Law Commons^™

Can We Trust Artificial Intelligence In Criminal Law Enforcement?, Sara M. Smyth

Canadian Journal of Law and Technology

With the rapid advances made by AI in the last few years, yet with so much of it happening behind the scenes, it’s no wonder that most people are both baffled and awestruck by the capacity for these systems to render humans obsolete. Until recently, much of what the general public knew about AI, robotics, and their superhuman capabilities came from Hollywood blockbuster films like Minority Report. While it’s true that these films, in fact, provided a surprisingly realistic portrait of the capabilities that AI can now deliver, there is still a real lack of understanding on the part of …

Non-Autonomous Artificial Intelligence Programs And Products Liability: How New Ai Products Challenge Existing Liability Models And Pose New Financial Burdens, Greg Swanson

Seattle University Law Review

This Comment argues that the unique relationship between manufacturers, consumers, and their reinforcement learning AI systems challenges existing products liability law models. These traditional models inform how to identify and apportion liability between manufacturers and consumers while exposing litigants to low-dollar tort remedies with inherently high-dollar litigation costs.11 Rather than waiting for AI autonomy, the political and legal communities should be proactive and generate a liability model that recognizes how new AI programs have already redefined the relationship between manufacturer, consumer, and product while challenging the legal and financial burden of prospective consumer-plaintiffs and manufacturer-defendants.

Artificial Intelligence And Patent Ownership, W. Michael Schuster

Washington and Lee Law Review

Invention by artificial intelligence (AI) is the future of innovation. Unfortunately, as discovered through Freedom of Information Act requests, the U.S. patent regime has yet to determine how it will address patents for inventions created solely by AI (AI patents). This Article fills that void by presenting the first comprehensive analysis on the allocation of patent rights arising from invention by AI. To this end, this Article employs Coase Theorem and its corollaries to determine who should be allowed to secure these patents to maximize economic efficiency. The study concludes that letting firms using AI to create new technologies (as …

Artificial Intelligence Is Here, Get Ready!, Jessica G. Martz

Catholic University Journal of Law and Technology

No one is certain whether Artificial Intelligence (“AI”) will make the future a better place or make it look like an apocalyptic Hollywood blockbuster. An opinion that is emerging among experts and nation-state leaders is that the nation-states that lead in AI advancements and implementation will likely have a greater influence on and power over the world economic and national security stages. The goal of this book review is to encourage the reader to enter the conversation about the role AI will play in global society and American life because AI will influence the job market in the near future. …

The New Legal Landscape For Text Mining And Machine Learning, Matthew Sag

Faculty Articles

Now that the dust has settled on the Authors Guild cases, this Article takes stock of the legal context for TDM research in the United States. This reappraisal begins in Part I with an assessment of exactly what the Authors Guild cases did and did not establish with respect to the fair use status of text mining. Those cases held unambiguously that reproducing copyrighted works as one step in the process of knowledge discovery through text data mining was transformative, and thus ultimately a fair use of those works. Part I explains why those rulings followed inexorably from copyright's most …

Artificial Intelligence And Law: An Overview, Harry Surden

Publications

Much has been written recently about artificial intelligence (AI) and law. But what is AI, and what is its relation to the practice and administration of law? This article addresses those questions by providing a high-level overview of AI and its use within law. The discussion aims to be nuanced but also understandable to those without a technical background. To that end, I first discuss AI generally. I then turn to AI and how it is being used by lawyers in the practice of law, people and companies who are governed by the law, and government officials who administer the …

Ok, Google, Will Artificial Intelligence Replace Human Lawyering?, Melissa Love Koenig, Julie A. Oseid, Amy Vorenberg

Marquette Law Review

Will Artificial Intelligence (AI) replace human lawyering? The answer is

no. Despite worries that AI is getting so sophisticated that it could take over

the profession, there is little cause for concern. Indeed, the surge of AI in the

legal field has crystalized the real essence of effective lawyering. The lawyer’s

craft goes beyond what AI can do because we listen with empathy to clients’

stories, strategize to find the story that might not be obvious, thoughtfully use

our imagination and judgment to decide which story will appeal to an audience,

and creatively tell those winning stories.

This Article reviews …

Lessons From Literal Crashes For Code, Margot Kaminski

Publications

No abstract provided.

Binary Governance: Lessons From The Gdpr’S Approach To Algorithmic Accountability, Margot E. Kaminski

Publications

Algorithms are now used to make significant decisions about individuals, from credit determinations to hiring and firing. But they are largely unregulated under U.S. law. A quickly growing literature has split on how to address algorithmic decision-making, with individual rights and accountability to nonexpert stakeholders and to the public at the crux of the debate. In this Article, I make the case for why both individual rights and public- and stakeholder-facing accountability are not just goods in and of themselves but crucial components of effective governance. Only individual rights can fully address dignitary and justificatory concerns behind calls for regulating …

The Right To Explanation, Explained, Margot E. Kaminski

Publications

Many have called for algorithmic accountability: laws governing decision-making by complex algorithms, or AI. The EU’s General Data Protection Regulation (GDPR) now establishes exactly this. The recent debate over the right to explanation (a right to information about individual decisions made by algorithms) has obscured the significant algorithmic accountability regime established by the GDPR. The GDPR’s provisions on algorithmic accountability, which include a right to explanation, have the potential to be broader, stronger, and deeper than the preceding requirements of the Data Protection Directive. This Essay clarifies, largely for a U.S. audience, what the GDPR actually requires, incorporating recently released …

Transparency And Algorithmic Governance, Cary Coglianese, David Lehr

All Faculty Scholarship

Machine-learning algorithms are improving and automating important functions in medicine, transportation, and business. Government officials have also started to take notice of the accuracy and speed that such algorithms provide, increasingly relying on them to aid with consequential public-sector functions, including tax administration, regulatory oversight, and benefits administration. Despite machine-learning algorithms’ superior predictive power over conventional analytic tools, algorithmic forecasts are difficult to understand and explain. Machine learning’s “black-box” nature has thus raised concern: Can algorithmic governance be squared with legal principles of governmental transparency? We analyze this question and conclude that machine-learning algorithms’ relative inscrutability does not pose a …

Recovering Tech's Humanity, Olivier Sylvain

Faculty Scholarship

No abstract provided.