Law Commons^™

Bots, Bias And Big Data: Artificial Intelligence, Algorithmic Bias And Disparate Impact Liability In Hiring Practices, Mckenzie Raub

Arkansas Law Review

No abstract provided.

The Business Of Ai Startups, James Bessen, Stephen Michael Impink, Robert Seamans, Lydia Reichensperger

Faculty Scholarship

New machine learning techniques have led to an acceleration of “artificial intelligence” (AI). Numerous papers have projected substantial job losses based on assessments of technical feasibility. But what is the actual impact? This paper reports on a survey of commercial AI startups, documenting rich detail about their businesses and their impacts on their customers. These firms report benefits of AI that are more often about enhancing human capabilities than replacing them. Their applications more often increase professional, managerial, and marketing jobs and decrease manual, clerical, and frontline service jobs. These startups sell to firms of different sizes, in different industries …

Economic Rationality And Ethical Values In Design-Defect Analysis: The Trolley Problem And Autonomous Vehicles, W. Bradley Wendel

Cornell Law Faculty Publications

The trolley problem is a well-known thought experiment in moral philosophy, used to explore issues such as rights, deontological reasons, and intention and the doctrine of double effect. Recently it has featured prominently in popular discussions of decision making by autonomous vehicle systems. For example, a Mercedes-Benz executive stated that, if faced with the choice between running over a child that had unexpectedly darted into the road and steering suddenly, causing a rollover accident that would kill the driver, an automated Mercedes would opt to kill the child. This paper considers not the ethical issues raised by such dilemmas, but …

The Tao Of The Dao: Taxing An Entity That Lives On A Blockchain, David J. Shakow

All Faculty Scholarship

In this report, Shakow explains how a decentralized autonomous organization functions and interacts with the U.S. tax system and presents the many tax issues that these structures raise. The possibility of using smart contracts to allow an entity to operate totally autonomously on a blockchain platform seems attractive. However, little thought has been given to how such an entity can comply with the requirements of a tax system. The DAO, the first major attempt to create such an organization, failed because of a programming error. If successful examples proliferate in the future, tax authorities will face significant problems in getting …

The Policy Challenge Of Artificial Intelligence, James Bessen

Faculty Scholarship

New "artificial intelligence" (AI) technology promises to bring dramatic social and economic changes, demanding major policy changes. In intellectual property and antitrust law, AI will exacerbate a damaging trend: across all major sectors of the economy, proprietary information technology is increasing the market dominance of large firms. This trend might not seem like bad news, but it is evidence of a slowdown in the spread of technical knowledge throughout the economy. The result is rising industry concentration, slower productivity growth and growing wage inequality. The key challenge to IP and antitrust policy will be counter this trend yet maintain innovation …

Outcome Prediction In The Practice Of Law, Mark K. Osbeck, Michael Gilliland

Articles

Business forecasters typically use time-series models to predict future demands, the forecasts informing management decision making and guiding organizational planning. But this type of forecasting is merely a subset of the broader field of predictive analytics, models used by data scientists in all manner of applications, including credit approvals, fraud detection, product-purchase and music-listening recommendations, and even the real-time decisions made by self-driving vehicles. The practice of law requires decisions that must be based on predictions of future legal outcomes, and data scientists are now developing forecasting methods to support the process. In this article, Mark Osbeck and Mike Gilliland …

How Copyright Law Can Fix Artificial Intelligence's Implicit Bias Problem, Amanda Levendowski

Georgetown Law Faculty Publications and Other Works

As the use of artificial intelligence (AI) continues to spread, we have seen an increase in examples of AI systems reflecting or exacerbating societal bias, from racist facial recognition to sexist natural language processing. These biases threaten to overshadow AI’s technological gains and potential benefits. While legal and computer science scholars have analyzed many sources of bias, including the unexamined assumptions of its often homogenous creators, flawed algorithms, and incomplete datasets, the role of the law itself has been largely ignored. Yet just as code and culture play significant roles in how AI agents learn about and act in the …

Information And The Regulatory Landscape: A Growing Need To Reconsider Existing Legal Frameworks, Anjanette H. Raymond

Washington and Lee Journal of Civil Rights and Social Justice

No abstract provided.

Humans Forget, Machines Remember: Artificial Intelligence And The Right To Be Forgotten, Tiffany Li, Eduard Fosch Villaronga, Peter Kieseberg

Faculty Scholarship

To understand the Right to be Forgotten in context of artificial intelligence, it is necessary to first delve into an overview of the concepts of human and AI memory and forgetting. Our current law appears to treat human and machine memory alike – supporting a fictitious understanding of memory and forgetting that does not comport with reality. (Some authors have already highlighted the concerns on the perfect remembering.) This Article will examine the problem of AI memory and the Right to be Forgotten, using this example as a model for understanding the failures of current privacy law to reflect the …

The Rise Of Artificial Intelligence In The Legal Field: Where We Are And Where We Are Going, Sergio David Becerra

The Journal of Business, Entrepreneurship & the Law

The twenty-first century has brought significant technological advancement that permeates all aspects of our lives. The legal field, though slow in the adaption of this technology, is beginning to pick up the pace. Artificial Intelligence (AI) technology is used now to perform legal work once completed solely by legal practitioners. This Comment outlines what AI is and reviews the current use of AI in the legal field. It also identifies AI products and developments that are in place. Finally, it argues that lawyers will always be needed in the practice of law, despite the continued growth of AI.

