Law Commons^™

Discredited Data, Ngozi Okidegbe

Faculty Scholarship

Jurisdictions are increasingly employing pretrial algorithms as a solution to the racial and socioeconomic inequities in the bail system. But in practice, pretrial algorithms have reproduced the very inequities they were intended to correct. Scholars have diagnosed this problem as the biased data problem: pretrial algorithms generate racially and socioeconomically biased predictions, because they are constructed and trained with biased data.

This Article contends that biased data is not the sole cause of algorithmic discrimination. Another reason pretrial algorithms produce biased results is that they are exclusively built and trained with data from carceral knowledge sources – the police, pretrial …

Using Artificial Intelligence In The Law Review Submissions Process, Brenda M. Simon

Faculty Scholarship

The use of artificial intelligence to help editors examine law review submissions may provide a way to improve an overburdened system. This Article is the first to explore the promise and pitfalls of using artificial intelligence in the law review submissions process. Technology-assisted review of submissions offers many possible benefits. It can simplify preemption checks, prevent plagiarism, detect failure to comply with formatting requirements, and identify missing citations. These efficiencies may allow editors to address serious flaws in the current selection process, including the use of heuristics that may result in discriminatory outcomes and dependence on lower-ranked journals to conduct …

Bridging The Computer Science – Law Divide, Azer Bestavros, Stacey Dogan, Paul Ohm, Andrew Sellars

Faculty Scholarship

Many pressing societal questions can be answered only by bringing experts from different disciplines together. Questions around misinformation and disinformation, platform power, surveillance capitalism, information privacy, and algorithmic bias, among many others, reside at the intersection of computer science and law. We need to develop institutions that bring together computer scientists and legal scholars to work together on issues like these, and to train new innovators, thought leaders, counselors, and policymakers with hybrid training in both disciplines. In Universities, the disciplines of Computer Science (CS) and Law are separated by many wide chasms. Differences in standards, language, methods, and culture …

Competition And Innovation: The Breakup Of Ig Farben, Felix Poege

Faculty Scholarship

The relationship between competition and innovation is difficult to disentangle, as exogenous variation in market structure is rare. The 1952 breakup of Germany’s leading chemical company, IG Farben, represents such a disruption. After the Second World War, the Allies occupying Germany imposed the breakup because of IG Farben’s importance for the German war economy instead of standard antitrust concerns. In technology areas where the breakup reduced concentration, patenting increased strongly, driven by domestic firms unrelated to IG Farben. An analysis of patent texts shows that an increased propensity to patent does not drive the effect. Descriptively, IG Farben’s successors increased …

Legislating Data Loyalty, Woodrow Hartzog, Neil Richards

Faculty Scholarship

Lawmakers looking to embolden privacy law have begun to consider imposing duties of loyalty on organizations trusted with people’s data and online experiences. The idea behind loyalty is simple: organizations should not process data or design technologies that conflict with the best interests of trusting parties. But the logistics and implementation of data loyalty need to be developed if the concept is going to be capable of moving privacy law beyond its “notice and consent” roots to confront people’s vulnerabilities in their relationship with powerful data collectors.

In this short Essay, we propose a model for legislating data loyalty. Our …

The Surprising Virtues Of Data Loyalty, Woodrow Hartzog, Neil M. Richards

Faculty Scholarship

Lawmakers in the United States and Europe are seriously considering imposing duties of data loyalty that implement ideas from privacy law scholarship, but critics claim such duties are unnecessary, unworkable, overly individualistic, and indeterminately vague. This paper takes those criticisms seriously, and its analysis of them reveals that duties of data loyalty have surprising virtues. Loyalty, it turns out, can support collective well-being by embracing privacy’s relational turn; it can be a powerful state of mind for reenergizing privacy reform; it prioritizes human values rather than potentially empty formalism; and it offers solutions that are flexible and clear rather than …