resources that regulators would have to pour into the task on crafting a workable enforcement regime; and/or (2) the massive loss of liberty it would entail for society more generally to devise such solutions. With the rise of the Internet of Things, wearable devices, mobile medical apps, and other networked health and fitness technologies, these issues are going to become increasingly ripe for academic and policy consideration.

A Hypothetical Regulatory Scenario

Here’s an interesting case study to consider in this regard:  Can  3D printing  of prosthetics be controlled? Clearly prosthetics are medical devices in the traditional regulatory sense, but few people are going to the FDA and asking for permission or a “right to try” new 3D-printed limbs. They’re just doing it. And the results have been incredibly exciting, as my Mercatus Center colleague Robert Graboyes has noted.

But let’s imagine what the regulators might do if they really wanted to impose their will and limit the right to try in this context:

  • Could government officials ban 3D printers outright? I don’t see how. The technology is already too diffuse and is utilized for so many alternative (and uncontroversial) uses that it doesn’t seem likely such a control regime would work or be acceptable. And if any government did take this extreme step, “global innovation arbitrage” would kick in. That is, innovators would just move offshore.
  • Could government officials ban the inputs used by 3D printers? Again, I don’t see how. After all, we are primarily talking about plastics and glue here!
  • Could government officials ban 3D printer blueprints? Two problems with that. First, such blueprints are a form of free speech and government efforts to censor them would represent a form of prior restraint that would violate the First Amendment of the U.S. Constitution. Second, even ignoring the First Amendment issues, information control is just damned hard and I don’t see how you could suppress such blueprints effectively when are they are freely available across the Internet. Or, people would just “torrent” them, as they do (illegally) with copyrighted files today.
  • Could government officials ban and/or fine specific companies (especially those with deep pockets)? Perhaps, but that is likely a losing strategy since 3D printing is already so highly decentralized and is done by average citizens in the comfort of their own home (and often for no monetary gain). So, attempting to go after a handful of corporate players and “make an example out of them” to deter others from experimenting isn’t likely to work. And, again, it’ll just lead to more offshoring and undergrounding of these devices and innovative activities.
  • Could government officials ban the sale of certain 3D printing applications? They could try, but enterprising minds would likely start using alternative payment methods (like Bitcoin) to conduct their deals. But the question of payments is largely irrelevant in many fields because much of this activity is non-commercial and open-source in character. People are freely distributing blueprints for 3D-printed prosthetics, for example, and they are even giving away the actual 3D-printed prosthetic devices to those who need them.
  • Could government officials just create a licensing / approval regime for narrowly-targeted 3D printed medical devices? Of course, but for all the reasons outlined above, it would likely be pretty easy to evade such a regime. Moreover, the very effort to enforce such a licensing regime would likely deter many beneficial innovations in the process, while also leading to the old cronyist problems associated with firms engaging in rent-seeking and courting favor with regulators in order to survive or prosper.

Anyway, you get the point: The practicality of control makes a difference and at some point the enormous costs associated with enforcement become an ethical matter in its own right. Stated differently, it’s not just that citizens should generally be at liberty to determine their own treatments and decide what drugs they ingest and what medical devices they use, it’s also the case that regulatory efforts aimed at limiting that right have so many corresponding enforcement costs that can spillover on to society more generally. And that’s an ethical matter of a different sort when you get right down to it. But, at a minimum, it’s an increasingly costly strategy and the costs associated with such technological control regimes should be considered closely and quantified where possible.

The Need for a Shift toward Risk Education

Let’s return to the question I raised above regarding the educational role that the FDA, or governments more generally, could play in the future. As I noted, a world in which citizens are granted the liberty to make more of their own health decisions is a world in which they could, at times, be rolling the dice with their health and lives. The highly paternalistic approach of modern food and drug regulation is rooted in the belief that citizens simply cannot be trusted to make such decisions on their own because they will never be able to appreciate the relative risks. You might be surprised to hear that I am somewhat sympathetic to that argument. People can and do make rash and unwise decisions about their health based on misinformation or a general lack of quality information presented in an easy-to-understand fashion. As a result, policymakers have taken the right to make these decisions away from us in many circumstances.

Although motivated by the best of intentions, paternalistic controls are not the optimal way to address these concerns. The better approach is rooted in risk education. To reiterate, the wise way to deal with the potential downsides associated with freedom of choice is to educate citizens about the relative risks associated with various medical treatments and devices, not to forbid them from seeking them out at all.

What does that mean for the future of the FDA? If the agency was smart, it would recognize that traditional command-and-control regulation is no longer a sensible strategy; it’s increasingly unworkable and imposes too many other costs on innovators and personal liberty. Thus, the agency needs to reorient its focus toward becoming a risk educator. Their goal should be to help create a more fully-informed citizenry that is empowered with more and better information about relative risk trade-offs.

Overcoming the Opposition & Getting Consent Mechanisms Right

Such an approach (i.e., shifting the FDA’s mission from being primarily a risk regulator to becoming a risk educator) will encounter opposition from strident defenders and opponents of the FDA alike.

The defenders of the FDA and its traditional approach will continue to insist that people can  never be trusted to make such decisions on their own, regardless of how much information they have at their disposal or how many warnings we might give them. The problem with that position is that it treats citizens like ignorant sheep and denies them the most basic of all human rights: The right to live a life of your own choosing and to make the ultimate determinations about your own health and welfare. And, again, blindly defending the old system isn’t wise because traditional command-and-control regulatory methods are increasingly impractical and incredibly costly to enforce.

Opponents of the FDA, by contrast, will insist that the agency can’t even be trusted to provide us with good information for us to make these decisions on our own. Additionally, critics will likely argue that the agency might give us the wrong information or try to “nudge” us in certain directions. I share some of those concerns, but I am willing to live with that possibility so long as we are moving toward a world in which that is the only real power that the FDA possess over me and my fellow citizens. Because if all the agency is doing is providing us with information about risk trade-offs, then at least we still remain free to seek out alternative information from other experts and then choose our own courses of action.

The tricky issue here is getting consent mechanisms right. In fact, it’s the lynchpin of the new regime I am suggesting. In other words, even if we could agree that a more fully-informed citizenry should be left free to make these decisions on their own, we need to make sure that those individuals have provided clear and informed consent to the parties they might need to contract with when seeking alternative treatments. That’s particularly essential in a litigious society like America, where the threat of liability always looms large over doctors, nurses, hospital, insurers, and medical innovators. Those parties will only be willing to go along with an expanded “right to try” regime if they can be assured they won’t be held to blame when citizens make controversial choices that they advised them against, or at least clearly laid out all the potential risks and other alternatives at their disposal. This will require not only an evolution of statutory law and regulatory standards, but also of the common law and insurance norms.

