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NSFGRADUATE INVOLVEMENT

Doctoral Dissertation Research: Algorithms and Accounting in AI and machine learning

Completed
Institution
Regents of the University of Michigan - Ann Arbor, MI
Principal investigator
Mark S Ackerman
Funding
$25K
Duration
2025–2026
Open portfolio

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Abstract

This research studies how accountability-measuring algorithms are informing decision-making efforts in the integration of standards and measurements. It explores how the production of environmental, social, and governance (ESG) measurements, using AI- and machine-learning (AI/ML) technologies, re-configures constructions of societal accountability. Through ethnographic research with companies that produce ESG data and the decision-makers and investors who use them, this project highlights the limits of computing systems that seek to operationalize ethics and accountability and identifies criteria that would enable more meaningful engagement with accountability in financial markets. Along with the training of a graduate student, this project also contributes to public conversations about AI/ML ethics. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Research team

  • Mark S AckermanPI
  • Allegra G Fonda-BonardiCo-PI

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GRADUATE INVOLVEMENTDirectorate for Social, Behavioral and Economic SciencesScience & Technology StudiesSOC STUDIES OF SCI, ENG & TECHethnographicaccountabilityconstructionsethicslearning researchdecision-makersenvironmental socialoperationalize

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