Law Commons^™

The Legal Imitation Game: Generative Ai’S Incompatibility With Clinical Legal Education, Jake Karr, Jason Schultz

Fordham Law Review

In this Essay, we briefly describe key aspects of [generative artificial intelligence] that are particularly relevant to, and raise particular risks for, its potential use by lawyers and law students. We then identify three foundational goals of clinical legal education that provide useful frameworks for evaluating technological tools like GenAI: (1) practice readiness, (2) justice readiness, and (3) client-centered lawyering. First is “practice readiness,” which is about ensuring that students have the baseline abilities, knowledge, and skills to practice law upon graduation. Second is “justice readiness,” a concept proposed by Professor Jane Aiken, which is about teaching law students to …

Critical Data Theory, Margaret Hu

William & Mary Law Review

Critical Data Theory examines the role of AI and algorithmic decisionmaking at its intersection with the law. This theory aims to deconstruct the impact of AI in law and policy contexts. The tools of AI and automated systems allow for legal, scientific, socioeconomic, and political hierarchies of power that can profitably be interrogated with critical theory. While the broader umbrella of critical theory features prominently in the work of surveillance scholars, legal scholars can also deploy criticality analyses to examine surveillance and privacy law challenges, particularly in an examination of how AI and other emerging technologies have been expanded in …

The Copyright Requirement Of Human Authorship For Works Containing Artificial Intelligence-Generated Content, Runhua Wang

IP Theory

The U.S. Copyright Office (the “Office”) unwaveringly refuses to register copyrights for artworks created by artificial intelligence (“AI”) systems. The prima facie reason is a lack of authorship because the U.S. copyright regime recognizes only humans as authors. However, the fundamental reason lies in the fact that legislators have not yet determined whether to grant copyrights to AI users. Despite adjustments made by the Office in response to the use of AI systems in creation, the agency’s implementation of copyright statutes suggests that it remains extremely conservative, rejecting any AI-generated content (“AIGC”) from copyright registration.

Will the copyright regime continue …

Code And Prejudice: Regulating Discriminatory Algorithms, Bernadette M. Coyle

Washington and Lee Law Review Online

In an era dominated by efficiency-driven technology, algorithms have seamlessly integrated into every facet of daily life, wielding significant influence over decisions that impact individuals and society at large. Algorithms are deliberately portrayed as impartial and automated in order to maintain their legitimacy. However, this illusion crumbles under scrutiny, revealing the inherent biases and discriminatory tendencies embedded in ostensibly unbiased algorithms. This Note delves into the pervasive issues of discriminatory algorithms, focusing on three key areas of life opportunities: housing, employment, and voting rights. This Note systematically addresses the multifaceted issues arising from discriminatory algorithms, showcasing real-world instances of algorithmic …

Our Changing Reality: The Metaverse And The Importance Of Privacy Regulations In The United States, Anushkay Raza

Global Business Law Review

This Note discusses the legal and pressing digital challenges that arise in connection with the growing use of virtual reality, and more specifically, the metaverse. As this digital realm becomes more integrated into our daily lives, the United States should look towards creating a federal privacy law that protects fundamental individual privacy rights. This Note argues that congress should emulate the European Union's privacy regulations, and further, balances the potential consequences and benefits of adapting European regulations within the United Sates. Finally, this Note provides drafting considerations of future lawyers who will not only be dealing with the rise of …

The First Byte Rule: A Proposal For Liability Of Artificial Intelligences, Hilyard Nichols

William & Mary Business Law Review

Artificial Intelligences (AIs) are a relatively new addition to human civilization. From delivery robots to board game champions, researchers and businesses have found a variety of ways to apply this new technology. As it continues to grow and become more prevalent, though, so do its interactions with society at large. This will create benefits for people, through cheaper or better products and services. It also has the possibility to create harm. AIs are not perfect, and as the range of AI uses grows, so will the range of potential harms. A mistake from an AI customer service bot could fraudulently …

Regulation Priorities For Artificial Intelligence Foundation Models, Matthew R. Gaske

Vanderbilt Journal of Entertainment & Technology Law

This Article responds to the call in technology law literature for high-level frameworks to guide regulation of the development and use of Artificial Intelligence (AI) technologies. Accordingly, it adapts a generalized form of the fintech Innovation Trilemma framework to argue that a regulatory scheme can prioritize only two of three aims when considering AI oversight: (1) promoting innovation, (2) mitigating systemic risk, and (3) providing clear regulatory requirements. Specifically, this Article expressly connects legal scholarship to research in other fields focusing on foundation model AI systems and explores this kind of system’s implications for regulation priorities from the geopolitical and …

