Law Commons^™

Open-Source Clinical Machine Learning Models: Critical Appraisal Of Feasibility, Advantages, And Challenges, Keerthi B. Harish, W. Nicholson Price Ii, Yindalon Aphinyanaphongs

Articles

Machine learning applications promise to augment clinical capabilities and at least 64 models have already been approved by the US Food and Drug Administration. These tools are developed, shared, and used in an environment in which regulations and market forces remain immature. An important consideration when evaluating this environment is the introduction of open-source solutions in which innovations are freely shared; such solutions have long been a facet of digital culture. We discuss the feasibility and implications of open-source machine learning in a health care infrastructure built upon proprietary information. The decreased cost of development as compared to drugs and …

Algorithmic Governance From The Bottom Up, Hannah Bloch-Wehba

Faculty Scholarship

Artificial intelligence and machine learning are both a blessing and a curse for governance. In theory, algorithmic governance makes government more efficient, more accurate, and more fair. But the emergence of automation in governance also rests on public-private collaborations that expand both public and private power, aggravate transparency and accountability gaps, and create significant obstacles for those seeking algorithmic justice. In response, a nascent body of law proposes technocratic policy changes to foster algorithmic accountability, ethics, and transparency.

This Article examines an alternative vision of algorithmic governance, one advanced primarily by social and labor movements instead of technocrats and firms. …

Using Artificial Intelligence In The Law Review Submissions Process, Brenda M. Simon

Faculty Scholarship

The use of artificial intelligence to help editors examine law review submissions may provide a way to improve an overburdened system. This Article is the first to explore the promise and pitfalls of using artificial intelligence in the law review submissions process. Technology-assisted review of submissions offers many possible benefits. It can simplify preemption checks, prevent plagiarism, detect failure to comply with formatting requirements, and identify missing citations. These efficiencies may allow editors to address serious flaws in the current selection process, including the use of heuristics that may result in discriminatory outcomes and dependence on lower-ranked journals to conduct …

Content Moderation As Surveillance, Hannah Bloch-Wehba

Faculty Scholarship

Technology platforms are the new governments, and content moderation is the new law, or so goes a common refrain. As platforms increasingly turn toward new, automated mechanisms of enforcing their rules, the apparent power of the private sector seems only to grow. Yet beneath the surface lies a web of complex relationships between public and private authorities that call into question whether platforms truly possess such unilateral power. Law enforcement and police are exerting influence over platform content rules, giving governments a louder voice in supposedly “private” decisions. At the same time, law enforcement avails itself of the affordances of …

Biometrics And An Ai Bill Of Rights, Margaret Hu

Faculty Publications

This Article contends that an informed discussion on an AI Bill of Rights requires grappling with biometric data collection and its integration into emerging AI systems. Biometric AI systems serve a wide range of governmental purposes, including policing, border security and immigration enforcement, and biometric cyberintelligence and biometric-enabled warfare. These systems are increasingly categorized as "high-risk" when deployed in ways that may impact fundamental constitutional rights and human rights. There is growing recognition that high-risk biometric AI systems, such as facial recognition identification, can pose unprecedented challenges to criminal procedure rights. This Article concludes that a failure to recognize these …

The Role Of Data For Ai Startup Growth, James Bessen, Stephen Michael Impink, Lydia Reichensperger, Robert Seamans

Faculty Scholarship

Artificial intelligence (“AI”)-enabled products are expected to drive economic growth. Training data are important for firms developing AI-enabled products; without training data, firms cannot develop or refine their algorithms. This is particularly the case for AI startups developing new algorithms and products. However, there is no consensus in the literature on which aspects of training data are most important. Using unique survey data of AI startups, we find that startups with access to proprietary training data are more likely to acquire venture capital funding.

Assessing Automated Administration, Cary Coglianese, Alicia Lai

All Faculty Scholarship

To fulfill their responsibilities, governments rely on administrators and employees who, simply because they are human, are prone to individual and group decision-making errors. These errors have at times produced both major tragedies and minor inefficiencies. One potential strategy for overcoming cognitive limitations and group fallibilities is to invest in artificial intelligence (AI) tools that allow for the automation of governmental tasks, thereby reducing reliance on human decision-making. Yet as much as AI tools show promise for improving public administration, automation itself can fail or can generate controversy. Public administrators face the question of when exactly they should use automation. …

Crossing The Rubicon: Evaluating The Use Of Artificial Intelligence In The Law And Singapore Courts, Ming En Tor

Research Collection Yong Pung How School Of Law

In recent years, Artificial Intelligence (“AI”) has challenged many fundamental assumptions of how organisations and industries should operate. The Courts, traditionally seen as a hallowed ground graced by the best of lawyers, still remains as unchartered territory for AI’s infiltration. Yet, there is growing evidence which suggest AI may soon cross this frontier to replace important court functions.

