Law Commons^™

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 …

Regulating New Tech: Problems, Pathways, And People, Cary Coglianese

All Faculty Scholarship

New technologies bring with them many promises, but also a series of new problems. Even though these problems are new, they are not unlike the types of problems that regulators have long addressed in other contexts. The lessons from regulation in the past can thus guide regulatory efforts today. Regulators must focus on understanding the problems they seek to address and the causal pathways that lead to these problems. Then they must undertake efforts to shape the behavior of those in industry so that private sector managers focus on their technologies’ problems and take actions to interrupt the causal pathways. …

Clearing Opacity Through Machine Learning, W. Nicholson Price Ii, Arti K. Rai

Articles

Artificial intelligence and machine learning represent powerful tools in many fields, ranging from criminal justice to human biology to climate change. Part of the power of these tools arises from their ability to make predictions and glean useful information about complex real-world systems without the need to understand the workings of those systems.

Fair Play: Notes On The Algorithmic Soccer Referee, Michael J. Madison

Articles

The soccer referee stands in for a judge. Soccer’s Video Assistant Referee (“VAR”) system stands in for algorithms that augment human deciders. Fair play stands in for justice. They are combined and set in a polycentric system of governance, with implications for designing, administering, and assessing human-machine combinations.

Book Review, Aamir S. Abdullah

Publications

No abstract provided.

The Right To Contest Ai, Margot E. Kaminski, Jennifer M. Urban

Publications

Artificial intelligence (AI) is increasingly used to make important decisions, from university admissions selections to loan determinations to the distribution of COVID-19 vaccines. These uses of AI raise a host of concerns about discrimination, accuracy, fairness, and accountability.

In the United States, recent proposals for regulating AI focus largely on ex ante and systemic governance. This Article argues instead—or really, in addition—for an individual right to contest AI decisions, modeled on due process but adapted for the digital age. The European Union, in fact, recognizes such a right, and a growing number of institutions around the world now call for …

Autonomous Business Reality, Carla L. Reyes

Faculty Journal Articles and Book Chapters

Society tends to expect technology to do more than it can actually achieve, at a faster pace than it can actually move. The resulting hype cycle infects all forms of discourse around technology. Unfortunately, the discourse on law and technology is no exception to this rule. The resulting discussion is often characterized by two or more positions at opposite ends of the spectrum, such that participants in the discussion speak past each other, rather than to each other. The rich context that sits in the middle ground goes disregarded altogether. This dynamic most recently surfaced in the legal literature regarding …

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

Law Library Newsletters/Blog

No abstract provided.

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 …

Digital Market Perfection, Rory Van Loo

Faculty Scholarship

Google’s, Apple’s, and other companies’ automated assistants are increasingly serving as personal shoppers. These digital intermediaries will save us time by purchasing grocery items, transferring bank accounts, and subscribing to cable. The literature has only begun to hint at the paradigm shift needed to navigate the legal risks and rewards of this coming era of automated commerce. This Article begins to fill that gap first by surveying legal battles related to contract exit, data access, and deception that will determine the extent to which automated assistants are able to help consumers to search and switch, potentially bringing tremendous societal benefits. …

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 …

Inside The Black Box Of Search Algorithms, Susan Nevelow Mart, Joe Breda, Ed Walters, Tito Sierra, Khalid Al-Kofahi

Publications

A behind-the-scenes look at the algorithms that rank results in Bloomberg Law, Fastcase, Lexis Advance, and Westlaw.

Power, Process, And Automated Decision-Making, Ari Ezra Waldman

Articles & Chapters

Many decisions that used to be made by humans are now made by machines. And yet, automated decision-making systems based on “big data” – powered algorithms and machine learning are just as prone to mistakes, biases, and arbitrariness as their human counterparts. The result is a technologically driven decision-making process that seems to defy interrogation, analysis, and accountability and, therefore, undermines due process. This should make algorithmic decision-making an illegitimate source of authority in a liberal democracy. This Essay argues that algorithmic decision-making is a product of the neoliberal project to undermine social values like equality, nondiscrimination, and human flourishing …

A Legal Perspective On The Trials And Tribulations Of Ai: How Artificial Intelligence, The Internet Of Things, Smart Contracts, And Other Technologies Will Affect The Law, Iria Giuffrida, Fredric Lederer, Nicolas Vermeys

Faculty Publications

No abstract provided.

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

Faculty Scholarship

No abstract provided.

