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Articles 1 - 6 of 6
Full-Text Articles in Law
Regulation Priorities For Artificial Intelligence Foundation Models, Matthew R. Gaske
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
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 …
The Data Trust Solution To Data Sharing Problems, Kimberly A. Houser, John W. Bagby
The Data Trust Solution To Data Sharing Problems, Kimberly A. Houser, John W. Bagby
Vanderbilt Journal of Entertainment & Technology Law
A small number of large companies hold most of the world’s data. Once in the hands of these companies, data subjects have little control over the use and sharing of their data. Additionally, this data is not generally available to small and medium enterprises or organizations who seek to use it for social good. A number of solutions have been proposed to limit Big Tech “power,” including antitrust actions and stricter privacy laws, but these measures are not likely to address both the oversharing and under-sharing of personal data. Although the data trust concept is being actively explored in the …
The Death Of The Legal Subject, Katrina Geddes
The Death Of The Legal Subject, Katrina Geddes
Vanderbilt Journal of Entertainment & Technology Law
The law is often engaged in prediction. In the calculation of tort damages, for example, a judge will consider what the tort victim’s likely future earnings would have been, but for their particular injury. Similarly, when considering injunctive relief, a judge will assess whether the plaintiff is likely to suffer irreparable harm if a preliminary injunction is not granted. And for the purposes of a child custody evaluation, a judge will consider which parent will provide an environment that is in the best interests of the child.
Relative to other areas of law, criminal law is oversaturated with prediction. Almost …
Human-Centered Design To Address Biases In Artificial Intelligence, Ellen W. Clayton, You Chen, Laurie L. Novak, Shilo Anders, Bradley Malin
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. …
Returning Integrated Genomic Risk And Clinical Recommendations: The Emerge Study, Ellen W. Clayton, Jodell E. Linder, Aimee Allworth, Sara T. Bland, 100 Others...
Returning Integrated Genomic Risk And Clinical Recommendations: The Emerge Study, Ellen W. Clayton, Jodell E. Linder, Aimee Allworth, Sara T. Bland, 100 Others...
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. …