Law Commons^™

Overcoming Racial Harms To Democracy From Artificial Intelligence, Spencer A. Overton

GW Law Faculty Publications & Other Works

While the United States is becoming more racially diverse, generative artificial intelligence and related technologies threaten to undermine truly representative democracy. Left unchecked, AI will exacerbate already substantial existing challenges, such as racial polarization, cultural anxiety, antidemocratic attitudes, racial vote dilution, and voter suppression. Synthetic video and audio (“deepfakes”) receive the bulk of popular attention—but are just the tip of the iceberg. Microtargeting of racially tailored disinformation, racial bias in automated election administration, discriminatory voting restrictions, racially targeted cyberattacks, and AI-powered surveillance that chills racial justice claims are just a few examples of how AI is threatening democracy. Unfortunately, existing …

The Prediction Society: Algorithms And The Problems Of Forecasting The Future, Hideyuki Matsumi, Daniel J. Solove

GW Law Faculty Publications & Other Works

Predictions about the future have been made since the earliest days of humankind, but today, we are living in a brave new world of prediction. Today’s predictions are produced by machine learning algorithms that analyze massive quantities of personal data. Increasingly, important decisions about people are being made based on these predictions.

Algorithmic predictions are a type of inference. Many laws struggle to account for inferences, and even when they do, the laws lump all inferences together. But as we argue in this Article, predictions are different from other inferences. Predictions raise several unique problems that current law is ill-suited …

Using Artificial Intelligence In The Law Review Submissions Process, Brenda M. Simon

Faculty Scholarship

The use of artificial intelligence to help editors examine law review submissions may provide a way to improve an overburdened system. This Article is the first to explore the promise and pitfalls of using artificial intelligence in the law review submissions process. Technology-assisted review of submissions offers many possible benefits. It can simplify preemption checks, prevent plagiarism, detect failure to comply with formatting requirements, and identify missing citations. These efficiencies may allow editors to address serious flaws in the current selection process, including the use of heuristics that may result in discriminatory outcomes and dependence on lower-ranked journals to conduct …

Law Library Blog (January 2021): Legal Beagle's Blog Archive, Roger Williams University School Of Law

Law Library Newsletters/Blog

No abstract provided.

Algorithms In Business, Merchant-Consumer Interactions, & Regulation, Tabrez Y. Ebrahim

Faculty Scholarship

The shift towards the use of algorithms in business has transformed merchant–consumer interactions. Products and services are increasingly tailored for consumers through algorithms that collect and analyze vast amounts of data from interconnected devices, digital platforms, and social networks. While traditionally merchants and marketeers have utilized market segmentation, customer demographic profiles, and statistical approaches, the exponential increase in consumer data and computing power enables them to develop and implement algorithmic techniques that change consumer markets and society as a whole. Algorithms enable targeting of consumers more effectively, in real-time, and with high predictive accuracy in pricing and profiling strategies. In …

Social Media Self-Regulation And The Rise Of Vaccine Misinformation, Ana Santos Rutschman

All Faculty Scholarship

This essay examines the main characteristics and shortcomings of mainstream social media responses to vaccine misinformation and disinformation. Parts I and II contextualize the recent expansion of vaccine information and disinformation in the online environment. Part III provides a survey and taxonomy of ongoing responses to vaccine misinformation adopted by mainstream social media. It further notes the limitations of current self-regulatory modes and illustrates these limitations by presenting a short case study on Facebook—the largest social media vehicle for vaccine-specific misinformation, currently estimated to harbor approximately half of the social media accounts linked to vaccine misinformation. Part IV examines potential …

Law Enforcement’S Use Of Facial Recognition Software In United States Cities, Samantha Jean Wunschel

Honors Program Theses and Projects

Facial recognition software is something we use every day, whether it’s a suggested tag on our Facebook post or a faster way to unlock our phones. As technology becomes increasingly pervasive in our lives, law enforcement has adapted to utilize the new tools available in accessory to their investigations and the legal process.