Bias In, Bias Out, Sandra G. Mayson

All Faculty Scholarship

Police, prosecutors, judges, and other criminal justice actors increasingly use algorithmic risk assessment to estimate the likelihood that a person will commit future crime. As many scholars have noted, these algorithms tend to have disparate racial impacts. In response, critics advocate three strategies of resistance: (1) the exclusion of input factors that correlate closely with race; (2) adjustments to algorithmic design to equalize predictions across racial lines; and (3) rejection of algorithmic methods altogether.

This Article’s central claim is that these strategies are at best superficial and at worst counterproductive because the source of racial inequality in risk assessment lies …

Results May Vary, Susan Nevelow Mart

Publications

No abstract provided.

Understanding The Human Element In Search Algorithms And Discovering How It Affects Search Results, Susan Nevelow Mart

Publications

When legal researchers search in online databases for the information they need to solve a legal problem, they need to remember that the algorithms that are returning results to them were designed by humans. The world of legal research is a human-constructed world, and the biases and assumptions the teams of humans that construct the online world bring to the task are imported into the systems we use for research. This article takes a look at what happens when six different teams of humans set out to solve the same problem: how to return results relevant to a searcher’s query …

Bloomberg’S Points Of Law: Can They Compete With Headnotes?, Jill Sturgeon

Publications

No abstract provided.

The Gdpr’S Version Of Algorithmic Accountability, Margot Kaminski

Publications

No abstract provided.

Artificial Intelligence In Health Care: Applications And Legal Implications, W. Nicholson Price Ii

Articles

Artificial intelligence (AI) is rapidly moving to change the healthcare system. Driven by the juxtaposition of big data and powerful machine learning techniques—terms I will explain momentarily—innovators have begun to develop tools to improve the process of clinical care, to advance medical research, and to improve efficiency. These tools rely on algorithms, programs created from healthcare data that can make predictions or recommendations. However, the algorithms themselves are often too complex for their reasoning to be understood or even stated explicitly. Such algorithms may be best described as “black-box.” This article briefly describes the concept of AI in medicine, including …

Data For The Algorithm As A Human Artifact: Implications For Legal [Re]Search, Susan Nevelow Mart

Research Data

These documents underlie and are cited in this empirical study: Susan Nevelow Mart, The Algorithm as a Human Artifact: Implications for Legal [Re]Search, 109 Law Libr. J. 387, 409 n.123 (2017), available at http://scholar.law.colorado.edu/articles/755/.

The ZIP file contains three files: one PDF document ("Tables for Charts 1-3"), and two SPSS files ("Data Archive" and "Syntax Archive" (SPSS version 24)). The "Syntax Archive" file may be viewed in a text editor (e.g., Notepad) as well as in SPSS.

Appendix B: The Algorithm As A Human Artifact: Implications For Legal [Re]Search, Susan Nevelow Mart

Research Data

This document, "Search Instructions for Algorithm Study," is an electronic Appendix B to, and is cited in, the empirical study: Susan Nevelow Mart, The Algorithm as a Human Artifact: Implications for Legal [Re]Search, 109 Law Libr. J. 387, 400 n.78 (2017), available at http://scholar.law.colorado.edu/articles/755/.

Authorship, Disrupted: Ai Authors In Copyright And First Amendment Law, Margot E. Kaminski

Publications

Technology is often characterized as an outside force, with essential qualities, acting on the law. But the law, through both doctrine and theory, constructs the meaning of the technology it encounters. A particular feature of a particular technology disrupts the law only because the law has been structured in a way that makes that feature relevant. The law, in other words, plays a significant role in shaping its own disruption. This Essay is a study of how a particular technology, artificial intelligence, is framed by both copyright law and the First Amendment. How the algorithmic author is framed by these …

Every Algorithm Has A Pov, Susan Nevelow Mart

Publications

When legal researchers search in online databases for the information they need to solve a legal problem, they need to remember that the algorithms that are returning results to them were designed by humans. The world of legal research is a human-constructed world, and the biases and assumptions the teams of humans that construct the online world bring to the task are imported into the systems we use for research. This article takes a look at what happens when six different teams of humans set out to solve the same problem: how to return results relevant to a searcher’s query …

The Algorithm As A Human Artifact: Implications For Legal [Re]Search, Susan Nevelow Mart

Publications

The results of using the search algorithms in Westlaw, Lexis Advance, Fastcase, Google Scholar, Ravel, and Casetext are compared. Six groups of humans created six different algorithms, and the results are a testament to the variability of human problem solving. That variability has implications both for researching and teaching research.

Research Algorithms Have A Point Of View: The Effect Of Human Decision Making On Your Search Results, Susan Nevelow Mart

Publications

No abstract provided.

From Google To Tolstoy Bot: Should The First Amendment Protect Speech Generated By Algorithms?, Margot Kaminski

Publications

No abstract provided.