Computer Law Commons^™

Algorithmic Jim Crow, Margaret Hu

Margaret Hu

This Article contends that current immigration- and security-related vetting protocols risk promulgating an algorithmically driven form of Jim Crow. Under the “separate but equal” discrimination of a historic Jim Crow regime, state laws required mandatory separation and discrimination on the front end, while purportedly establishing equality on the back end. In contrast, an Algorithmic Jim Crow regime allows for “equal but separate” discrimination. Under Algorithmic Jim Crow, equal vetting and database screening of all citizens and noncitizens will make it appear that fairness and equality principles are preserved on the front end. Algorithmic Jim Crow, however, will enable discrimination on …

Algorithmic Jim Crow, Margaret Hu

Fordham Law Review

This Article contends that current immigration- and security-related vetting protocols risk promulgating an algorithmically driven form of Jim Crow. Under the “separate but equal” discrimination of a historic Jim Crow regime, state laws required mandatory separation and discrimination on the front end, while purportedly establishing equality on the back end. In contrast, an Algorithmic Jim Crow regime allows for “equal but separate” discrimination. Under Algorithmic Jim Crow, equal vetting and database screening of all citizens and noncitizens will make it appear that fairness and equality principles are preserved on the front end. Algorithmic Jim Crow, however, will enable discrimination on …

Regulating By Robot: Administrative Decision Making In The Machine-Learning Era, Cary Coglianese, David Lehr

All Faculty Scholarship

Machine-learning algorithms are transforming large segments of the economy, underlying everything from product marketing by online retailers to personalized search engines, and from advanced medical imaging to the software in self-driving cars. As machine learning’s use has expanded across all facets of society, anxiety has emerged about the intrusion of algorithmic machines into facets of life previously dependent on human judgment. Alarm bells sounding over the diffusion of artificial intelligence throughout the private sector only portend greater anxiety about digital robots replacing humans in the governmental sphere. A few administrative agencies have already begun to adopt this technology, while others …

Algorithmic Discrimination White Paper, Vicky Wei, Teresa Stephenson

Technology Law and Public Policy Clinic

Technological innovation has led to the prevalent use of algorithms in everyday decision making. So ubiquitous is the application of algorithms that many may not recognize its impact on their daily lives. From online shopping to applying for a home loan, algorithms are at play in categorizing and filtering individuals to serve the goal of providing more accurate and efficient results than human decisionmaking would. At the basic level, algorithms are nothing more than a series of step-by-step instructions compiled by a computer, which then analyzes swaths of data based on those instructions. However, when algorithms use incorrect variables to …

The Racist Algorithm?, Anupam Chander

Michigan Law Review

Review of The Black Box Society: The Secret Algorithms That Control Money and Information by Frank Pasquale.

Civil Liberty Or National Security: The Battle Over Iphone Encryption, Karen Lowell

Georgia State University Law Review

On June 5, 2013, Edward Snowden released what would be the first of many documents exposing the vast breadth of electronic surveillance the Federal Bureau of Investigation (FBI) and the National Security Agency (NSA) had been conducting on millions of United States citizens. Although the federal agencies had legal authority under the Foreign Intelligence Surveillance Act (FISA) to collect metadata from companies such as Verizon, many Americans considered this data collection to be a massive invasion of privacy.

Equipped with the knowledge of sweeping domestic surveillance programs, citizens and technology firms fighting for strong privacy and security protection, have started …

Exposure To Police Brutality Allows For Transparency And Accountability Of Law Enforcement, 33 J. Marshall J. Info. Tech. & Privacy L. 75 (2017), Kendal Harden

UIC John Marshall Journal of Information Technology & Privacy Law

Thanks to the advancements in technology and valor of citizens, the public is finally able to understand the true severity of police brutality within the United States. The following considerations aim to address the lack of accountability and transparency of police brutality in the United States today. Part III will show how advancements in technology brings police brutality to the forefront of our nation’s issues by creating an informed society. Part IV will describe how individual states control the use of private cameras and cell phones of citizens to capture occurrences of police brutality. States do this by employing anti-wiretapping …

Ancient Worries And Modern Fears: Different Roots And Common Effects Of U.S. And Eu Privacy Regulation, David Thaw, Pierluigi Perri

Articles

Much legal and technical scholarship discusses the differing views of the United States and European Union toward privacy concepts and regulation. A substantial amount of effort in recent years, in both research and policy, focuses on attempting to reconcile these viewpoints searching for a common framework with a common level of protection for citizens from both sides of Atlantic. Reconciliation, we argue, misunderstands the nature of the challenge facing effective cross-border data flows. No such reconciliation can occur without abdication of some sovereign authority of nations, that would require the adoption of an international agreement with typical tools of international …

Data-Driven Discrimination At Work, Pauline Kim

Scholarship@WashULaw

A data revolution is transforming the workplace. Employers are increasingly relying on algorithms to decide who gets interviewed, hired, or promoted. Although data algorithms can help to avoid biased human decision-making, they also risk introducing new sources of bias. Algorithms built on inaccurate, biased, or unrepresentative data can produce outcomes biased along lines of race, sex, or other protected characteristics. Data mining techniques may cause employment decisions to be based on correlations rather than causal relationships; they may obscure the basis on which employment decisions are made; and they may further exacerbate inequality because error detection is limited and feedback …

Auditing Algorithms For Discrimination, Pauline Kim

Scholarship@WashULaw

This Essay responds to the argument by Joshua Kroll, et al., in Accountable Algorithms, 165 U.PA.L.REV. 633 (2017), that technical tools can be more effective in ensuring the fairness of algorithms than insisting on transparency. When it comes to combating discrimination, technical tools alone will not be able to prevent discriminatory outcomes. Because the causes of bias often lie, not in the code, but in broader social processes, techniques like randomization or predefining constraints on the decision-process cannot guarantee the absence of bias. Even the most carefully designed systems may inadvertently encode preexisting prejudices or reflect structural bias. For this …