Reconciling Risk And Equality, Christopher Slobogin

Vanderbilt Law School Faculty Publications

States have increasingly resorted to statistically-derived risk algorithms to determine when diversion from prison should occur, whether sentences should be enhanced, and the level of security and treatment a prisoner requires. The federal government has jumped on the bandwagon in a big way with the First Step Act, which mandated that a risk assessment instrument be developed to determine which prisoners can be released early on parole. Policymakers are turning to these algorithms because they are thought to be more accurate and less biased than judges and correctional officials, making them useful tools for reducing prison populations through identification of …

Mining The Harvard Caselaw Access Project, Felix B. Chang, Erin Mccabe, James Lee

Faculty Articles and Other Publications

This Essay illustrates how machine learning can disrupt legal scholarship through the algorithmic extraction and analysis of big data. Specifically, we utilize data from Harvard Law School’s Caselaw Access Project to model how courts tackle two thorny question in antitrust: the measure of market power and the balance between antitrust and regulation.

Facebook V. Sullivan: Public Figures And Newsworthiness In Online Speech, Thomas E. Kadri, Kate Klonick

Faculty Publications

In the United States, there are now two systems to adjudicate disputes about harmful speech. The first is older and more established: the legal system in which judges apply constitutional law to limit tort claims alleging injuries caused by speech. The second is newer and less familiar: the content-moderation system in which platforms like Facebook implement the rules that govern online speech. These platforms are not bound by the First Amendment. But, as it turns out, they rely on many of the tools used by courts to resolve tensions between regulating harmful speech and preserving free expression—particularly the entangled concepts …

The Law Of Advertising Outrage, Mark Bartholomew

Journal Articles

This article examines the stimulation of audience outrage, both as a marketing strategy and as a subject of legal regulation. A brief history of advertising in the United States reveals repeated yet relatively infrequent attempts to attract consumer attention through overt transgressions of social norms relating to sex, violence, race, and religion. Natural concerns over audience reaction limited use of this particular advertising tactic as businesses needed to be careful not to alienate prospective purchasers. But now companies can engage in “algorithmic outrage”—social media advertising meant to stimulate individual feelings of anger and upset—with less concern for a consumer backlash. …

Classifying Political Similarity Of Twitter Users, William K. Paustian

Computer Science Summer Fellows

The emergence of large scale social networks has led to research in approaches to classify similar users on a network. While many such approaches use data mining techniques, recent efforts have focused on measuring the similarity of users using structural properties of the underlying graph representing the network. In this paper, we identify the Twitter followers of the 2016 presidential candidates and classify them as Democrat, Republican or Bipartisan. We did this by designing a new approach to measuring structural similarity, PolRANK. PolRANK computes the similarity of a pair of users by accounting for both the number of candidates they …

Research Strategies Using Headnotes: Citators And Relevance, Susan Nevelow Mart

Publications

No abstract provided.

Algorithmic Entities, Lynn M. Lopucki

UF Law Faculty Publications

In a 2014 article, Professor Shawn Bayern demonstrated that anyone can confer legal personhood on an autonomous computer algorithm by putting it in control of a limited liability company. Bayern’s demonstration coincided with the development of “autonomous” online businesses that operate independently of their human owners—accepting payments in online currencies and contracting with human agents to perform the off-line aspects of their businesses. About the same time, leading technologists Elon Musk, Bill Gates, and Stephen Hawking said that they regard human-level artificial intelligence as an existential threat to the human race. This Article argues that algorithmic entities—legal entities that have …

Negligence, Causation And Information, Stephen G. Marks

Faculty Scholarship

This note suggests a model to unify, in a simple information-based framework, the notion of negligence and the various notions of causation. In effect, the model demonstrates that negligence, probabilistic cause and cause-in-fact represent an identical concept applied to different information sets. This note uses the unified framework to develop a simple algorithm for the practical application of the principles of causation in the law of negligence.

Parker V. Flook, Lewis F. Powell Jr.

Supreme Court Case Files

No abstract provided.