Law Commons^™

Artificial Intelligence And Interspecific Law, Daniel J. Gervais, John J. Nay

Vanderbilt Law School Faculty Publications

Several experts have warned about artificial intelligence (AI) exceeding human capabilities, a “singularity” at which it might evolve beyond human control. Whether this will ever happen is a matter of conjecture. A legal singularity is afoot, however: For the first time, nonhuman entities that are not directed by humans may enter the legal system as a new “species” of legal subjects. This possibility of an “interspecific” legal system provides an opportunity to consider how AI might be built and governed. We argue that the legal system may be more ready for AI agents than many believe. Rather than attempt to …

Developing Ethics And Equity Principles, Terms And Engagement Tools, Ellen W. Clayton, Rachele Hendricks-Sturrup, Shilo Anders, Et Al.

Vanderbilt Law School Faculty Publications

Background:

Artificial intelligence (AI) and machine learning (ML) technology design and development continues to be rapid, despite major limitations in its current form as a practice and discipline to address all sociohumanitarian issues and complexities. From these limitations emerges an imperative to strengthen AI and ML literacy in underserved communities and build a more diverse AI and ML design and development workforce engaged in health research.

Objective:

AI and ML has the potential to account for and assess a variety of factors that contribute to health and disease and to improve prevention, diagnosis, and therapy. Here, we describe recent activities …

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 …

The National Security Case For Breaking Up Big Tech, Ganesh Sitaraman

Vanderbilt Law School Faculty Publications

In recent years, scholars, commentators, former tech company founders, and political leaders have made the case for breaking up and regulating big tech companies like Alphabet (the parent company of Google), Facebook, and Amazon. The proposals to break up and regulate big tech companies are specific: Unwind mergers, require tech platforms to separate from businesses that operate on the platform, regulate platforms with nondiscrimination principles drawn from public utilities and public accommodations laws, and adopt privacy regulations. Advocates for breaking up and regulating big tech hold that these companies have become a danger to the economy, society, and democracy. Opponents …

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 …

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 …

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 …