Science and Technology Law Commons^™

How Ai Destroys Institutions, Woodrow Hartzog, Jessica Silbey

Faculty Scholarship

Civic institutions—the rule of law, universities, and a free press—are the backbone of democratic life. They are the mechanisms through which complex societies encourage cooperation and stability, while also adapting to changing circumstances. The real superpower of institutions is their ability to evolve and adapt within a hierarchy of authority and a framework for roles and rules, while maintaining legitimacy for the knowledge produced and the actions taken. Purpose-driven institutions built around transparency, cooperation, and accountability empower individuals to take intellectual risks and challenge the status quo. This happens through the machinations of interpersonal relationships within those institutions, which broaden …

Ai Mistakes: "Confabulation" And Abduction, Not "Hallucination", Stephen M. Mcjohn, Ian Mcjohn

Suffolk University Law School Faculty Works

"Hallucination" has become the common term for errors by AI systems, yet it implies a misleading analogy to human perception. LLM's process tokens. They do not have conscious experience or conscious perception. A hallucination is an experience, and (to our knowledge, to date) LLM's do not experience anything. This paper suggests that legal scholars follow the lead of a small number of AI researchers who have suggested that "confabulation" is a more accurate term, a metaphor grounded in psychology. People confabulate when they unknowingly invent spurious explanations or facts. We then take this terminological question and stretch it into a …

Confidentiality Of Ai Conversations: Protecting Self-Represented Litigants Who Use Chatgpt For Legal Advice, Anoo D. Vyas

Duke Law & Technology Review

When a layperson uses ChatGPT to obtain feedback on a legal matter, attorney-client privilege may not apply, as ChatGPT is not a lawyer, much less a human. Further, while lawyers are entitled to protection for their opinion work-product, it is not clear whether self-represented litigants are entitled to the same protection. Additionally, the broader duty of confidentiality binds only attorneys, not AI systems like ChatGPT. The public increasingly uses AI tools such as ChatGPT. If a layperson employs ChatGPT for legal advice, particularly in a civil matter, such communications may be discoverable and potentially admissible. This presents an access to …

Advice For Incorporating Ai Tools Into Your Legal Practice, Celia Bigoness, Robert A. Mackenzie, David J. Reiss

Cornell Law Faculty Publications

We have been speaking with many lawyers and law students about using generative artificial intelligence (AI) tools in their legal practice. We are struck by the fact that many of them have not been experimenting much, if at all, with the tools that are available to them - although many acknowledge that their clients are increasingly integrating generative AI into their businesses. We have been integrating a lot of these tools into our own professional lives, and here are some tips to help lawyers and law students get comfortable with AI tools that can help them, in big ways and …

Grading Machines: Can Ai Exam-Grading Replace Law Professors?, Kevin L. Cope, Jen Frankenreiter, Scott Hirst, Eric A. Posner, Daniel Schwarcz, Dane Thorley

Faculty Scholarship

In the past few years, large language models (LLMs) have achieved significant technical advances, such that legal-advocacy organizations are increasingly adopting them as complements to—or substitutes for—lawyers and other human experts. Several studies have examined LLMs' performance in taking law school exams, finding mixed results. Yet there have been no published studies systematically analyzing LLMs' competence at one of law professors' chief responsibilities: grading law school exams. This paper presents results of an analysis of how LLMs perform in evaluating student responses to legal analysis questions of the kind typically administered in law school exams. The underlying data come from …

Friend Or Foe? Generative Ai And Legal Writing, Peter Nemerovski

Maine Law Review

Much has been made in recent years of the capabilities of generative artificial intelligence ("Generative AI") programs in performing law-related tasks. We have learned, for example, that OpenAI's product, GPT-4, is capable of passing the Uniform Bar Exam with flying colors. ChatGPT also earned passing grades on the final exams in four different law school courses. Another study found that "AI assistance consistently induced large declines in the amount of time taken to complete tasks" like drafting complaints, contracts, and employee handbook sections. These and other success stories have led commentators to predict that Generative AI programs "will revolutionize what …