This paper critically assesses the use of AI in law and the courts. Part II will first examine the arguments for and against the adoption of AI in the legal profession. Thereafter, Part III will critically examine whether AI should …

Volume Introduction, I. Glenn Cohen, Timo Minssen, W. Nicholson Price Ii, Christopher Robertson, Carmel Shachar

Other Publications

Medical devices have historically been less regulated than their drug and biologic counterparts. A benefit of this less demanding regulatory regime is facilitating innovation by making new devices available to consumers in a timely fashion. Nevertheless, there is increasing concern that this approach raises serious public health and safety concerns. The Institute of Medicine in 2011 published a critique of the American pathway allowing moderate-risk devices to be brought to the market through the less-rigorous 501(k) pathway,1 flagging a need for increased postmarket review and surveillance. High-profile recalls of medical devices, such as vaginal mesh products, along with reports globally …

Distributed Governance Of Medical Ai, W. Nicholson Price Ii

Law & Economics Working Papers

Artificial intelligence (AI) promises to bring substantial benefits to medicine. In addition to pushing the frontiers of what is humanly possible, like predicting kidney failure or sepsis before any human can notice, it can democratize expertise beyond the circle of highly specialized practitioners, like letting generalists diagnose diabetic degeneration of the retina. But AI doesn’t always work, and it doesn’t always work for everyone, and it doesn’t always work in every context. AI is likely to behave differently in well-resourced hospitals where it is developed than in poorly resourced frontline health environments where it might well make the biggest difference …

Moving Toward Personalized Law, Cary Coglianese

All Faculty Scholarship

Rules operate as a tool of governance by making generalizations, thereby cutting down on government officials’ need to make individual determinations. But because they are generalizations, rules can result in inefficient or perverse outcomes due to their over- and under-inclusiveness. With the aid of advances in machine-learning algorithms, however, it is becoming increasingly possible to imagine governments shifting away from a predominant reliance on general rules and instead moving toward increased reliance on precise individual determinations—or on “personalized law,” to use the term Omri Ben-Shahar and Ariel Porat use in the title of their 2021 book. Among the various technological, …

Ethical Ai Development: Evidence From Ai Startups, James Bessen, Stephen Michael Impink, Lydia Reichensperger, Robert Seamans

Faculty Scholarship

Artificial Intelligence startups use training data as direct inputs in product development. These firms must balance numerous trade-offs between ethical issues and data access without substantive guidance from regulators or existing judicial precedence. We survey these startups to determine what actions they have taken to address these ethical issues and the consequences of those actions. We find that 58% of these startups have established a set of AI principles. Startups with data-sharing relationships with high-technology firms; that were impacted by privacy regulations; or with prior (non-seed) funding from institutional investors are more likely to establish ethical AI principles. Lastly, startups …

New Innovation Models In Medical Ai, W Nicholson Price Ii, Rachel E. Sachs, Rebecca S. Eisenberg

Articles

In recent years, scientists and researchers have devoted considerable resources to developing medical artificial intelligence (AI) technologies. Many of these technologies—particularly those that resemble traditional medical devices in their functions—have received substantial attention in the legal and policy literature. But other types of novel AI technologies, such as those related to quality improvement and optimizing use of scarce facilities, have been largely absent from the discussion thus far. These AI innovations have the potential to shed light on important aspects of health innovation policy. First, these AI innovations interact less with the legal regimes that scholars traditionally conceive of as …

Ai Derivatives: The Application To The Derivative Work Right To Literary And Artistic Productions Of Ai Machines, Daniel J. Gervais

Vanderbilt Law School Faculty Publications

This Article predicts that there will be attempts to use courts to try to broaden the derivative work right in litigation either to prevent the use of, or claim protection for, literary and artistic productions made by Artificial Intelligence (AI) machines. This Article considers the normative valence of, and the (significant) doctrinal pitfalls associated with, such attempts. It also considers a possible legislative alternative, namely attempts to introduce a new sui generis right in AI productions. Finally, this Article explains how, whether such attempts succeed or not, the debate on rights (if any) in productions made by AI machines is …

Part I - Ai And Data As Medical Devices, W. Nicholson Price Ii

Other Publications

It may seem counterintuitive to open a book on medical devices with chapters on software and data, but these are the frontiers of new medical device regulation and law. Physical devices are still crucial to medicine, but they – and medical practice as a whole – are embedded in and permeated by networks of software and caches of data. Those software systems are often mindbogglingly complex and largely inscrutable, involving artificial intelligence and machine learning. Ensuring that such software works effectively and safely remains a substantial challenge for regulators and policymakers. Each of the three chapters in this part examines …

