Abigail Jacobs

Abigail Jacobs is an Assistant Professor at the University of Michigan, jointly appointed in the School of Information and the College of Literature, Science, and the Arts. She is also affiliated with the Center for Ethics, Society, and Computing (ESC) and the Michigan Institute for Data Science (MIDAS).

• Education:
  • PhD in Computer Science, University of Colorado Boulder (2015-2019)
  • BA in Mathematical Methods in the Social Sciences and Mathematics, Northwestern University (2011-2015)

Research Interests: Dr. Jacobs examines measurement and validity in machine learning, focusing on hidden assumptions in AI systems, governance structures in sociotechnical systems, and inequality in algorithmic design. Her work bridges AI, data science, and social science methodologies, emphasizing interdisciplinary collaboration.

Recent Publications (2024-2025) explore generative AI evaluation, algorithmic transparency in government (e.g., US Census Bureau), motion capture data ethics, and sociotechnical frameworks for AI governance. Earlier works (2023) address fairness in ranking systems and racial categorization in algorithmic bias studies.

Scientific Awards:

• Microsoft Research AI & Society Fellowship (2024)
• NSF Graduate Research Fellowship (during PhD)

Advising & Grants: She co-advises Ph.D. students Amina Abdu and Meera Desai. Her research includes a Notre Dame-IBM Tech Ethics Lab grant on AI audits and collaborations with institutions like UC Berkeley, Microsoft Research, and the National Academies.