Once we get all that figured out—and it will, no doubt, take some time—we’ll be on our way to a better world where the idea of having a “right to try” is the norm instead of the exception.

(My thanks to Adam Marcus for commenting on a draft of this essay. For more general background on 3D printing, see his excellent 2011 primer here, “3D Printing: The Future is Here.”)

]]> https://techliberation.com/2015/08/10/the-right-to-try-3d-printing-the-costs-of-technological-control-the-future-of-the-fda/feed/ 3 75660 The Challenge of Defining Privacy Harm https://techliberation.com/2015/06/19/the-challenge-of-defining-privacy-harm/ https://techliberation.com/2015/06/19/the-challenge-of-defining-privacy-harm/#respond Fri, 19 Jun 2015 18:12:30 +0000 http://techliberation.com/?p=75593

On Thursday, it was my great pleasure to participate in a Washington Legal Foundation (WLF) event on “Online Privacy Regulation: The Challenge of Defining Harm.” The entire event video can be found on YouTube here, but down below I pasted the clip of just my remarks. Other speakers at the event included:  FTC Commissioner Maureen K. Ohlhausen, Commissioner; John B. Morris, Jr., the Associate Administrator and Director of Internet Policy athe U.S. Department of Commerce’s National Telecommunications and Information Administration; and Katherine Armstrong, Counsel at the law firm of Hogan Lovells. Glenn Lammi of the WLF moderated the session.

My remarks drew upon a few recent law review articles I have published relating digital privacy debates to previous debates over free speech and online child safety issues. (Here are those articles: 1, 2, 3).

]]> https://techliberation.com/2015/06/19/the-challenge-of-defining-privacy-harm/feed/ 0 75593 Making Sure the “Trolley Problem” Doesn’t Derail Life-Saving Innovation https://techliberation.com/2015/01/13/making-sure-the-trolley-problem-doesnt-derail-life-saving-innovation/ https://techliberation.com/2015/01/13/making-sure-the-trolley-problem-doesnt-derail-life-saving-innovation/#comments Tue, 13 Jan 2015 18:07:16 +0000 http://techliberation.com/?p=75238

I want to highlight an important new blog post (“Slow Down That Runaway Ethical Trolley“) on the ethical trade-offs at work with autonomous vehicle systems by Bryant Walker Smith, a leading expert on these issues. Writing over at Stanford University’s Center for Internet and Society blog, Smith notes that, while serious ethical dilemmas will always be present with such technologies, “we should not allow the perfect to be the enemy of the good.” He notes that many ethical philosophers, legal theorists, and media pundits have recently been actively debating variations of the classic “Trolley Problem,” and its ramifications for the development of autonomous or semi-autonomous systems. (Here’s some quick background on the Trolley Problem, a thought experiment involving the choices made during various no-win accident scenarios.) Commenting on the increased prevalence of the Trolley Problem in these debates, Smith observes that:

Unfortunately, the reality that automated vehicles will eventually kill people has morphed into the illusion that a paramount challenge for or to these vehicles is deciding who precisely to kill in any given crash. This was probably not the intent of the thoughtful proponents of this thought experiment, but it seems to be the result. Late last year, I was asked the “who to kill” question more than any other — by journalists, regulators, and academics. An influential working group to which I belong even (briefly) identified the trolley problem as one of the most significant barriers to fully automated motor vehicles. Although dilemma situations are relevant to the field, they have been overhyped in comparison to other issues implicated by vehicle automation. The fundamental ethical question, in my opinion, is this: In the United States alone, tens of thousands of people die in motor vehicle crashes every year, and many more are injured. Automated vehicles have great potential to one day reduce this toll, but the path to this point will involve mistakes and crashes and fatalities. Given this stark choice, what is the proper balance between caution and urgency in bringing these systems to the market? How safe is safe enough?

That’s a great question and one that Ryan Hagemann and put some thought into as part of our recent Mercatus Center working paper, “Removing Roadblocks to Intelligent Vehicles and Driverless Cars.” That paper, which has been accepted for publication in a forthcoming edition of the Wake Forest Journal of Law & Policy, outlines the many benefits of autonomous or semi-autonomous systems and discusses the potential cost of delaying their widespread adoption. When it comes to “Trolley Problem”-like ethical questions, Hagemann and I argue that, “these ethical considerations need to be evaluated against the backdrop of the current state of affairs, in which tens of thousands of people die each year in auto-related accidents due to human error.” We continue on later in the paper:

Autonomous vehicles are unlikely to create 100 percent safe, crash-free roadways, but if they significantly decrease the number of people killed or injured as a result of human error, then we can comfortably suggest that the implications of the technology, as a whole, are a boon to society. The ethical underpinnings of what makes for good software design and computer-generated responses are a difficult and philosophically robust space for discussion. Given the abstract nature of the intersection of ethics and robotics, a more detailed consideration and analysis of this space must be left for future research. Important work is currently being done on this subject. But those ethical considerations must not derail ongoing experimentation with intelligent-vehicle technology, which could save many lives and have many other benefits, as already noted. Only through ongoing experimentation and feedback mechanisms can we expect to see constant improvement in how autonomous vehicles respond in these situations to further minimize the potential for accidents and harms. (p. 42-3)

None of this should be read to suggest that the ethical issues being raised by some philosophers or other pundits are unimportant. To the contrary, they are raising legitimate concerns about how ethics are “baked-in” to the algorithms that control autonomous or semi-autonomous systems. It is vital we continue to debate the wisdom of the choices made by the companies and programmers behind those technologies and consider better ways to inform and improve their judgments about how to ‘optimize the sub-optimal,’ so to speak. After all, when you are making decisions about how to minimize the potential for harm — including the loss of life — there are many thorny issues that must be considered and all of them will have downsides. Smith considers a few when he notes:

Automation does not mean an end to uncertainty. How is an automated vehicle (or its designers or users) to immediately know what another driver will do? How is it to precisely ascertain the number or condition of passengers in adjacent vehicles? How is it to accurately predict the harm that will follow from a particular course of action? Even if specific ethical choices are made prospectively, this continuing uncertainty could frustrate their implementation.