The Business Of Ai-Producing Startups: Evidence From A Worldwide Survey, James Bessen, Stephen Michael Impink, Robert Seamans

Faculty Scholarship

We report results from a multi-year, worldwide survey of artificial intelligence (AI)-producing startups to describe the types of technologies, frameworks, data protection, and partnerships nascent firms use to develop their AI products. Analyses of our survey findings also inform how startups gather the resources to commercialize their AI applications in alignment with their entrepreneurial strategies, address competitive barriers, and respond to regulations. These data provide initial evidence of the perceived impact of these products on their customers’ tasks and industries, suggesting that these firms’ AI products not only reduce labor costs but augment human capabilities.

Ethics Of Artificial Intelligence For Lawyers: Resistance Is Futile: Candor, Supervision, And Fees, Cliff Mckinney

Arkansas Law Notes

In Star Trek: The Next Generation, the Borg deliver their iconic warning to every species they encounter: “Resistance is futile.” The line resonates because it conveys the inevitability that once the Borg arrive, escape is no longer an option.

For lawyers, the duties of candor, supervision, and fairness in fees are just as inescapable. ABA Formal Opinion 512 (“ABA Opinion”) makes clear that, regardless of how powerful artificial intelligence becomes, it cannot relieve attorneys of their obligation. Attorneys must verify what they file, oversee how their colleagues use the technology, and ensure that clients are charged fairly. This installment examines …

Ethics Of Artificial Intelligence For Lawyers: You Will Be Assimilated: Best Practices For Lawyers Using Artificial Intelligence, Cliff Mckinney

Arkansas Law Notes

In Star Trek: The Next Generation, the Borg, a species augmented with artificial intelligence, give a chilling ultimatum to every civilization they encounter: “You will be assimilated.” The warning is terrifying because it suggests not destruction, but absorption with the loss of independence to a relentless collective.

For lawyers, the rise of artificial intelligence carries a similar threat of assimilation. Artificial intelligence is already entering law practice, whether lawyers welcome it or not. The real question is not if lawyers will be assimilated into a future integrated with artificial intelligence, but how they will use these tools without sacrificing judgment, …

Ethics Of Artificial Intelligence For Lawyers: That Is The Sound Of Inevitability: Legislatures And Regulators Step In, Cliff Mckinney

Arkansas Law Notes

In The Matrix, the evil artificial intelligence entity, Agent Smith, corners the human hero, Neo, on the subway tracks. Agent Smith says, “You hear that Mr. Anderson? . . . That is the sound of inevitability. . . .” And if there is one thing that is inevitable, it is that regulations will quickly develop around the way that we interact with and utilize artificial intelligence.

No matter how innovative or disruptive artificial intelligence may be, lawmakers and regulators will not allow it to operate unchecked. Congress recently elected not to impose a moratorium on state regulation, and California has …

Shifting Structural Power: The Tech Energy Transition, Amy L. Stein

UF Law Faculty Publications

For the first time in over a decade, flat and stagnant electricity demand is expected to skyrocket. This increased demand is driven in large part by data centers that support artificial intelligence, crypto mining, and cloud computing. This is straining the electric grid, its stakeholders, and legal constructs in significant ways. Legal energy scholarship has spent the last fifteen years focused on the challenges of managing an electric grid transitioning to clean energy, in a world where privately owned electric utilities maintain powerful monopolies across the country. But there are no accounts of how the balance of power in this …

Ai Can't Adlib: Theorizing An Improvisation Carveout In The Work For Hire Doctrine, Audrey Pope