Professional Speech At Scale, Cassandra Burke Robertson, Sharona Hoffman

Faculty Publications

Regulatory actions affecting professional speech are facing new challenges from all sides. On one side, the Supreme Court has grown increasingly protective of professionals’ free speech rights, and it has subjected regulations affecting that speech to heightened levels of scrutiny that call into question traditional regulatory practices in both law and medicine. On the other side, technological developments, including the growth of massive digital platforms and the introduction of artificial intelligence programs, have created brand new problems of regulatory scale. Professional speech is now able to reach a wide audience faster than ever before, creating risks that misinformation will cause …

When Ai Goes To War: Corporate Accountability For Virtual Mass Disinformation, Algorithmic Atrocities, And Synthetic Propaganda, Jon M. Garon

Faculty Scholarship

No abstract provided.

Algorithm Vs. Algorithm, Cary Coglianese, Alicia Lai

All Faculty Scholarship

Critics raise alarm bells about governmental use of digital algorithms, charging that they are too complex, inscrutable, and prone to bias. A realistic assessment of digital algorithms, though, must acknowledge that government is already driven by algorithms of arguably greater complexity and potential for abuse: the algorithms implicit in human decision-making. The human brain operates algorithmically through complex neural networks. And when humans make collective decisions, they operate via algorithms too—those reflected in legislative, judicial, and administrative processes. Yet these human algorithms undeniably fail and are far from transparent. On an individual level, human decision-making suffers from memory limitations, fatigue, …

Liability For Use Of Artificial Intelligence In Medicine, W. Nicholson Price, Sara Gerke, I. Glenn Cohen

Law & Economics Working Papers

While artificial intelligence has substantial potential to improve medical practice, errors will certainly occur, sometimes resulting in injury. Who will be liable? Questions of liability for AI-related injury raise not only immediate concerns for potentially liable parties, but also broader systemic questions about how AI will be developed and adopted. The landscape of liability is complex, involving health-care providers and institutions and the developers of AI systems. In this chapter, we consider these three principal loci of liability: individual health-care providers, focused on physicians; institutions, focused on hospitals; and developers.

Artificially Intelligent Boards And The Future Of Delaware Corporate Law, Christopher Bruner

Scholarly Works

The prospects for Artificial Intelligence (AI) to impact the development of Delaware corporate law are at once over- and under-stated. As a general matter, claims to the effect that AI systems might ultimately displace human directors not only exaggerate the foreseeable technological potential of these systems, but also tend to ignore doctrinal and institutional impediments intrinsic to Delaware's competitive model – notably, heavy reliance on nuanced and context-specific applications of the fiduciary duty of loyalty by a true court of equity. At the same time, however, there are specific applications of AI systems that might not merely be accommodated by …

Modeling Through, Ryan Calo

Articles

Theorists of justice have long imagined a decision-maker capable of acting wisely in every circumstance. Policymakers seldom live up to this ideal. They face well-understood limits, including an inability to anticipate the societal impacts of state intervention along a range of dimensions and values. Policymakers cannot see around corners or address societal problems at their roots. When it comes to regulation and policy-setting, policymakers are often forced, in the memorable words of political economist Charles Lindblom, to “muddle through” as best they can.

Powerful new affordances, from supercomputing to artificial intelligence, have arisen in the decades since Lindblom’s 1959 article …

Terrified By Technology: How Systemic Bias Distorts U.S. Legal And Regulatory Responses To Emerging Technology, Steve Calandrillo, Nolan Kobuke Anderson

Articles

Americans are becoming increasingly aware of the systemic biases we possess and how those biases preclude us from collectively living out the true meaning of our national creed. But to fully understand systemic bias we must acknowledge that it is pervasive and extends beyond the contexts of race, privilege, and economic status. Understanding all forms of systemic bias helps us to better understand ourselves and our shortcomings. At first glance, a human bias against emerging technology caused by systemic risk misperception might seem uninteresting or unimportant. But this Article demonstrates how the presence of systemic bias anywhere, even in an …

Professional Speech At Scale, Cassandra Burke Robertson, Sharona Hoffman

Faculty Publications

Regulatory actions affecting professional speech are facing new challenges from all sides. On one side, the Supreme Court has grown increasingly protective of professionals’ free speech rights, and it has subjected regulations affecting that speech to heightened levels of scrutiny that call into question traditional regulatory practices in both law and medicine. On the other side, technological developments, including the growth of massive digital platforms and the introduction of artificial intelligence programs, have created brand new problems of regulatory scale. Professional speech is now able to reach a wide audience faster than ever before, creating risks that misinformation will cause …