Fair’S Fair: How Public Benefit Considerations In The Fair Use Doctrine Can Patch Bias In Artificial Intelligence Systems, Patrick K. Lin

Indiana Journal of Law and Social Equality

The impact of artificial intelligence (AI) expands relentlessly despite well documented examples of bias in AI systems, from facial recognition failing to differentiate between darker-skinned faces to hiring tools discriminating against female candidates. These biases can be introduced to AI systems in a variety of ways; however, a major source of bias is found in training datasets, the collection of images, text, audio, or information used to build and train AI systems. This Article first grapples with the pressure copyright law exerts on AI developers and researchers to use biased training data to build algorithms, focusing on the potential risk …

Toward An Enhanced Level Of Corporate Governance: Tech Committees As A Game Changer For The Board Of Directors, Maria Lillà Montagnani, Maria Lucia Passador

The Journal of Business, Entrepreneurship & the Law

Although tech committees are increasingly being included in the functioning of the board of directors, a gap exists in the current literature on board committees, as it tends to focus on traditional board committees, such as nominating, auditing or remuneration ones. Therefore, this article performs an empirical analysis of tech committees adopted by North American and European listed companies in 2019 in terms of their composition, characteristics and functions. The aim of the study is to understand what “technology” really stands for in the “tech committees” label within the board, or – to phrase it differently – to ascertain what …

The Perks Of Being Human, Max Stul Oppenheimer

Washington and Lee Law Review Online

The power of artificial intelligence has recently entered the public consciousness, prompting debates over numerous legal issues raised by use of the tool. Among the questions that need to be resolved is whether to grant intellectual property rights to copyrightable works or patentable inventions created by a machine, where there is no human intervention sufficient to grant those rights to the human. Both the U. S. Copyright Office and the U. S. Patent and Trademark Office have taken the position that in cases where there is no human author or inventor, there is no right to copyright or patent protection. …

Exams In The Time Of Chatgpt, Margaret Ryznar

Washington and Lee Law Review Online

Invaluable guidance has emerged regarding online teaching in recent years, but less so concerning online and take-home final exams. This article offers various methods to administer such exams while maintaining their integrity—after asking artificial intelligence writing tool ChatGPT for its views on the matter. The sophisticated response of the chatbot, which students can use in their written work, only raises the stakes of figuring out how to administer exams fairly.

Regulating Uncertain States: A Risk-Based Policy Agenda For Quantum Technologies, Tina Dekker, Florian Martin-Bariteau

Canadian Journal of Law and Technology

Many countries are taking a national approach to developing quantum strategies with a strong focus on innovation. However, societal, ethical, legal, and policy considerations should not be an afterthought that is pushed aside by the drive for innovation. A responsible, global approach to quantum technologies that considers the legal, ethical, and societal dimensions of quantum technologies is necessary to avoid exacerbating existing global inequalities. Quantum technologies are expected to disrupt other transformative technologies whose legal landscape is still under development (e.g., artificial intelligence [‘‘AI”], blockchain, etc.). The shortcomings of global policies regarding AI and the digital context teach lessons that …

Recognizing Operators’ Duties To Properly Select And Supervise Ai Agents – A (Better?) Tool For Algorithmic Accountability, Richard Zuroff

Canadian Journal of Law and Technology

In November of 2020, the Privacy Commissioner of Canada proposed creating GDPR-inspired rights for decision subjects and allowing financial penalties for violations of those rights. Shortly afterward, the proposal to create a right to an explanation for algorithmic decisions was incorporated into Bill C-11, the Digital Charter Implementation Act. This commentary proposes that creating duties for operators to properly select and supervise artificial agents would be a complementary, and potentially more effective, accountability mechanism than creating a right to an explanation. These duties would be a natural extension of employers’ duties to properly select and retain human employees. Allowing victims …

The Need For An Australian Regulatory Code For The Use Of Artificial Intelligence (Ai) In Military Application, Sascha-Dominik Dov Bachmann, Richard V. Grant

American University National Security Law Brief

Artificial Intelligence (AI) is enabling rapid technological innovation and is ever more pervasive, in a global technological eco-system lacking suitable governance and absence of regulation over AI-enabled technologies. Australia is committed to being a global leader in trusted secure and responsible AI and has escalated the development of its own sovereign AI capabilities. Military and Defence organisations have similarly embraced AI, harnessing advantages for applications supporting battlefield autonomy, intelligence analysis, capability planning, operations, training, and autonomous weapons systems. While no regulation exists covering AI-enabled military systems and autonomous weapons, these platforms must comply with International Humanitarian Law, the Law of …

