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2020

Algorithms

Articles 1 - 13 of 13

Full-Text Articles in Law

Law Library Blog (November 2020): Legal Beagle's Blog Archive, Roger Williams University School Of Law Nov 2020

Law Library Blog (November 2020): Legal Beagle's Blog Archive, Roger Williams University School Of Law

Law Library Newsletters/Blog

No abstract provided.


Algorithmic Personalized Pricing, Pascale Chapdelaine Oct 2020

Algorithmic Personalized Pricing, Pascale Chapdelaine

Law Publications

Price is an essential term at the heart of supplier-consumer transactions and relationships increasingly taking place in “micro-marketplace chambers,” where points of comparison with similar relevant products may be difficult to discern and time-consuming to make. This article critically reviews recent legal and economic academic literature, policy reports on algorithmic personalized pricing (i.e. setting prices according to consumers’ personal characteristics to target their willingness to pay), as well as recent developments in privacy regulation, competition law, and policy discourse, to derive the guiding norms that should inform the regulation of this practice, predominantly from a consumer protection perspective. Looking more …


Poverty Lawgorithms A Poverty Lawyer’S Guide To Fighting Automated Decision-Making Harms On Low-Income Communities, Michele E. Gilman Sep 2020

Poverty Lawgorithms A Poverty Lawyer’S Guide To Fighting Automated Decision-Making Harms On Low-Income Communities, Michele E. Gilman

All Faculty Scholarship

Automated decision-making systems make decisions about our lives, and those with low-socioeconomic status often bear the brunt of the harms these systems cause. Poverty Lawgorithms: A Poverty Lawyers Guide to Fighting Automated Decision-Making Harms on Low-Income Communities is a guide by Data & Society Faculty Fellow Michele Gilman to familiarize fellow poverty and civil legal services lawyers with the ins and outs of data-centric and automated-decision making systems, so that they can clearly understand the sources of the problems their clients are facing and effectively advocate on their behalf.


When They Hear Us: Race, Algorithms And The Practice Of Criminal Law, Ngozi Okidegbe Jul 2020

When They Hear Us: Race, Algorithms And The Practice Of Criminal Law, Ngozi Okidegbe

Faculty Scholarship

We are in the midst of a fraught debate in criminal justice reform circles about the merits of using algorithms. Proponents claim that these algorithms offer an objective path towards substantially lowering high rates of incarceration and racial and socioeconomic disparities without endangering community safety. On the other hand, racial justice scholars argue that these algorithms threaten to entrench racial inequity within the system because they utilize risk factors that correlate with historic racial inequities, and in so doing, reproduce the same racial status quo, but under the guise of scientific objectivity.

This symposium keynote address discusses the challenge that …


Artificial Financial Intelligence, William Magnuson Jul 2020

Artificial Financial Intelligence, William Magnuson

Faculty Scholarship

Recent advances in the field of artificial intelligence have revived long-standing debates about what happens when robots become smarter than humans. Will they destroy us? Will they put us all out of work? Will they lead to a world of techno-savvy haves and techno-ignorant have-nots? These debates have found particular resonance in finance, where computers already play a dominant role. High-frequency traders, quant hedge funds, and robo-advisors all represent, to a greater or lesser degree, real-world instantiations of the impact that artificial intelligence is having on the field. This Article will argue that the primary danger of artificial intelligence in …


Deploying Machine Learning For A Sustainable Future, Cary Coglianese May 2020

Deploying Machine Learning For A Sustainable Future, Cary Coglianese

All Faculty Scholarship

To meet the environmental challenges of a warming planet and an increasingly complex, high tech economy, government must become smarter about how it makes policies and deploys its limited resources. It specifically needs to build a robust capacity to analyze large volumes of environmental and economic data by using machine-learning algorithms to improve regulatory oversight, monitoring, and decision-making. Three challenges can be expected to drive the need for algorithmic environmental governance: more problems, less funding, and growing public demands. This paper explains why algorithmic governance will prove pivotal in meeting these challenges, but it also presents four likely obstacles that …


Statistical Precedent: Allocating Judicial Attention, Ryan W. Copus Apr 2020

Statistical Precedent: Allocating Judicial Attention, Ryan W. Copus

Faculty Works

Suffering from a well-covered “crisis of volume,” the United States Courts of Appeals have patched together an ad hoc system of triage in an effort to provide cases with sufficient attention. For example, only some cases are assigned to central staff, analyzed by law clerks, orally argued, debated over by judges, or decided in published opinions. The courts have evaded overt disaster by increasing the number of active, senior, and visiting judges, but the additional personnel poses its own demands on attention—judges must also pay attention to one another in order to coherently develop and apply the law. With too …