From Negative To Positive Algorithm Rights, Cary Coglianese, Kat Hefter

All Faculty Scholarship

Artificial intelligence, or “AI,” is raising alarm bells. Advocates and scholars propose policies to constrain or even prohibit certain AI uses by governmental entities. These efforts to establish a negative right to be free from AI stem from an understandable motivation to protect the public from arbitrary, biased, or unjust applications of algorithms. This movement to enshrine protective rights follows a familiar pattern of suspicion that has accompanied the introduction of other technologies into governmental processes. Sometimes this initial suspicion of a new technology later transforms into widespread acceptance and even a demand for its use. In this paper, we …

A Compulsory Solution To The Machine Problem, Cole G. Merritt

Vanderbilt Law School Faculty Publications

Artificial Intelligence (AI) is already disrupting and will likely continue to disrupt many industries. Despite the role AI already plays, AI systems are becoming increasingly powerful. Ultimately, these systems may become a powerful tool that can lead to the discovery of important inventions or significantly reduce the time required to discover these inventions. Even now, AI systems are independently inventing. However, the resulting AI-generated inventions are unable to receive patent protection under current US patent law. This unpatentability may lead to inefficient results and ineffectively serves the goals of patent law.

To embrace the development and power of AI, Congress …

Artificially Intelligent Boards And The Future Of Delaware Corporate Law, Christopher Bruner

Scholarly Works

This article argues that the prospects for Artificial Intelligence (AI) to impact corporate law are at once over- and under-stated, focusing on the law of Delaware – the predominant jurisdiction of incorporation for US public companies. Claims that AI systems might displace human directors not only exaggerate AI’s foreseeable technological potential, but ignore doctrinal and institutional impediments intrinsic to Delaware’s competitive model – notably, heavy reliance on nuanced applications of the fiduciary duty of loyalty by a true court of equity. At the same time, however, there are discrete AI applications that might not merely be accommodated by Delaware corporate …

Data Privacy, Human Rights, And Algorithmic Opacity, Sylvia Lu

Fellow, Adjunct, Lecturer, and Research Scholar Works

Decades ago, it was difficult to imagine a reality in which artificial intelligence (AI) could penetrate every corner of our lives to monitor our innermost selves for commercial interests. Within just a few decades, the private sector has seen a wild proliferation of AI systems, many of which are more powerful and penetrating than anticipated. In many cases, AI systems have become “the power behind the throne,” tracking user activities and making fateful decisions through predictive analysis of personal information. Despite the growing power of AI, proprietary algorithmic systems can be technically complex, legally claimed as trade secrets, and managerially …

Using Ai To Reduce Performance Risk In U.S. Procurement, Jessica Tillipman

GW Law Faculty Publications & Other Works

In recent years, several U.S. government agencies have pioneered the use of artificial intelligence (AI) and other emerging technologies to improve the efficiency and accuracy of their "responsibility determinations" (reviews of, among other things, contractor representations and certifications, past performance history, civil and criminal settlements, exclusions (such as suspensions or debarments), and contract terminations). As federal agencies continue to think strategically about how to improve processes and reduce risk in their procurements, technology-driven solutions will play a critical role in this undertaking.

Antitrust By Algorithm, Cary Coglianese, Alicia Lai

All Faculty Scholarship

Technological innovation is changing private markets around the world. New advances in digital technology have created new opportunities for subtle and evasive forms of anticompetitive behavior by private firms. But some of these same technological advances could also help antitrust regulators improve their performance in detecting and responding to unlawful private conduct. We foresee that the growing digital complexity of the marketplace will necessitate that antitrust authorities increasingly rely on machine-learning algorithms to oversee market behavior. In making this transition, authorities will need to meet several key institutional challenges—building organizational capacity, avoiding legal pitfalls, and establishing public trust—to ensure successful …

Artificial Intelligence Accountability Of Public Administration, Francesca Bignami

GW Law Faculty Publications & Other Works

This article canvasses the use and regulation of artificial intelligence (AI) in US administrative agencies. It is structured as a reply to the questionnaire circulated in advance of the 2022 International Congress of Comparative Law for purposes of preparing the national reports and the general report on the topic of “Artificial Intelligence Accountability of Public Administration.” In large part, the questionnaire’s point of reference is the comprehensive regulation of AI in the European Union’s proposed AI Act. The US reply, contained in this article, highlights the many lacunae in US regulation of AI, similar to the US’s patchwork approach to …