Again, these are all valid questions deserving serious exploration, but we’re not having this discussion in a vacuum. Ivory Tower debates cannot be divorced from real-world realities. Although road safety has been improving for many years, people are still dying at a staggering rate due to vehicle-related accidents. Specifically, in 2012, there were 33,561 total traffic fatalities (92 per day) and 2,362,000 people injured (6,454 per day) in over 5,615,000 reported crashes. And, to reiterate, the bulk of those accidents were due to human error.

That is a staggering toll and anything we can do to reduce it significantly is something we need to be pursuing with great vigor, even while we continue to sort through some of those challenging ethical issues associated with automated systems and algorithms. Smith argues, correctly in my opinion, that “a more practical approach in emergency situations may be to weight general rules of behavior: decelerate, avoid humans, avoid obstacles as they arise, stay in the lane, and so forth. … [T]his simplified approach would accept some failures in order to expedite and entrench what could be automation’s larger successes. As Voltaire reminds us, we should not allow the perfect to be the enemy of the good.”

Quite right. Indeed, the next time someone poses an an ethical thought experiment along the lines of the Trolley Problem, do what I do and reverse the equation. Ask them about the ethics of slowing down the introduction of a technology into our society that would result in a (potentially significant) lowering of the nearly 100 deaths and over 6,000 injuries that occur because of vehicle-related fatalities each day in the United States. Because that’s no hypothetical thought experiment; that’s the world we live in right now.

(P.S. The late, great political scientist Aaron Wildavsky crafted a framework for considering these complex issues in his brilliant 1988 book, Searching for Safety. No book has had a more significant influence on my thinking about these and other “risk trade-off” issues since I first read it 25 years ago. I cannot recommend it highly enough. I discussed Wildavsky’s framework and vision in my recent little book on “Permissionless Innovation.” Readers might also be interested in my August 2013 essay, “On the Line between Technology Ethics vs. Technology Policy,” which featured an exchange with ethical philosopher Patrick Lin, co-editor of an excellent collection of essays on Robot Ethics: The Ethical and Social Implications of Robotics. You should add that book to your shelf if you are interested in these issues.

 

]]> https://techliberation.com/2015/01/13/making-sure-the-trolley-problem-doesnt-derail-life-saving-innovation/feed/ 2 75238 Is Privacy an Unalienable Right? The Problem with Privacy Paternalism https://techliberation.com/2014/01/27/is-privacy-an-unalienable-right-the-problem-with-privacy-paternalism/ https://techliberation.com/2014/01/27/is-privacy-an-unalienable-right-the-problem-with-privacy-paternalism/#comments Mon, 27 Jan 2014 21:16:37 +0000 http://techliberation.com/?p=74147

Last week, it was my great pleasure to be invited on NPR’s “On Point with Tom Ashbrook,” to debate Jeffrey Rosen, a leading privacy scholar and the president and chief executive of the National Constitution Center. In an editorial in the previous Sunday’s New York Times (“Madison’s Privacy Blind Spot”), Rosen proposed “constitutional amendment to prohibit unreasonable searches and seizures of our persons and electronic effects, whether by the government or by private corporations like Google and AT&T.” He said his proposed amendment would limit “outrageous and unreasonable” collection practices and would even disallow consumers from sharing their personal information with private actors even if they saw an advantage in doing so.

I responded to Rosen’s proposal in an essay posted on the IAPP  Privacy Perspectives blog, “Do We Need A Constitutional Amendment Restricting Private-Sector Data Collection?” In my essay, I argued that there are several legal, economic, and practical problems with Rosen’s proposal. You can head over to the IAPP blog to read my entire response but the gist of it is that “a constitutional amendment [governing private data collection] would be too sweeping in effect and that better alternatives exist to deal with the privacy concerns he identifies.” There are very good reasons we treat public and private actors differently under the law and there “are all far more practical and less-restrictive steps that can be taken without resorting to the sort of constitutional sledgehammer that Jeff Rosen favors. We can protect privacy without rewriting the Constitution or upending the information economy,” I concluded.

But I wanted to elaborate on one particular thing I found particularly interesting about Rosen’s comments when we were on NPR together. During the show, Rosen kept stressing how we needed to adopt a more European construction of privacy as “dignity rights” and he even said his proposed privacy amendment would even disallow individuals from surrendering their private data or their privacy because he viewed these rights as “unalienable.” In other words, from Rosen’s perspective, privacy pretty much trumps  everything, even if you want to trade it off against other values. 

Privacy Paternalism?

I’ve been seeing more and more privacy advocates and scholars adopt this attitude, including Anita Allen, Julie Cohen, Siva Vaidhyanathan, and others. Allen, for example, says that privacy is such a “foundational” human right that it some cases the law should override individual choice when consumers act against their own privacy interests. Cohen and Vaidhyanathan make similar arguments in their recent books. Vaidhyanathan claims that consumers are being tricked by the “smokescreen” of “free” online services and “freedom of choice.” Although he admits that no one is forced to use online services and that consumers are also able to opt-out of most of services or data collection practices, he argues that “such choices mean very little” because “the design of the system rigs it in favor of the interests of the company and against the interests of users.” “Celebrating freedom and user autonomy is one of the great rhetorical ploys of the global information economy,” he says.“We are conditioned to believe that having more choices–empty though they may be–is the very essence of human freedom. But meaningful freedom implies real control over the conditions of one’s life.” These are the sort of arguments I increasingly hear made by privacy scholars when claiming that consumers simply can’t be left free to make choices for themselves in this regard.  In an interesting recent article in the Harvard Law Review , privacy scholar  Daniel Solove notes that what binds these thinkers and their work together is, in essence, a sort of privacy paternalism. The point of most modern privacy advocacy has been to better empower consumers to make privacy decisions for themselves. But, Solove notes, “t he implication [of these privacy scholar’s work] is that the law must override individual consent in certain instances.” Yet, if that choice is taken away from us by law, Solove notes, then privacy regulation, “risks becoming too paternalistic. Regulation that sidesteps consent denies people the freedom to make choices,” Solove argues.

Jeff Rosen now appears to be adopting the sort of approach Solove identifies by claiming that privacy is an “unalienable right” such that it cannot be traded away for other things. By making that choice for us, Rosen’s proposed amendment would, therefore, suffer from that same sort of privacy paternalism Solove identifies. In a forthcoming law review aritcle that will appear in the  Maine Law Review, I identify some of the problems associated with privacy paternalism. Most obviously, these scholars should keep in mind that not everyone shares the same privacy values as they do and that many of us will voluntarily trade some of our data for the innovative information services and devices that we desire. If imposed in the form of legal sanctions, privacy paternalism would open the door to almost boundless controls on the activities of both producers and consumers of digital services, potentially limiting future innovations in this space.