IP Theory

AI-generated actors and digital replicas are an increasingly pressing concern in the filmmaking industry. While this technology is only one of the myriad ways that generative AI is set to change Hollywood, debates about its use reflect a throughline in debates about AI generally: Can this technology do a convincing, much less desirable, job of what humans have done before? This Article argues that, at least in one particular context, the answer is no. It focuses on the art of adlibbing. It explains the unique position of improvisation within copyright law and proposes one mechanism—a carveout in the work for …

Artificial Elections: How Artificial Intelligence Can Affect Elections And Decide Our Future, Ryan D. Granger

Honors Undergraduate Theses

This thesis examines the growing role of artificial intelligence (AI) in democratic elections, highlighting both its transformative potential and its associated risks. Drawing on a qualitative analysis of existing literature, the study explores how AI is increasingly integrated into political campaigns, election administration, and voter engagement. Key benefits include enhanced data analysis, personalized political messaging, and improved efficiency in campaign operations. AI also supports real-time fact-checking and more accurate vote tabulation, which can strengthen transparency and trust in electoral processes. However, the thesis emphasizes that these advantages are accompanied by significant challenges. AI technologies enable the rapid creation and dissemination …

Against Ai Half Measures, Woodrow Hartzog, Neil Richards, Ryan Durrie, Jordan Francis

Faculty Scholarship

So far, U.S. consumer protection policy for artificial intelligence (AI) accountability has largely consisted of industry-led approaches such as encouraging transparency, mitigating bias, promoting principles of ethics, and empowering people. These approaches are vital, but they are only half measures. To bring AI within the rule of law, lawmakers must start drawing substantive lines.

In this Article, we identify four AI regulatory approaches to consumer, data, and democratic harms as half measures. First, transparency does not produce accountability on its own. Second, while mitigating bias in AI systems is critical, even unbiased systems are a threat to the vulnerable. Third, …

A Bottom-Up Approach To Ai Facial Recognition Technology Wrongful Arrests And Subsequent 42 U.S.C. § 1983 Actions, Marty Ishmael

University of Cincinnati Law Review

No abstract provided.

The Role Of Artificial Intelligence In Reducing Internet Crimes Against Children, Malyssa Shaw

Student Scholar Symposium Abstracts and Posters

When generative artificial intelligence (AI) first surfaced and broke into the public sphere, my immediate concern was in its development, implementation, and harmful applications. I was not surprised when deepfake technology rapidly advanced alongside these new developments and impacted women and children worldwide. Disproportionately, they have been made victims of intimate media forgery as early as the 1990s, with an unprecedented uptick in recent years as a direct result of these developments. In response, I wrote "Deepfake, Real Harm: Protecting Children in the Age of AI", analyzing data specifically regarding child sexual abuse material (CSAM) created with artificial intelligence while …

Data As Policy, Janet Freilich, W. Nicholson Price Ii

Faculty Scholarship

A large literature on regulation highlights the many different methods of policy-making: command-and-control rulemaking, informational disclosures, tort liability, taxes, and more. But the literature overlooks a powerful method to achieve policy objectives: data. The state can provide (or suppress) data as a regulatory tool to solve policy problems. For administrations with expansive views of government’s purpose, government-provided data can serve as infrastructure for innovation and push innovation in socially desirable directions; for administrations with deregulatory ambitions, suppressing or choosing not to collect data can reduce regulatory power or serve as a back-door mechanism to subvert statutory or common law rules. …

Attorneys And Ai: How Lawyers Use Artificial Intelligence And Analyze Its Impacts, Matthew I. Hall, Christian Turner, Eddie A. Gomez Schieber, Nathaniel Kite, Ari Schlesinger

Scholarly Works

AI systems are testing lawyers' professional ethics obligations of competence, confidentiality, and candor. In the legal profession, the widespread availability of AI systems presents opportunities, like improving the review of documents during the discovery stage of a lawsuit, and challenges, illustrated by the handful of high-profile incidents where lawyers submitted legal briefs in court citing and describing fictitious cases based on AI-generated output. We conducted interviews with 44 legal professionals in the U.S. to understand how attorneys are making sense of AI technology and the impacts these technologies are having on their profession, legal ethics, and legal institutions. We describe …

An Out-Of-The-Block Solution For Modern Ip Law: How Pairing Generative Ai With Blockchain Could Resolve Copyright Conflicts, Emma Wozniak

University of Cincinnati Law Review

No abstract provided.

