Project Grant 2051196

Award Date 7/1/21
Completion Date 6/30/24
Dollars Obligated $330K
Funding Federal Agency
National Science Foundation
Federal Grant Program
47.075
Assistance Type
Project Grant
Place of Performance
Cambridge, MA 02138, USA
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The team will develop statistical frameworks to estimate the causal effects of algorithm-generated pretrial risk assessment score recommendations on judicial decisions, evaluate the accuracy of such risk assessment scores, and assess how the scores impact the fairness of human decisions. Jiang will contribute to data analysis, help develop open-source R software packages to implement the frameworks, and supervise a graduate student. He will also collaborate with the team to produce research papers, policy reports, and applied academic papers applying the methodology to Greiner's datasets. The research aims to contribute to understanding how machine learning impacts human judgment in a context consequential for justice and fairness.

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