For example, when we were on  NPR together, Rosen mentioned wireless geolocation technology as a potential source of serious privacy harm, although he did not make it clear whether he wanted it stopped entirely or what. If used improperly, wireless geolocation technology certainly can raise serious privacy concerns. But wireless geolocation technology is also what powers the mapping and traffic services that most of us now take for granted. Many of us expect — no, we demand — that our digital devices be able to give us real-time mapping and traffic notification capabilities. And most of us are willing to make the minor privacy trade-off associated with sharing our location constantly in exchange for the right to receive these services, which are also provided to us free of charge.

So, what would Rosen’s proposed amendment have to say about this trade-off? Would these wireless geolocation technologies be banned altogether, even if consumers desire them? It isn’t really clear at this point because he hasn’t offered us many details about his proposal. But, to the extent it would preempt these technological capabilities on the grounds that our locational privacy is somehow in unalienable right, then that seems like a fairly paternalistic approach to policy and it it would seem to confirm Thomas Lenard and Paul Rubin’s claim that “many of the privacy advocates and writers on the subject do not trust the consumers for whom they purport to advocate.”

Such paternalism is particularly problematic in this case since privacy is such a highly subjective value and one that evolves over time. As Solove notes, “the correct choices regarding privacy and data use are not always clear. For example, although extensive self-exposure can have disastrous consequences, many people use social media successfully and productively.” Privacy norms and ethics are changing faster than ever today. One day’s “creepy” tool or service is often the next day’s “killer app.”

Balancing Values; Considering Costs

As I will discuss in my forthcoming  Maine Law Review article and I also discussed in my recent George Mason University Law Review  article, at least here in the United States, consumer protection standards have traditionally depended on a clear showing of actual, not prospective or hypothetical, harm. In some cases, when the potential harm associated with a particular practice or technology is extreme in character and poses a direct threat to physical well-being, law has preempted the general presumption that ongoing experimentation and innovation should be allowed by default. But these are extremely rare scenarios, at least as it pertains to privacy concerns under American law, and they mostly involved health and safety measures aimed at preemptively avoiding catastrophic harm to individual or environmental well-being. In the vast majority of other cases, our culture has not accepted that paternalistic idea that law must “save us from ourselves” (i.e., our own irrationality or mistakes). As Solove notes in his recent essay, “People make decisions all the time that are not in their best interests. People relinquish rights and take bad risks, and the law often does not stop them.” Sometimes privacy advocates also ignore the costs of preemptive policy action and don’t bother conducting a serious review of the potential costs of their regulatory proposals. As a result, preemptive policy action is almost always the preferred remedy to any alleged harm. “By limiting or conditioning the collection of information, regulators can limit market manipulation at the activity level,” Ryan Calo argues in a recent paper. “We could imagine the government fashioning a rule — perhaps inadvisable for other reasons―that limits the collection of information about consumers in order to reduce asymmetries of information.” [*Clarification: In a comment down below and a subsequent Twitter exchange, Ryan clarifies that he ultimately does not come down in favor of such a rule, preferring instead to find various other incentives to solve these problems. I thank him for this clarification — and definitely welcome it! — although I found his position somewhat murky after debating him personally on these issues recently. Nonetheless, I apologize if I mischaracterized his position in any way here.]

Unfortunately, Professor Calo does not fully consider the corresponding cost of such regulatory proposals in calling for the enactment of such a rule. If preemptive regulation slowed or ended certain information practices, it could stifle the provision of new and better services that consumers demand, as I have noted elsewhere. It might also trump other choices or values that consumers care about. While privacy is obviously an incredibly important value, we cannot assume that it is the only value, or the most important value, at stake here. Consumers also care about having access to a constantly growing array of innovative goods and services, and they also care about getting those goods and services at a reasonable price.

Moving from “Rights Talk” to Practical Privacy Solutions

This is the point in the essay where some readers are getting pretty frustrated with me and thinking I am some sort of nihilist who doesn’t give a damn about privacy. I assure you that nothing is further from the truth and that I care very deeply about privacy.

But if you really care about expanding the horizons of privacy protection in our modern world, at some point you have to accept that all the “rights talk” and top-down enforcement efforts in the world are not necessarily going to help as much as you wish they would. The same thing is true for online safety, digital security, and IP protection efforts: No matter how much you might wish the opposite was true, information control is just really, really hard. Legal and regulatory approaches to bottling up information flows will inevitably be several steps behind cutting-edge technological developments. (I’ve discussed these issues in several essays here, including: “Privacy as an Information Control Regime: The Challenges Ahead,” “Copyright, Privacy, Property Rights & Information Control: Common Themes, Common Challenges,” and “When It Comes to Information Control, Everybody Has a Pet Issue & Everyone Will Be Disappointed.”)

That doesn’t mean we should surrender in our efforts to identify more concrete privacy harms, but we should recognize that it will always be a hugely contentious matter and that a great many people will gladly trade away their privacy in a way that others will consider outrageous. In a free society, we must allow them to do so if they derive greater utility from other things. A paternalistic approach based on a sort of privacy fundamentalism will deny them the right to make that choice for themselves. And, practically speaking, no matter how much some might think that privacy values are “unalienable,” the reality is that there will be no way to stop many others from making different choices and relinquishing their privacy all the time.

Educating and empowering citizens is the better way to address this issue. We can try to teach them to make better privacy choices and treat their information, and information about others, with far greater care. We should also work to provide citizens more tools to help accomplish those goals. And if the problem is “information asymmetry” or some general lack of awareness about certain data collection and use practices, then let’s work even harder to make sure consumers are aware of those practices and what they can do about them.

It’s all part of the media literacy and digital citizenship agenda that we need to be investing much more of time and resources into. I outlined that approach in much more detail in this law review article. We need diverse tools and strategies for a diverse citizenry. We need to be talking to both consumers and developers about smarter data hygiene and sensible digital ethics. We need more transparency. We need more privacy privacy professionals working inside organizations to craft sensible data collection and use policies. And so on. Only by working to change attitudes about privacy, online “Netiquette,” and more ethical data use, can we really start to make a dent in this problem.