Ethics Of Using Artificial Intelligence To Augment Drafting Legal Documents, David Hricik

Articles

Skynet is not and may never be self-aware, but machines are al-ready doing legal research, drafting legal documents, negotiating disputes such as traffic tickets and divorce schedules, and even drafting patent applications. Machines learn from us, and each other, to augment the ability of lawyers to represent clients—and even to replace lawyers completely. While it also threatens lawyers’ jobs, the exponential increase in the capacity of machines to transmit, store, and process data presents the opportunity for lawyers to use these services to provide better, cheaper, or faster legal representation to clients. By way of familiar example, instead of determining …

Will Ai Change How Or What We Teach, Virginia A. Neisler

Law Librarian Scholarship

A micro essay on AI in legal education.

A Rule Of Persons, Not Machines: The Limits Of Legal Automation, Frank A. Pasquale

Faculty Scholarship

No abstract provided.

Algorithms And Automation: Fostering Trustworthiness In Artificial Intelligence, Andrew B. Ware

Honors Theses and Capstones

No abstract provided.

The Modern Trolley Problem: Ethical And Economically-Sound Liability Schemes For Autonomous Vehicles, Amar Kumar Moolayil

Journal of Law, Technology, & the Internet

The paper synthesizes modern scholarship in the fields of Artificial Intelligence law, Ethics, Corporate Liability, and Economics to develop potential liability schemes that the automotive and insurance industries may impose when autonomous vehicles eventually come to dominate the roadways. By addressing the issues of whom the autonomous vehicle’s AI protects and who bears liability in the event of an accident—two issues that this author believes are critical to the successful adoption of autonomous vehicle technology—the transition from human drivers to AI drivers will be less contentious. Because of the prescient nature of the topic, as well as a discussion of …

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 …

Is Tricking A Robot Hacking?, Ryan Calo, Ivan Evtimov, Earlence Fernandes, Tadayoshi Kohno, David O'Hair

Tech Policy Lab

The authors of this essay represent an interdisciplinary team of experts in machine learning, computer security, and law. Our aim is to introduce the law and policy community within and beyond academia to the ways adversarial machine learning (ML) alter the nature of hacking and with it the cybersecurity landscape. Using the Computer Fraud and Abuse Act of 1986—the paradigmatic federal anti-hacking law—as a case study, we mean to evidence the burgeoning disconnect between law and technical practice. And we hope to explain what is at stake should we fail to address the uncertainty that flows from the prospect that …

Bridges Ii: The Law--Stem Alliance & Next Generation Innovation, Harry Surden

Publications

Technological change recently has altered business models in the legal field, and these changes will continue to affect the practice of law itself. How can we, as educators, prepare law students to meet the challenges of new technology throughout their careers?

Expanding The Artificial Intelligence-Data Protection Debate, Fred H. Cate, Christopher Kuner, Orla Lynskey, Christopher Millard, Nora Ni Loideain, Dan Jerker B. Svantesson

Articles by Maurer Faculty

No abstract provided.

Robotic Speakers And Human Listeners, Helen Norton

Publications

In their new book, Robotica, Ron Collins and David Skover assert that we protect speech not so much because of its value to speakers but instead because of its affirmative value to listeners. If we assume that the First Amendment is largely, if not entirely, about serving listeners’ interests—in other words, that it’s listeners all the way down—what would a listener-centered approach to robotic speech require? This short symposium essay briefly discusses the complicated and sometimes even dark side of robotic speech from a listener-centered perspective.

Panel 1: Robotic Speech And The First Amendment, Bruce E. H. Johnson, Helen Norton, David Skover

Publications

Moderator: Professor Gregory Silverman.

Book discussed: Ronald L. Collins & David M. Skover, Robotica: Speech Rights and Artificial Intelligence (Cambridge Univ. Press 2018).

Autonomy In The Age Of Autonomous Vehicles, Michael Mattioli

Articles by Maurer Faculty

This essay describes intertwined policy challenges related to autonomous vehicle data. The policy goals of promoting privacy, safety, competition, and commerce are all so deeply intertwined, I conclude, that they must be understood and addressed together. This essay does not attempt to solve the problem. Instead, it presents a descriptive snapshot of the current state of play in the industry and closes by raising a set of questions. I hope these questions will prompt useful discussions among policy experts and the public.

Emerging Technologies Challenging Current Legal Paradigms, W. Keith Robinson, Joshua T. Smith

Faculty Journal Articles and Book Chapters

U.S. patent law has made assumptions about where new inventions will be created, who will create them, and how they will be infringed. Throughout history, emerging technologies have challenged these paradigms. This decade’s emerging technologies will allow humans to create in virtual worlds, connect billions of every day devices via the Internet, and use artificial intelligence to invent across technology fields. If countries like the U.S. wish to encourage inventors to seek patent protection in these emerging areas, then a paradigm shift in the law must occur. Specifically, the law must clarify patent eligibility, recognize the increasing role of artificial …

Artificial Intelligence And Role-Reversible Judgment, Stephen E. Henderson, Kiel Brennan-Marquez

Stephen E Henderson