Governance In The Absence Of Government, Tracy Hresko Pearl

Faculty Articles

Artificial intelligence (AI) is advancing at an unprecedented pace, with generative systems exerting growing influence over social, economic, and political life. While Al offers opportunities for innovation and efficiency, it also poses risks ranging from misinformation and job displacement to existential threats if highly autonomous systems evade human control. Across industry, government, and civil society, there is broad consensus that Al requires oversight.

Yet traditional U.S. regulatory approaches face six significant barriers: (1) technology outpacing legislation, (2) limited Al expertise among policymakers, (3) regulatory capture, (4) political gridlock, (5) outdated governance structures, and (6) the inherent complexity of Al. Combined …

The Sec Proposed Cybersecurity Infrastructure Rules And New Disclosure Requirements, Neal F. Newman, Lawrence J. Trautman, Brian Elzweig

Faculty Scholarship

In addition to regulation of securities market issuers, the Securities & Exchange Commission (SEC) is also responsible for regulation of those entities that provide the networks, either electronic or physical, that enable the functioning of our securities markets. On February 9, 2022, the Commission published a Release for Cybersecurity Risk Management for Investment Advisers, Registered Investment Companies, and Business Development Companies containing proposals that, if adopted, would establish a new cybersecurity incident reporting and disclosure regime and require registered investment advisers (“advisers”) and investment companies (“funds”) to implement policies and procedures designed to address cyber risks. The comment period for …

Are Ai-Assisted Drug Technologies Addressing Or Aggravating The Opioid Crisis In The United States?, Abby O'Hern

West Virginia Law Review

The opioid crisis is a significant public health emergency, intensified by the rise of synthetic opioids such as fentanyl. Lawmakers have described fentanyl as “terroristic in nature” due to its often-fatal properties. According to the Center for Disease Control (“CDC”), an estimated 107,543 people died from drug overdoses in the United States in 2023. As fentanyl use has surged, it has increasingly shaped public health policy through harm reduction initiatives, expanded addiction treatment resources, and legislative reforms aimed at curbing overdose deaths. Artificial Intelligence (“AI”) now plays a dual role in this evolving crisis. While AI technologies offer valuable tools …

What 2 Profs Noticed As Transactional Law Students Used Ai, Celia Bigoness, David Reiss

Cornell Law Faculty Publications

We teach entrepreneurship law clinics in which our students do transactional work on a wide range of matters, including business formation, contracts, intellectual property protection and regulatory compliance.

This past semester, we had access to generative artificial intelligence tools from Lexis, Westlaw and Bloomberg Law, as well as those that are more broadly available to the general public, including ChatGPT and Perplexity.

While we have not done a rigorous study of these tools, we have some early observations about how AI is changing how transactional lawyers do their jobs, particularly new transactional lawyers. Our own experience has been mostly positive, …

The Use Of Ai In Canadian Courts, Shaughnessy Dow

Dalhousie Journal of Legal Studies

Like many other fields, there has been growing discussion about the potential benefits of AI for the law. In light of the Federal Court’s interim principles and guidelines on the use of AI, this paper considers whether AI applications can assist the judiciary with its decision-making function. In doing so, it starts by considering the role that judges play in our legal system, finding that they are often called upon to consider and weigh information with human, emotional qualities and to assess the broader policy implications of their legal rulings. This paper concludes that the optimism of proponents of AI …

Can We Train Bots To Negotiate Like Lawyers? And What Do We Learn About Bargaining As We Do?, Dwight Golann

Suffolk University Law School Faculty Works

Forthcoming in 79 Wash. U. J. of Law and Policy ____ (2025)

AI “bots” like ChatGPT can negotiate without training, but they are overly cooperative, making concessions that weaken their bargaining position—unlike skilled legal negotiators, who adapt their tactics to individual situations as well as what occurs in the process and move as needed between cooperative and competitive tactics.

