Certifying and removing disparate impact

Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Volumn 2015-August, Issue , 2015, Pages 259-268

  Feldman, Michael ^a   Friedler, Sorelle A ^a   Moeller, John ^b   Scheidegger, Carlos ^c   Venkatasubramanian, Suresh ^b  

^a HAVERFORD COLLEGE   (United States)

^b UNIVERSITY OF UTAH   (United States)

^c UNIVERSITY OF ARIZONA   (United States)

Author keywords

Disparate impact; Fairness; Machine learning

Indexed keywords

ALGORITHMS; ARTIFICIAL INTELLIGENCE; LEARNING SYSTEMS;

CLASSIFICATION ACCURACY; DISPARATE IMPACT; FAIRNESS; LEGAL SCRUTINY;

DATA MINING;

EID: 84954161181     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2783258.2783311     Document Type: Conference Paper

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