In West Philadelphia Born And Raised Or Moving To Bel-Air? Racial Steering As A Consequence Of Using Race Data On Real Estate Websites, Nadiyah J. Humber Jan 2020

In West Philadelphia Born And Raised Or Moving To Bel-Air? Racial Steering As A Consequence Of Using Race Data On Real Estate Websites, Nadiyah J. Humber

Law Faculty Scholarship

No abstract provided.


Fair Housing Enforcement In The Age Of Digital Advertising: A Closer Look At Facebook’S Marketing Algorithms, Nadiyah J. Humber, James Matthews Jan 2020

Fair Housing Enforcement In The Age Of Digital Advertising: A Closer Look At Facebook’S Marketing Algorithms, Nadiyah J. Humber, James Matthews

Law Faculty Scholarship

No abstract provided.


A New Frontier Facing Attorneys And Paralegals: The Promise & Challenges Of Artificial Intelligence As Applied To Law & Legal Decision-Making, Marissa Moran Jan 2020

A New Frontier Facing Attorneys And Paralegals: The Promise & Challenges Of Artificial Intelligence As Applied To Law & Legal Decision-Making, Marissa Moran

Publications and Research

Artificial Intelligence/AI invisibly navigates and informs our lives today and may also be used to determine a client’s legal fate. Through executive order, statements by a U.S. Supreme Court justice and a Congressional Commission on AI, all three branches of the United States government have addressed the use of AI to resolve societal and legal matters. Pursuant to the American Bar Association Model Rules of Professional Conduct[i] and New York Rules of Professional Conduct (NYRPC), [ii] the legal profession recognizes the need for competency in technology which requires both substantive knowledge of law and competent use of technology for …


Ethical Testing In The Real World: Evaluating Physical Testing Of Adversarial Machine Learning, Kendra Albert, Maggie Delano, Jonathon Penney, Afsaneh Ragot, Ram Shankar Siva Kumar Jan 2020

Ethical Testing In The Real World: Evaluating Physical Testing Of Adversarial Machine Learning, Kendra Albert, Maggie Delano, Jonathon Penney, Afsaneh Ragot, Ram Shankar Siva Kumar

Articles, Book Chapters, & Popular Press

This paper critically assesses the adequacy and representativeness of physical domain testing for various adversarial machine learning (ML) attacks against computer vision systems involving human subjects. Many papers that deploy such attacks characterize themselves as “real world.” Despite this framing, however, we found the physical or real-world testing conducted was minimal, provided few details about testing subjects and was often conducted as an afterthought or demonstration. Adversarial ML research without representative trials or testing is an ethical, scientific, and health/safety issue that can cause real harms. We introduce the problem and our methodology, and then critique the physical domain testing …


Secret Conviction Programs, Meghan J. Ryan Jan 2020

Secret Conviction Programs, Meghan J. Ryan

Faculty Journal Articles and Book Chapters

Judges and juries across the country are convicting criminal defendants based on secret evidence. Although defendants have sought access to the details of this evidence—the results of computer programs and their underlying algorithms and source codes—judges have generally denied their requests. Instead, judges have prioritized the business interests of the for-profit companies that developed these “conviction programs” and which could lose market share if the secret algorithms and source codes on which the programs are based were exposed. This decision has jeopardized criminal defendants’ constitutional rights.


Ai Report: Humanity Is Doomed. Send Lawyers, Guns, And Money!, Ashley M. London Jan 2020

Ai Report: Humanity Is Doomed. Send Lawyers, Guns, And Money!, Ashley M. London

Law Faculty Publications

AI systems are powerful technologies being built and implemented by private corporations motivated by profit, not altruism. Change makers, such as attorneys and law students, must therefore be educated on the benefits, detriments, and pitfalls of the rapid spread, and often secret implementation of this technology. The implementation is secret because private corporations place proprietary AI systems inside of black boxes to conceal what is inside. If they did not, the popular myth that AI systems are unbiased machines crunching inherently objective data would be revealed as a falsehood. Algorithms created to run AI systems reflect the inherent human categorization …