Law Commons^™

Dynamic Pricing Algorithms, Consumer Harm, And Regulatory Response, Alexander Mackay, Samuel Weinstein

Faculty Articles

Pricing algorithms are rapidly transforming markets, from ride-sharing, to air travel, to online retail. Regulators and scholars have watched this development with a wary eye. Their focus so far has been on the potential for pricing algorithms to facilitate explicit and tacit collusion. This Article argues that the policy challenges pricing algorithms pose are far broader than collusive conduct. It demonstrates that algorithmic pricing can lead to higher prices for consumers in competitive markets and even in the absence of collusion. This consumer harm can be initiated by a single firm employing a superior pricing algorithm. Higher prices arise from …

The Role Of Data For Ai Startup Growth, James Bessen, Stephen Michael Impink, Lydia Reichensperger, Robert Seamans

Faculty Scholarship

Artificial intelligence (“AI”)-enabled products are expected to drive economic growth. Training data are important for firms developing AI-enabled products; without training data, firms cannot develop or refine their algorithms. This is particularly the case for AI startups developing new algorithms and products. However, there is no consensus in the literature on which aspects of training data are most important. Using unique survey data of AI startups, we find that startups with access to proprietary training data are more likely to acquire venture capital funding.

Law Library Blog (April 2022): Legal Beagle's Blog Archive, Roger Williams University School Of Law

Law Library Newsletters/Blog

No abstract provided.

The Democratizing Potential Of Algorithms?, Ngozi Okidegbe

Faculty Scholarship

Jurisdictions are increasingly embracing the use of pretrial risk assessment algorithms as a solution to the problem of mass pretrial incarceration. Conversations about the use of pretrial algorithms in legal scholarship have tended to focus on their opacity, determinativeness, reliability, validity, or their (in)ability to reduce high rates of incarceration as well as racial and socioeconomic disparities within the pretrial system. This Article breaks from this tendency, examining these algorithms from a democratization of criminal law perspective. Using this framework, it points out that currently employed algorithms are exclusionary of the viewpoints and values of the racially marginalized communities most …

Beyond Section 230 Liability For Facebook, Nancy S. Kim

Articles

No abstract provided.

Hunting And Gathering On The Legal Information Savannah, Susan Nevelow Mart, Adam Litzler, David Gunderman

Publications

This article asks, what is it like for novice researchers to research real-world legal problems using four platforms: Bloomberg Law, Fastcase, Lexis Advance, and Westlaw? The study findings produced some surprises, as well as some clear implications for teaching legal research.

Manipulation And The First Amendment, Helen Norton

Publications

No abstract provided.

Of Afrofuturism, Of Algorithms, Ngozi Okidegbe

Faculty Scholarship

Algorithms are proliferating in criminal legal structures. The predictions produced by these algorithms inform life-altering decisions around surveillance and incarceration. Their continued use poses a challenge to ongoing racial justice efforts. Contesting how algorithms of today maintain the racial status quo requires a fundamental rethinking of the algorithm project. This essay explores how Afrofuturism can facilitate such a rethinking. It imagines how applying an Afrofuturist paradigm to the adoption, construction, implementation, and oversight of algorithms could radically change the kind of algorithms developed and the purposes for which they are developed. Tapping into this potential offers the chance for members …

Considering "Machine Testimony": The Impact Of Facial Recognition Software On Eyewitness Identifications, Valena Beety

Articles by Maurer Faculty

This Article uses a wrongful conviction lens to compare identifications by machines, notably facial recognition software, with identifications by humans. The Article advocates for greater reliability checks on both before use against a criminal defendant. The Article examines the cascading influence of facial recognition software on eyewitness identifications themselves and the related potential for greater errors. As a solution, the Article advocates the inclusion of eyewitness identification in the Organization of Scientific Area Committees' ("OSAC") review of facial recognition software for a more robust examination and consideration of software and its usage. The Article also encourages police departments to adopt …

Tailoring Ex Machina: Perspectives On Personalized Law, Gregory Klass

Georgetown Law Faculty Publications and Other Works

In their book Personalized Law: Different Rules for Different People, Omri Ben-Shahar and Ariel Porat propose a radical approach to lawmaking: using of big data and artificial intelligence to tailor legal dictates to the individual histories and characteristics of persons they affect. This essay critically discusses that proposal.

It first examines normative differences among the Ben-Shahar and Porat’s proposals for personalizing laws. There are important differences, for example, between using big data and artificial intelligence to tailor how a private legal power can be exercised to the capacities and interests of the power-holder and imposing different speed limits on …