Law Commons^™

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 …

A Compulsory Solution To The Machine Problem: Recognizing Artificial Intelligence As Inventors In Patent Law, Cole G. Merritt

Vanderbilt Journal of Entertainment & Technology Law

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 …

Human-Centered Design To Address Biases In Artificial Intelligence, Ellen W. Clayton, You Chen, Laurie L. Novak, Shilo Anders, Bradley Malin

Vanderbilt Law School Faculty Publications

The potential of artificial intelligence (AI) to reduce health care disparities and inequities is recognized, but it can also exacerbate these issues if not implemented in an equitable manner. This perspective identifies potential biases in each stage of the AI life cycle, including data collection, annotation, machine learning model development, evaluation, deployment, operationalization, monitoring, and feedback integration. To mitigate these biases, we suggest involving a diverse group of stakeholders, using human-centered AI principles. Human-centered AI can help ensure that AI systems are designed and used in a way that benefits patients and society, which can reduce health disparities and inequities. …

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 …

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 …

Algorithmic Opacity, Private Accountability, And Corporate Social Disclosure In The Age Of Artificial Intelligence, Sylvia Lu

Vanderbilt Journal of Entertainment & Technology Law

Today, firms develop machine-learning algorithms to control human decisions in nearly every industry, creating a structural tension between commercial opacity and democratic transparency. In many of their commercial applications, advanced algorithms are technically complicated and privately owned, which allows them to hide from legal regimes and prevents public scrutiny. However, they may demonstrate their negative effects—erosion of democratic norms, damages to financial gains, and extending harms to stakeholders—without warning. Nevertheless, because the inner workings and applications of algorithms are generally incomprehensible and protected as trade secrets, they can be completely shielded from public surveillance. One of the solutions to this …

The Machine As Author, Daniel J. Gervais

Vanderbilt Law School Faculty Publications

Machines are increasingly good at emulating humans and laying siege to what has been a strictly human outpost: intellectual creativity.

At this juncture, we cannot know with certainty how high machines will reach on the creativity ladder when compared to, or measured against, their human counterparts, but we do know this. They are far enough already to force us to ask a genuinely hard and complex question, one that intellectual property (“IP”) scholars and courts will need to answer soon; namely, whether copyrights should be granted to productions made not by humans but by machines.

This Article’s specific objective is …

Fintech And International Financial Regulation, Yesha Yadav

Vanderbilt Law School Faculty Publications

This Article shows that fintech exacerbates the difficulties of standard setting in international financial regulation. Earlier work introduced the "Innovation Trilemma" (the Trilemma). When seeking to balance the goals of achieving market integrity and innovation through clear and simple rulemaking, regulators can-at best-achieve only two out of these three objectives. Fintech's unique characteristics- a reliance on automation and artificial intelligence, novel types of big data, as well as the use of disintermediating financial supply chains comprising a mix of traditional firms as well as technology specialists and newcomers-complicates the application of the Trilemma. Rulemaking struggles to achieve needed clarity where …

Neuroscience, Artificial Intelligence, And The Case Against Solitary Confinement, Francis X. Shen

Vanderbilt Journal of Entertainment & Technology Law

Prolonged solitary confinement remains in widespread use in the United States despite many legal challenges. A difficulty when making the legal case against solitary confinement is proffering sufficiently systematic and precise evidence of the detrimental effects of the practice on inmates' mental health. Given this need for further evidence, this Article explores how neuroscience and artificial intelligence (AI) might provide new evidence of the effects of solitary confinement on the human brain.

This Article argues that both neuroscience and AI are promising in their potential ability to present courts with new types of evidence on the effects of solitary confinement …

Topic Modeling The President: Conventional And Computational Methods, J.B. Ruhl, John Nay, Jonathan Gilligan

Vanderbilt Law School Faculty Publications

Legal and policy scholars modeling direct actions into substantive topic classifications thus far have not employed computational methods. To compare the results of their conventional modeling methods with the computational method, we generated computational topic models of all direct actions over time periods other scholars have studied using conventional methods, and did the same for a case study of environmental-policy direct actions. Our computational model of all direct actions closely matched one of the two comprehensive empirical models developed using conventional methods. By contrast, our environmental-case-study model differed markedly from the only empirical topic model of environmental-policy direct actions using …

Keeping Ai Legal, Amitai Etzioni, Oren Etzioni

Vanderbilt Journal of Entertainment & Technology Law

AI programs make numerous decisions on their own, lack transparency, and may change frequently. Hence, unassisted human agents, such as auditors, accountants, inspectors, and police, cannot ensure that AI-guided instruments will abide by the law. This Article suggests that human agents need the assistance of AI oversight programs that analyze and oversee operational AI programs. This Article asks whether operational AI programs should be programmed to enable human users to override them; without that, such a move would undermine the legal order. This Article also points out that AI operational programs provide high surveillance capacities and, therefore, are essential for …