If nothing else, we must understand the limitations of information control in such highly context-specific harm scenarios. Prof. Rosen might want to ask himself how long it would take to even get his proposed constitutional amendment in place and what the chances are such a movement would even been successful. But, again, and far more importantly, Prof. Rosen and advocates of similar regulatory approaches should remember that their values are not shared by everyone and that, in a free society, a value as inherently subjective as privacy is likely to remain a hugely contentious, every-changing matter, especially when elevated to the level of constitutional rights talk. We need practical solutions to our privacy problems, not pie-in-the-sky Hail Mary schemes that are unlikely to go anywhere and, even if they did, would end up being too heavy-handed and potentially override individual autonomy in the process.

]]> https://techliberation.com/2014/01/27/is-privacy-an-unalienable-right-the-problem-with-privacy-paternalism/feed/ 1 74147 The Growing Conflict of Visions over the Internet of Things & Privacy https://techliberation.com/2014/01/14/the-growing-conflict-of-visions-over-the-internet-of-things-privacy/ https://techliberation.com/2014/01/14/the-growing-conflict-of-visions-over-the-internet-of-things-privacy/#comments Tue, 14 Jan 2014 20:32:44 +0000 http://techliberation.com/?p=74086

When Google announced it was acquiring digital thermostat company Nest yesterday, it set off another round of privacy and security-related technopanic talk on Twitter and elsewhere. Fear and loathing seemed to be the order of the day. It seems that each new product launch or business announcement in the “Internet of Things” space is destined to set off another round of Chicken Little hand-wringing. We are typically told that the digital sky will soon fall on our collective heads unless we act preemptively to somehow head-off some sort of pending privacy or security apocalypse.

Meanwhile, however, a whole heck of lot of people are demanding more and more of these technologies, and American entrepreneurs are already engaged in heated competition with European and Asian rivals to be at the forefront of the next round Internet innovation to satisfy those consumer demands. So, how is this going to play out?

This gets to what becoming the defining policy issue of our time, not just for the Internet but for technology policy more generally: To what extent should the creators of new technologies seek the blessing of public officials before they develop and deploy their innovations? We can think of this as “the permission question” and it is creating a massive rift between those who desire more preemptive, precautionary safeguards for a variety of reasons (safety, security, privacy, copyright, etc.) and those of us who continue to believe that permissionless innovation should be the guiding ethos of our age. The chasm between these two worldviews is only going to deepen in coming years as the pace of innovation around new technologies (the Internet of Things, wearable tech, driverless cars, 3D printing, commercial drones, etc) continues to accelerate.

Sarah Kessler of Fast Company was kind enough to call me last night and ask for some general comments about Google buying Nest and she also sought out the comments of Marc Rotenberg of EPIC about privacy in the Internet of Things era more generally. Our comments provide a useful example of the divide between these two worldviews and foreshadow debates to come:

With an estimated 50 billion connected objects coming online by 2050, some see good reason to put policies in place that regulate the new categories of data they will collect about the people who use those products. “The basic problem with the Internet of Things, unless privacy safeguards are established up front, is that users will lose control over the data they generate,” Marc Rotenberg, the president of the Electronic Privacy Information Center, told Fast Company in an email. Others see the emerging category as a perfect reason to block omnibus attempts to regulate user data. “If we spend all of our time living in fear of hypothetical worst-case scenarios, then the best-case scenarios will never come about,” says Adam Thierer, a Senior Research Fellow at George Mason University’s Mercatus Center. “That’s the nature of how innovation works. You have to allow for risks and experimentation, and even accidents and failures, if you want to get progress.”

Last week, I wrote about this conflict of visions in my dispatch from the CES show and this topic is also the focus of my forthcoming eBook, “Permissionless Innovation: The Continuing Case for Comprehensive Technological Freedom.” To reiterate what I already said, my book will describe the future of the Internet of Things and all technology policy as a grand battle the “precautionary principle” and “permissionless innovation.” The “precautionary principle” refers to the belief that new innovations should be curtailed or disallowed until their developers can prove that they will not cause any harms to individuals, groups, specific entities, cultural norms, or various existing laws, norms, or traditions. The other worldview, “permissionless innovation,” refers to the notion that experimentation with new technologies and business models should generally be permitted by default. Unless a compelling case can be made that a new invention will bring serious harm to society, innovation should be allowed to continue unabated and problems, if they develop at all, can be addressed later.

While those adhering to the precautionary principle mindset tend to favor “top-down” legalistic approaches to solving those potential problems that might creep up, those of us who favor the premissionless innovation approach favor “bottom-up” solutions that evolve over time but do not interrupt the ongoing experimentation and innovation that consumers demand. What does a “bottom-up” approach mean in practice? Education and empowerment, social pressure, societal norms, voluntary self-regulation, and targeted enforcement of existing legal norms (especially through the common law) are almost always superior to top-down, command-and-control regulatory edits and bureaucratic schemes of a “Mother, May I” (i.e., permissioned) nature.

We really should not underestimate the power of norms and public pressure to “regulate” in this regard, perhaps even better than law, which tends to be too slow-moving to make much of a difference. In my book I spend a great deal of time talking about how other technological innovations have been shaped by social norms, public pressure, and press attention. That same will be true for the Internet of Things and various new technologies I discuss in my book. Others will gradually adapt to the new technological realities and integrate these new devices and services into their lives over time.

Perhaps, then, it will be the case that if Google does something particularly bone-headed with Nest that a public backlash will ensue. Or maybe some consumers will just reject Nest and look for other options, which is apparently what Rotenberg is doing according to the Fast Company article. Of course, as I noted in concluding the interview, others may act quite differently and accept Nest and other new Internet of Things technologies, even if there are some privacy or security downsides. As I told Sarah Kessler, while I was visiting the consumer electronics show last week, I heard it was freezing back here in DC. If I would have had Nest in my house, perhaps Google Now could have alerted me to the dangerously low temps in my house and suggested that I raise the temp remotely before my pipes froze. As I noted to Kessler:

“Would that have been creepy?” he says. “To me it would have been helpful. So for everything that people regard as a negative, I can usually find a positive. And if there’s that balance there, then it should be left to individuals to decide for themselves how to decide that balance.”

Finally, since I often get accused of being some sort of nihilist in these debates, I want to make it clear that ethics should influence all these discussions, but I prefer that we not impose ethics in a heavy-handed, inflexible way through preemptive, proscriptive regulatory controls. It makes more sense to wait and see how things play out before regulating to address harms, once we figure out which ones are real. (See the second and third essays listed below for more on ethics and technological innovation.) But we absolutely need to be engaging in robust societal discussions about digital ethics, digital citizenship, privacy and security by design, and sensible online etiquette. I’ve spent a lifetime writing about the power of that approach in the context of online child safety and I think it is equally applicable for privacy and security-related matters. In particular, we need to talk to our kids and our future technologists and innovators about smarter digital habits that respect the safety, security, and privacy of others. Those conversations can help us chart a more sensible path forward without sacrificing the many benefits that accompany the ongoing technological revolution we are blessed to be experiencing today.

