The Race + Data Science Lecture Series aims to celebrate and advance research in the areas of race and data, engineering, and computational science. With this series of events, our goal is to improve how we as data scientists and data-adjacent researchers speak about race. 

Guest Speaker

Abeba Birhane, PhD Candidate, School of Computer Science, University College Dublin 

Details & Recording

Wednesday, September 29 (9:00 AM – 10:00 AM ET) – Virtual

Chair & Moderator

Desmond Upton Patton, Associate Director of Diversity, Equity and Inclusion, The Data Science Institute, Columbia University. Patton is also Associate Professor of Social Work; Associate Dean of Curriculum Innovation and Academic Affairs; and Courtesy Appointment in Department of Sociology, Columbia University School of Social Work.

Abstract & Biography

The Limits of Fairness 

As algorithmic systems permeate all corners of social and political life, enquiries into their negative impacts have also become a topic of interest. Yet,  much of this work remains “technical”, limited, and narrow in scope. In this talk, I argue why just and equitable algorithmic systems need looking beyond “fairness” metrics and “debiased” datasets. Instead, they require fundamental and structural rethinking of how fields such as data science approach social phenomena. 

Bio: I am a cognitive science PhD researcher at the Complex Software Lab in the school of computer science at University college Dublin , Ireland. My interdisciplinary research sits at the intersection of complex adaptive systems, machine learning, and critical race studies. On the one hand, complexity science tells us that people, as complex adaptive systems are inherently indeterminable. On the other, machine learning systems that claim to predict human behaviour are becoming ubiquitous in all spheres of social life. Machine prediction, when deployed to high-stake situations, not only is erroneous but also presents real harm to those at the margins of society. I examine questions of such nature in my PhD.

I co-lead the Data Economies and Data Governance working group, one of the Mechanism Design for Social Good (MD4SG) working groups. I am also a member of the Coalition For Critical Technology group. I am currently working as a Research Scientist intern at DeepMind with the Ethics Research team. I have numerous ongoing projects and I look forward to sharing them as they come to completion. As well as my full-time intern position at DeepMind, I am also currently in the final year of my PhD which means I am unable to accept invitations to speak at conferences, workshops, or similar events.

The Race + Data Science Lecture Series is supported by funding from the MacArthur Foundation and New America.