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The Scored Society: Due Process For Automated Predictions, Danielle Keats Citron, Frank A. Pasquale Jan 2014

The Scored Society: Due Process For Automated Predictions, Danielle Keats Citron, Frank A. Pasquale

Faculty Scholarship

Big Data is increasingly mined to rank and rate individuals. Predictive algorithms assess whether we are good credit risks, desirable employees, reliable tenants, valuable customers—or deadbeats, shirkers, menaces, and “wastes of time.” Crucial opportunities are on the line, including the ability to obtain loans, work, housing, and insurance. Though automated scoring is pervasive and consequential, it is also opaque and lacking oversight. In one area where regulation does prevail—credit—the law focuses on credit history, not the derivation of scores from data.

Procedural regularity is essential for those stigmatized by “artificially intelligent” scoring systems. The American due process tradition should inform …


Note, Institutionally Appropriate Approaches To Privacy: Striking A Balance Between Judicial And Administrative Enforcement Of Privacy Law, Lauren Henry Scholz Jan 2014

Note, Institutionally Appropriate Approaches To Privacy: Striking A Balance Between Judicial And Administrative Enforcement Of Privacy Law, Lauren Henry Scholz

Scholarly Publications

No abstract provided.