About
Ngozi Okidegbe has long been interested in racial justice in society. But she also has become an expert in computer coding, algorithms, and new technologies developed through big data. Those passions provided the perfect opportunity for her to become BU's first dual-appointed faculty member in law and data sciences, and she can't wait to get started. She is an associate professor in the School of Law and an assistant professor in the Faculty of Computing & Data Sciences.As an example of her research and work, Okidegbe points to injustices related to pretrial release decisions within the legal system. When a person is charged with a crime, she explains, a judge has to determine whether to release or detain a person while their trial is pending. But studies have shown that class and race often affect this process, resulting in the pretrial detention of a large number of defendants, primarily Black or brown, who pose no danger or flight risk.
The disparity in who gets released pretrial is one reason why some jurisdictions are now turning to using pretrial algorithms that use big data, statistical methods, and information about a defendant to produce a prediction about whether that defendant would miss a court appearance or be arrested for a crime while awaiting their trial. The hope is that the predictions provided by the algorithms will help judges make their decisions in a less biased way.
But it's not that simple, Okidegbe says. Algorithms for pretrial decision-making are not perfect. They are still built off of data produced by legal institutions, and therefore they tend to produce racially unequal positions about marginalized or underrepresented communities.