Additional Reading:

]]> https://techliberation.com/2014/01/14/the-growing-conflict-of-visions-over-the-internet-of-things-privacy/feed/ 2 74086 On the Line between Technology Ethics vs. Technology Policy https://techliberation.com/2013/08/01/on-the-line-between-technology-ethics-vs-technology-policy/ https://techliberation.com/2013/08/01/on-the-line-between-technology-ethics-vs-technology-policy/#comments Thu, 01 Aug 2013 14:32:00 +0000 http://techliberation.com/?p=45354

10 commandmentsWhat works well as an ethical directive might not work equally well as a policy prescription. Stated differently, what one ought to do it certain situations should not always be synonymous with what they must do by force of law.

I’m going to relate this lesson to tech policy debates in a moment, but let’s first think of an example of how this lesson applies more generally. Consider the Ten Commandments. Some of them make excellent ethical guidelines (especially the stuff about not coveting neighbor’s house, wife, or possessions). But most of us would agree that, in a free and tolerant society, only two of the Ten Commandments make good law: Thou shalt not kill and Thou shalt not steal.

In other words, not every sin should be a crime. Perhaps some should be; but most should not. Taking this out of the realm of religion and into the world of moral philosophy, we can apply the lesson more generally as: Not every wise ethical principle makes for wise public policy.

Before I get accused of being accused of being some sort of nihilist, I want to be clear that I am absolutely not saying that ethics should never have a bearing on policy. Obviously, all political theory is, at some level, reducible to ethical precepts. My own political philosophy is strongly rooted in the Millian harm principle (“The only purpose for which power can be rightfully exercised over any member of a civilized community, against his will, is to prevent harm to others.”) Not everyone will agree will Mill’s principle, but I would hope most of us could agree that, if we hope to preserve a free and open society, we simply cannot convert every ethical directive into a legal directive or else the scope of human freedom will need to shrink precipitously.

Can We Plan for Every “Bad Butterfly-Effect”?

Anyway, what got me thinking about all this and it its applicability to technology policy was an interesting Wired essay by Patrick Lin entitled, “The Ethics of Saving Lives With Autonomous Cars Are Far Murkier Than You Think.” Lin is the director of the Ethics + Emerging Sciences Group at California Polytechnic State University in San Luis Obispo and lead editor of Robot Ethics (MIT Press, 2012). So, this a man who has obviously done a lot of thinking about the potential ethical challenges presented by the growing ubiquity of robots and autonomous vehicles in society. (His column makes for particularly fun reading if you’ve ever spent time pondering Asimov’s “Laws of Robotics.”)

Lin walks through various hypothetical scenarios regarding the future of autonomous vehicles and discusses the ethical trade-offs at work here. He asks a number of questions about a future of robotic cars and encourages us to give some thoughtful deliberation to the benefits and potential costs of autonomous vehicles. I will not comment here on all the specific issues that lead Lin to question whether they are worth it; instead I want to focus on Lin’s ultimate conclusion.

I commenting on the potential risks and trade-offs, Lin notes:

The introduction of any new technology changes the lives of future people. We know it as the “butterfly effect” or chaos theory: Anything we do could start a chain-reaction of other effects that result in actual harm (or benefit) to some persons somewhere on the planet.

That’s self-evident, of course, but what of it? How should that truism influence tech ethics and/or tech policy? Here are Lin’s thoughts:

For us humans, those effects are impossible to precisely predict, and therefore it is impractical to worry about those effects too much. It would be absurdly paralyzing to follow an ethical principle that we ought to stand down on any action that could have bad butterfly-effects, as any action or inaction could have negative unforeseen and unintended consequences. But … we can foresee the general disruptive effects of a new technology, especially the nearer-term ones, and we should therefore mitigate them. The butterfly-effect doesn’t release us from the responsibility of anticipating and addressing problems the best we can. As we rush into our technological future, don’t think of these sorts of issues as roadblocks, but as a sensible yellow light — telling us to look carefully both ways before we cross an ethical intersection.

Lin makes some important points here, but these closing comments (and his article more generally) have a whiff of “precautionary principle” thinking to it that makes me more than a bit uncomfortable. The precautionary principle generally holds that, because a new idea or technology could pose some theoretical danger or risk in the future, public policies should control or limit the development of such innovations until their creators can prove that they won’t cause any harms. Before we walk down that precautionary path, we need to consider the consequences.

The Problem with Precaution

I have spent a great deal of time writing about the dangers of precautionary principle thinking in my recent articles and essays, including my recent law review article, “Technopanics, Threat Inflation, and the Danger of an Information Technology Precautionary Principle,” as well as in two lengthy blog posts asking the questions, “Who Really Believes in ‘Permissionless Innovation’?” and “What Does It Mean to ‘Have a Conversation’ about a New Technology?”

The key point I try to get across in those essays is that letting such precautionary thinking guide policy poses a serious threat to technological progress, economic entrepreneurialism, social adaptation, and long-run prosperity. If public policy is guided at every turn by the precautionary principle, technological innovation is impossible because of fear of the unknown; hypothetical worst-case scenarios trump all other considerations. Social learning and economic opportunities become far less likely, perhaps even impossible, under such a regime. In practical terms, it means fewer services, lower quality goods, higher prices, diminished economic growth, and a decline in the overall standard of living.

In Lin’s essay, we see some precautionary reasoning at work when he argues that “we can foresee the general disruptive effects of a new technology, especially the nearer-term ones, and we should therefore mitigate them” and that we have “responsibility [for] anticipating and addressing problems the best we can.”

To be fair, Lin caveats this by first noting that precise effects are “impossible to predict” and, therefore, that “It would be absurdly paralyzing to follow an ethical principle that we ought to stand down on any action that could have bad butterfly-effects, as any action or inaction could have negative unforeseen and unintended consequences.” Second, as it relates to general effects, he says we should just be “addressing problems the best we can.”

Despite those caveats, I continue to have serious concerns about the potential blurring of ethics and law here. The most obvious question I would have for Lin is: Who is the “we” in this construct?  Is it “we” as individuals and institutions interacting throughout society freely and spontaneously, or is it “we” as in the government imposing precautionary thinking through top-down public policy?

