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Full-Text Articles in Law
Privacy, Poverty, And Big Data: A Matrix Of Vulnerabilities For Poor Americans, Mary Madden, Michele E. Gilman, Karen Levy, Alice Marwick
Privacy, Poverty, And Big Data: A Matrix Of Vulnerabilities For Poor Americans, Mary Madden, Michele E. Gilman, Karen Levy, Alice Marwick
All Faculty Scholarship
This Article examines the matrix of vulnerabilities that low-income people face as a result of the collection and aggregation of big data and the application of predictive analytics. On one hand, big data systems could reverse growing economic inequality by expanding access to opportunities for low-income people. On the other hand, big data could widen economic gaps by making it possible to prey on low-income people or to exclude them from opportunities due to biases entrenched in algorithmic decision-making tools. New kinds of “networked privacy” harms, in which users are simultaneously held liable for their own behavior and the actions …
Predictive Analytics' Punishment Mismatch, Jessica M. Eaglin
Predictive Analytics' Punishment Mismatch, Jessica M. Eaglin
Articles by Maurer Faculty
No abstract provided.
Constructing Recidivism Risk, Jessica M. Eaglin
Constructing Recidivism Risk, Jessica M. Eaglin
Articles by Maurer Faculty
Courts increasingly use actuarial meaning statistically derived information about a defendant's likelihood of engaging in criminal behavior in the future at sentencing. This Article examines how developers construct the tools that predict recidivism risk. It exposes the numerous choices that developers make during tool construction with serious consequences to sentencing law and policy. These design decisions require normative judgments concerning accuracy, equality, and the purpose of punishment. Whether and how to address these concerns reflects societal values about the administration of criminal justice more broadly. Currently, developers make these choices in the absence of law, even as they face distinct …
Substantiating Big Data In Health Care, Nathan Cortez
Substantiating Big Data In Health Care, Nathan Cortez
Faculty Journal Articles and Book Chapters
Predictive analytics and "big data" are emerging as important new tools for diagnosing and treating patients. But as data collection becomes more pervasive, and as machine learning and analytical methods become more sophisticated, the companies that traffic in health-related big data will face competitive pressures to make more aggressive claims regarding what their programs can predict. Already, patients, practitioners, and payors are inundated with claims that software programs, "apps," and other forms of predictive analytics can help solve some of the health care system's most pressing problems. This article considers the evidence and substantiation that we should require of these …