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LTEC Lab Seminar Series: Discredited Data: The Epistemic Origins of Algorithmic Discrimination

March 22 @ 2:00 pm - 4:00 pm

LTE Lab Seminar Series presents Professor Ngozi Okidegbe, Boston University and Professor Danardo Jones, Windsor Law; will be sharing knowledge on Discredited Data  on Algorithmic Discrimination.

The Law and Technology Lab (LTEC Lab) is a community of interest that gathers University of Windsor faculty, students, and alumni whose research, teaching and experiential learning initiatives revolve around the themes of law and technology embedded within our institutional values of access to justice and transnational law. 

Professor Okidegbe will be discussing her article Ngozi Okidegbe, “Discredited Data” (2022) 107 Cornell Law Rev. Available at: https://scholarship.law.bu.edu/faculty_scholarship/3137

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 services agencies, and the court system. Redressing this problem will require a paradigmatic shift away from carceral knowledge sources toward non-carceral knowledge sources. This Article explores knowledge produced by communities most impacted by the criminal legal system (“community knowledge sources”) as one category of non-carceral knowledge sources worth utilizing. Though data derived from community knowledge sources have traditionally been discredited and excluded in the construction of pretrial algorithms, tapping into them offers a path toward developing algorithms that have the potential to produce racially and socioeconomically just outcomes.
 The full article can be found here:
 Ngozi Okidegbe, “Discredited Data” (2022) 107 Cornell Law Rev. Available at: https://scholarship.law.bu.edu/faculty_scholarship/3137

This is an in person event with an online option. Lunch will be served to in person guests at the event at 1:30 p.m.

Location: LTECLAB
University of Windsor
Faculty of Law
401 Sunset Ave.
 Room 0140



March 22
2:00 pm - 4:00 pm
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