I can imagine plenty of scenarios in which a certain amount of precautionary thinking may be entirely appropriate if applied as an informal ethical norm at the individual, household, organizational or even societal level, but which would not be as sensible if applied as a policy prescription. For example, parents should take steps to shield their kids from truly offensive and hateful material on the Internet before they are mature enough to understand the ramifications of it. But that doesn’t mean it would be wise to enshrine the same principle into law in the form of censorship.

Similarly, there are plenty of smart privacy and security norms that organizations should practice that need not be forced on them by law, especially since such mandates would have serious costs if mandated. For example, I think that organizations should feel a strong obligation to safeguard user data and avoid privacy and security screw-ups. I’d like to see more organizations using encryption wherever they can in their systems and also delete unnecessary data whenever possible. But, for a variety of reasons, I do not believe any of these things should be mandated through law or regulation.

Don’t Foreclose Experimentation

While Lin rightly acknowledges the “negative unforeseen and unintended consequences” of preemptive policy action to address precise concerns, he does not unpack the full ramifications of those unseen consequences. Nor does he answer how the royal “we” separate the “precise” from the “general” concerns? (For example, are the specific issues I just raised in the preceding paragraphs “precise” or “general”? What’s the line between the two?)

But I have a bigger concern with Lin’s argument, as well with the field of technology ethics more generally: We rarely hear much discussion of the benefits associated with the ongoing process of trial-and-error experimentation and, more importantly, the benefits of failure and what we learn — both individually and collectively — from the mistakes we inevitably make.

The problem with regulatory systems is that they are permission-based. They focus on preemptive remedies that aim to forecast the future, and future mistakes (i.e., Lin’s “butterfly effects”) in particular.  Worse yet, administrative regulation generally preempts or prohibits the beneficial experiments that yield new and better ways of doing things — including what we learn from failed efforts at doing things. But we will never discover better ways of doing things unless the process of evolutionary, experimental change is allowed to continue. We need to keep trying and failing in order to learn how we can move forward. As Samuel Beckett once counseled: “Ever tried. Ever failed. No matter. Try Again. Fail again. Fail better.” Real wisdom is born of experience, especially mistakes we make along the way.

This is why I feel so passionately about drawing a distinction between ethical norms and public policy pronouncements.  Law forecloses. It is inflexible. It does not adapt as efficiently or rapidly as social norms do. Ethics and norms provide guidance but also leave plenty of breathing room for ongoing experimentation, and they are refined continuously and in response to ongoing social developments.

It is worth noting that ethics evolve, too. There is a sort of ethical trial-and-error that occurs in society over time as new developments challenge, and then change, old ethical norms. This is another reason we want to be careful about enshrining norms into law.

Thus, policymakers should not be imposing prospective restrictions on new innovations without clear evidence of actual, not merely hypothesized, harm. That’s especially the case since, more often than not, human adapt to new technologies and find creative ways to assimilate even the most disruptive innovations into their lives. We cannot possibly plan for all the “bad butterfly-effects” that might occur, and attempts to do so will result in significant sacrifices in terms of social and economic liberty.

The burden of proof should be on those who advocate preemptive restrictions on technological innovation to show why freedom to tinker and experiment must be foreclosed by policy. There should exist the strongest presumption that the freedom to innovate and experiment will advance human welfare and teach us new and better ways of doing things to overcome most of those “bad butterfly-effects” over time.

So, in closing, let us yield at Lin’s “sensible yellow light — telling us to look carefully both ways before we cross an ethical intersection.” But let us not be cowed into an irrational fear of an unknown and ultimately unknowable future. And let us not be tempted to try to plan for every potential pitfall through preemptive policy prescriptions, lest progress and prosperity get sacrificed as a result of such hubris.

]]> https://techliberation.com/2013/08/01/on-the-line-between-technology-ethics-vs-technology-policy/feed/ 6 45354 Richard Brandt on Jeff Bezos and amazon.com https://techliberation.com/2013/06/25/richard-brandt/ https://techliberation.com/2013/06/25/richard-brandt/#respond Tue, 25 Jun 2013 10:00:04 +0000 http://techliberation.com/?p=45008

Richard Brandt, technology journalist and author, discusses his new book, One Click: Jeff Bezos and the Rise of Amazon.Com. Brandt discusses Bezos’ entrepreneurial drive, his business philosophy, and how he’s grown Amazon to become the biggest retailer in the world. This episode also covers the biggest mistake Bezos ever made, how Amazon uses patent laws to its advantage, whether Amazon will soon become a publishing house, Bezos’ idea for privately-funded space exploration and his plan to revolutionize technology with quantum computing.

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]]> https://techliberation.com/2013/06/25/richard-brandt/feed/ 0 45008 Guidelines & Best Practices for Anonymous Blogging (Pt.2) https://techliberation.com/2009/08/29/guidelines-best-practices-for-anonymous-blogging-pt-2/ https://techliberation.com/2009/08/29/guidelines-best-practices-for-anonymous-blogging-pt-2/#comments Sat, 29 Aug 2009 15:17:46 +0000 http://techliberation.com/?p=20787

Dan GillmorIn a post earlier this week, I discussed Randy Cohen’s “guideline” for anonymous blogging. Specifically, Cohen argued in a recent New York Times piece that, “The effects of anonymous posting have become so baleful that it should be forsworn unless there is a reasonable fear of retribution.  By posting openly, we support the conditions in which honest conversation can flourish.”  While sympathetic to that guideline, I noted I agreed with it as an ethical principle, not a legal matter.  In others words, what might make sense as a “best practice” for the Internet and its users would not make sense as a regulatory standard.  I prefer using social norms and public pressure to drive these standards, not regulation that could have an unintended chilling effect on beneficial forms of anonymous online speech.

Dan Gillmor of the Center for Citizen Media of the Harvard Berkman Center has a new column up at the UK Guardian in which he takes a slightly different cut at a new standard or social norm for dealing with some of the more caustic anonymous speech out there:

One of the norms we’d be wise to establish is this: People who don’t stand behind their words deserve, in almost every case, no respect for what they say. In many cases, anonymity is a hiding place that harbours cowardice, not honour. The more we can encourage people to use their real names, the better. But if we try to force this, we’ll create more trouble than we fix.  But we don’t want, in the end, to turn everything over to the lawyers. The rest of us — the audience, if you will — need to establish some new norms as well.