The article explores how to train bots to “negotiate like lawyers” by giving them role instructions, knowledge about bargaining, and iterative practice, including step-by-step instructions to create a bargaining bot in ChatGPT.

The author notes that texts on negotiation, and his …

Stranger Disputes: When Artificial Intelligence Turns Arbitration Upside Down, Imre Stephen Szalai

Pepperdine Dispute Resolution Law Journal

Arbitration agreements are everywhere in the United States. These agreements already block access to courts in a troubling manner, and pursuant to these agreements, parties must resolve their disputes before a private, human arbitrator with broad, virtually unreviewable powers. However, with the growth of AI, companies could easily redraft their contracts to require arbitration before non-human bots or AI arbitrators instead of a human arbitrator. Based on the history, values, policy, and text of the Federal Arbitration Act (FAA), this Article concludes that the FAA would govern and support the use of an AI arbitrator. As a result, a pre-dispute …

Multiplicity As An Ai Governance Principle, Michal Shur-Ofry

Indiana Law Journal

As AI becomes increasingly embedded in our daily lives, this Article explores one of its critical, yet overlooked, societal implications: the propensity of large language models (LLMs) to generate mainstream, standardized content, potentially narrowing their users’ worldviews.

Taking a close look at the technological underpinnings of LLMs, the analysis suggests that—due to the combination of human judgments, training datasets, and inherent features of the underlying technological paradigm—LLMs’ outputs are likely to be geared toward the popular and to project to their users concentrated, mainstream worldviews, sidelining a broader spectrum of perspectives. This Article explores the asymmetrical power relations between LLMs …

Can Ai, As Such, Invade Your Privacy? An Experimental Study Of The Social Element Of Surveillance, Aileen Nielsen

Indiana Law Journal

The increasing use of AI rather than human surveillance puts pressure on two long-used cultural and (sometimes) legal distinctions: as between human and machine observers and as between content and metadata. Machines do more and more watching through advancing technology, rendering AI a plausible replacement for humans in surveillance tasks. Further, machines can commit to surveil only certain forms of information in a way that humans cannot, rendering the distinction between content and metadata increasingly relevant too for crafting privacy law and policy. Yet despite the increasing importance of these distinctions, their legal importance remains in four key domains of …

The Mirage Of Artificial Intelligence Terms Of Use Restrictions, Peter Henderson, Mark A. Lemley

Indiana Law Journal

Artificial intelligence (AI) model creators commonly attach restrictive terms of use to both their models and their outputs. These terms typically prohibit activities ranging from creating competing AI models to spreading disinformation. Often taken at face value, these terms are positioned by companies as key enforceable tools for preventing misuse, particularly in policy dialogs. The California AI Transparency Act even codifies this approach, mandating certain responsible use terms to accompany models.

But are these terms truly meaningful, or merely a mirage? There are myriad examples where these broad terms are regularly and repeatedly violated. Yet except for some account suspensions …

The Overstated Cost Of Ai Fairness In Criminal Justice, Ignacio Cofone, Warut Khern-Am-Nuai

Indiana Law Journal

The dominant critique of algorithmic fairness in AI decision-making, particularly in criminal justice, is that increasing fairness reduces the accuracy of predictions, thereby imposing a cost on society. This Article challenges that assumption by empirically analyzing the COMPAS algorithm, a widely used and widely discussed risk assessment tool in the U.S. criminal justice system.

This Article makes two contributions. First, it demonstrates that widely used AI models do more than replicate existing biases—they exacerbate them. Using causal inference methods, we show that racial bias is not only present in the COMPAS dataset but also worsened by AI models such as …