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Full-Text Articles in Law
Digital Market Perfection, Rory Van Loo
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. …
Power, Process, And Automated Decision-Making, Ari Ezra Waldman
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 …
Transparency And Algorithmic Governance, Cary Coglianese, David Lehr
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
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.