Specifically, Gillmor argues that, ” We need to readjust our internal BS meters in a media-saturated age,” because “We are far too prone to accepting what we see and hear.”  I think Gillmor has too little faith in most digital denizens; most of us take anonymous comments with a grain of salt and assume that the ugliest of those comments are often untrue.  And that’s generally the “principle” he recommends each of us adopt going forward:

When you read or hear an anonymous or pseudonymous attack on someone else, you should not just assume — barring persuasive evidence of the charge — that it’s false. Assume that the accuser is an outright, contemptible liar.

I am generally sympathetic to Gillmor’s principle, but I think he goes a bit overboard in asking us to assume that all anonymous or pseudonymous attacks are false. So, here’s a reformulation of it: We should discount, by at least some small measure, anonymous online speech that attacks others in a heated manner and which lacks supporting evidence for the assertions made or charges levied. However, the more heated or vicious the attack, the greater we should discount the veracity of the claims asserted.

Of course, this is simply a guideline for readers, not speakers or the sites that host online speech.  Each speaker will have to decide for themselves whether to post anonymously or reveal their identities. As I noted in my previous essay, however, I think it makes sense to generally encourage people to reveal their true identities when blogging or commenting.  I have always lived by that rule personally when blogging or posting comments on other sites, whether they are blogs, discussion boards, or even shopping sites.

For sites that host speech, things get trickier.  Luckily, we have Section 230 of the CDA to protect online operators from onerous forms of liability for the content they host on their sites, although some would like to change that. Also, as I’ve discussed here before, some critics of online anonymity would like to see “civility check” or “cooling off periods” instituted that would prevent instantaneous comments from being posted without some sort of human or automated review of the content.  But tweaking Sec. 230 liability norms or requiring “cooling off periods” for comments could have a profoundly chilling effect on many beneficial forms of online speech. As Gillmor wisely notes in his essay:

anonymity has crucially important value. We need it for whistleblowers, for political dissidents in dictatorships — for those who have important stories to tell but whose lives or livelihoods would be in jeopardy if their identities were exposed.

And one has to think through the mechanics of regulation before willy-nilly proposing to “ban anonymity” online.  As Gillmor points out, that could lead to some troubling outcomes:

People who’d ban anonymity don’t seem to realise that it’s technically impossible unless we’re willing to turn over all of our communications in every venue to a central authority — a system that would herald the end of liberty. They can’t really want such a regime, can they? Meanwhile, even that kind of structure could and would be hacked by motivated types, though with more difficulty.

That’s exactly right. Nonetheless, online speakers and websites shouldn’t just treat Sec. 230 as a “get-out-of-jail-free” card or let their anonymous speech rights go to their heads.  There’s nothing wrong with a little sensible site policing and self-regulation to deal with the baser elements of the blogosphere.

]]> https://techliberation.com/2009/08/29/guidelines-best-practices-for-anonymous-blogging-pt-2/feed/ 18 20787 Randy Cohen’s “Guideline” for Anonymous Blogging: Ethical or Legal Matter? https://techliberation.com/2009/08/26/randy-cohens-guideline-for-anonymous-blogging-ethical-or-legal-matter/ https://techliberation.com/2009/08/26/randy-cohens-guideline-for-anonymous-blogging-ethical-or-legal-matter/#comments Wed, 26 Aug 2009 04:28:59 +0000 http://techliberation.com/?p=20711

Liskula CohenRandy Cohen, who pens “The Ethicist” column for The New York Times Magazine, wrote this week about the “skank case,” or the controversy surrounding the recent legal outing for an anonymous blogger who called fashion model Liskula Cohen a “psychotic, lying, whoring … skank.”   Thanks to a recent court decision, we now know that the blogger who uttered those words is Rosemary Port, a 29-year-old Fashion Institute of Technology student.  And she now apparently plans to sue Google for revealing her identity to the court. [As a shameful aside, can I just say that there has never been a nerdy Internet legal battle that involved two more smokin’ hot women than this! Sorry, I couldn’t resist pointing out the obvious.]

Rosemary PortReflecting on this catfight in his NY Times Magazine editorial, “Is It O.K. to Blog About This Woman Anonymously?” Randy Cohen asks:

Has anonymous posting, though generally protected by law, become so toxic that it should be discouraged? It has. To promote the social good of lively conversation and the exchange of ideas, transparency should be the default mode. […]
Here is a guideline. The effects of anonymous posting have become so baleful that it should be forsworn unless there is a reasonable fear of retribution.  By posting openly, we support the conditions in which honest conversation can flourish.

But Mr. Cohen never specifies whether he is talking about an ethical guideline or a legal guideline. There is a world of difference, of course.  As a matter of social or personal ethics, I think many of us would agree that anonymity “should be forsworn” and we should encourage people to “post openly.”   I always live by that rule myself when blogging or posting comments on other sites, whether they are blogs, discussion boards, or even shopping sites.  But that is my choice. I would not want that choice forced by law upon others.

Some might say, why not? Isn’t it just as good of a legal principle as a social norm? Absolutely not. The chilling effect would be substantial.  Of course, some would say, ‘Fine, we need to chill a little speech when that speech gets too heated or vulgar.’  But that’s a dangerous line we should be wary of asking judges to cross.  As is always the case in matters such as this, it comes down to a line-drawing exercise regarding what should constitute “acceptable speech.”

The better approach is to take Mr. Cohen’s “guideline” and push for its general acceptance for some (perhaps most) websites, but leave everyone free to decide whether anonymous posting and comments remain in place.  We don’t demand identification here at the TLF, for example, because we don’t necessarily mind what some shitheads (you know who you are!) will say about us or our views. But we certainly try to encourage people to self-identify by signing in first and “claiming” their comments.  Most do. A handful don’t. And still others do sign in but leave comments under a pseudonym.  I say let the various models continue to flourish across the web while also encouraging bloggers and websites to adopt Randy Cohen’s general rule as a website “best practice.”

Can self-regulation, social norms, public and press attention, and external pressure form others encourage some of the most vitriolic voices of the Net to moderate their tone?  Perhaps not.  With a platform like the Internet, you have to be willing to accept some silliness from those loonies who haven’t quite learned how to responsibly use this wonderful tool that has been put at their disposal.  But I will take this approach over the forced surrender of our anonymity any day of the week.

Other views: Dan Solove;  Kathleen Parker of the Washington Post;  Maureen Dowd of the New York Times; UK Guardian “Belle de Jour” column; Richard Korman of ZDNet; Chris Matyszczyk writing at CNet News; JR Raphael writing at PC World; Lance Ulanoff of PC Mag.com

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