Vicarious Liability For Ai, Mihailis E. Diamantis

Indiana Law Journal

When an algorithm harms someone—say by discriminating against her, exposing her personal data, or buying her stock using inside information—who should pay? If that harm is criminal, who deserves punishment? In ordinary cases, when A harms B, the first step in the liability analysis turns on what sort of thing A is. If A is a natural phenomenon, like a typhoon or mudslide, B pays, and no one is punished. If A is a person, then A might be liable for damages and sanction. The trouble with algorithms is that neither paradigm fits. Algorithms are trainable artifacts with “off” switches, …

Big Data Affirmative Action, Peter N. Salib

Northwestern University Law Review

As a vast and ever-growing body of social-scientific research shows, discrimination remains pervasive in the United States. In education, work, consumer markets, healthcare, criminal justice, and more, Black people fare worse than whites, women worse than men, and so on. Moreover, the evidence now convincingly demonstrates that this inequality is driven by discrimination. Yet solutions are scarce. The best empirical studies find that popular interventions—like diversity seminars and antibias trainings—have little or no effect. And more muscular solutions—like hiring quotas or school busing—are now regularly struck down as illegal. Indeed, in the last thirty years, the Supreme Court has invalidated …

Deepfake Fight: Ai-Powered Disinformation And Perfidy Under The Geneva Conventions, David Nicholas Allen

Notre Dame Journal on Emerging Technologies

Deception and disinformation are as much a part of the battlefield as bullets and bombs. However, just like with bullets and bombs, if the law does not properly regulate a capability’s use the capability could degrade faith in the law. In this respect, this paper examines deepfake technology, a modern artificial intelligence-based capability that can generate superficially-perfect yet wholly invented media content. The paper looks ahead to its potential future applications in armed conflict, processes the ways in which current law contemplates such deception, and distills recommendations for improving governance where needed.

In Defense Of (Virtuous) Autonomous Weapons, Don Howard

Notre Dame Journal on Emerging Technologies

I will argue, we can construct effective means for norming the use of autonomous weapons short of a total ban by building upon the foundation of existing requirements stipulated in Article 36 of Protocol I to the Geneva Conventions that all new weapons technologies be reviewed for compliance with the International Law of Armed Conflict (ILOAC) and International Humanitarian Law (IHL). I begin with a critical review of several of the most commonly encountered arguments in favor of a ban. That is followed by a discussion of the moral opportunities afforded by enhanced autonomy. I conclude with a concrete policy …

Ethical Ai In American Policing, Elizabeth E. Joh

Notre Dame Journal on Emerging Technologies

We know there are problems in the use of artificial intelligence in policing, but we don’t quite know what to do about them. One can also find many reports and white papers today offering principles for the responsible use of AI systems by the government, civil society organizations, and the private sector. Yet, largely missing from the current debate in the United States is a shared framework for thinking about the ethical and responsible use of AI that is specific to policing. There are many AI policy guidance documents now, but their value to the police is limited. Simply repeating …

Note: Regulating Artificial Intelligence: A Call For A United States Artificial Intelligence Agency, Noah John Kahekili Rosenberg

Notre Dame Journal on Emerging Technologies

this Note draws upon two examples of emerging AI technologies that demonstrate the need for federal regulation: autonomous vehicles (i.e., self-driving cars) and algorithm-based hiring software. Part I illustrates the public safety concerns associated with AI technologies by outlining the inadequacy of existing laws and regulations on autonomous vehicles. Part II addresses the shortcomings of current regulations on algorithm-based hiring software and the issue of discrimination and inherent bias in AI. Part III recommends the creation of a new federal agency to guide AI regulation and enforcement.

Arbitral Analytics: How Moneyball Based Litigation/Judicial Analytics Can Be Used To Predict Arbitration Claims And Outcomes, Benjamin Davies

Pepperdine Dispute Resolution Law Journal

This paper reviews, discusses, and advances the field of artificial intelligence in the field of litigation analytics and its application to arbitrations. To better explain the weight an attorney, judge, arbitrator, or the public should have towards artificial intelligence and its utilization in the legal field, this paper reviews current AI publications in the litigation analytics field, historical examples, ethical considerations for analytics, and issues surrounding the accumulation of litigation data. Thereafter, this combined knowledge and experience is applied to Federal Industry Regulatory Authority (FINRA) arbitration awards with a novel AI program designed to scrape, index, and analyze these awards …

The Future Of Ai Accountability In The Financial Markets, Gina-Gail S. Fletcher, Michelle M. Le

Vanderbilt Journal of Entertainment & Technology Law

Consumer interaction with the financial market ranges from applying for credit cards, to financing the purchase of a home, to buying and selling securities. And with each transaction, the lender, bank, and brokerage firm are likely utilizing artificial intelligence (AI) behind the scenes to augment their operations. While AI’s ability to process data at high speeds and in large quantities makes it an important tool for financial institutions, it is imperative to be attentive to the risks and limitations that accompany its use. In the context of financial markets, AI’s lack of decision-making transparency, often called the “black box problem,” …

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

William & Mary Bill of Rights Journal

We consider this issue here and suggest that the current calls for a negative right to be free from AI could very well transform over time into positive claims that demand the use of algorithmic tools by government officials. In Part I, we begin by sketching the current landscape surrounding the adoption of AI by government. That landscape is characterized by strong activist and scholarly voices expressing a pronounced aversion to the use of digital algorithms—and taking a decidedly negative rights tone. In Part II, we show that, although aversion to complex technology might be understandable, that aversion is neither …

Distributed Governance Of Medical Ai, W. Nicholson Price Ii

SMU Science and Technology Law Review

Artificial intelligence (AI) has the potential to democratize expertise in medicine, bring expertise previously limited to specialists to a variety of health-care settings. But AI can easily falter, and making sure that AI works well across that variety of settings is a challenging task. Centralized governance, such as review by the Food and Drug Administration, can only do so much, since system performance will depend on the particular health-care setting and how the AI system is integrated into setting-specific clinical workflows. This Essay presents the need for distributed governance, where some oversight tasks are undertaken in localized settings. It points …

Moving From Harm Mitigation To Affirmative Discrimination Mitigation: The Untapped Potential Of Artificial Intelligence To Fight School Segregation And Other Forms Of Racial Discrimination, Andrew Gall

Catholic University Journal of Law and Technology

No abstract provided.

Artificial Intelligence In Canadian Healthcare: Will The Law Protect Us From Algorithmic Bias Resulting In Discrimination?, Bradley Henderson, Colleen M. Flood, Teresa Scassa

Canadian Journal of Law and Technology

In this article, we canvas why AI may perpetuate or exacerbate extant discrimination through a review of the training, development, and implementation of healthcare-related AI applications and set out policy options to militate against such discrimination. The article is divided into eight short parts including this introduction. Part II focuses on explaining AI, some of its basic functions and processes, and its relevance to healthcare. In Part III, we define and explain the difference and relationship between algorithmic bias and data bias, both of which can result in discrimination in healthcare settings, and provide some prominent examples of healthcare-related AI …

The Ratio Method: Addressing Complex Tort Liability In The Fourth Industrial Revolution, Harrison C. Margolin, Grant H. Frazier

St. Mary's Law Journal

Emerging technologies of the Fourth Industrial Revolution show fundamental promise for improving productivity and quality of life, though their misuse may also cause significant social disruption. For example, while artificial intelligence will be used to accelerate society’s processes, it may also displace millions of workers and arm cybercriminals with increasingly powerful hacking capabilities. Similarly, human gene editing shows promise for curing numerous diseases, but also raises significant concerns about adverse health consequences related to the corruption of human and pathogenic genomes.

In most instances, only specialists understand the growing intricacies of these novel technologies. As the complexity and speed of …

Deep Fakes: The Algorithms That Create And Detect Them And The National Security Risks They Pose, Nick Dunard

James Madison Undergraduate Research Journal (JMURJ)

The dissemination of deep fakes for nefarious purposes poses significant national security risks to the United States, requiring an urgent development of technologies to detect their use and strategies to mitigate their effects. Deep fakes are images and videos created by or with the assistance of AI algorithms in which a person’s likeness, actions, or words have been replaced by someone else’s to deceive an audience. Often created with the help of generative adversarial networks, deep fakes can be used to blackmail, harass, exploit, and intimidate individuals and businesses; in large-scale disinformation campaigns, they can incite political tensions around the …

How Can I Tell If My Algorithm Was Reasonable?, Karni A. Chagal-Feferkorn

Michigan Technology Law Review

Self-learning algorithms are gradually dominating more and more aspects of our lives. They do so by performing tasks and reaching decisions that were once reserved exclusively for human beings. And not only that—in certain contexts, their decision-making performance is shown to be superior to that of humans. However, as superior as they may be, self-learning algorithms (also referred to as artificial intelligence (AI) systems, “smart robots,” or “autonomous machines”) can still cause damage.

When determining the liability of a human tortfeasor causing damage, the applicable legal framework is generally that of negligence. To be found negligent, the tortfeasor must have …

Natural Language Processing For Lawyers And Judges, Frank Fagan

Michigan Law Review

A Review of Law as Data: Computation, Text, & the Future of Legal Analysis. Edited by Michael A. Livermore and Daniel N. Rockmore.