Algorithmic Transparency via Quantitative Input Influence: Theory and Experiments with Learning Systems

Proceedings - 2016 IEEE Symposium on Security and Privacy, SP 2016

Volumn , Issue , 2016, Pages 598-617

  Datta, Anupam ^a   Sen, Shayak ^a   Zick, Yair ^a  

^a CARNEGIE MELLON UNIVERSITY   (United States)

Author keywords

fairness; machine learning; transparency

Indexed keywords

ALGORITHMS; ARTIFICIAL INTELLIGENCE; DECISION MAKING; LEARNING SYSTEMS; ONLINE SYSTEMS; TRANSPARENCY;

DECISION MAKING PROCESS; DECISION-MAKING SYSTEMS; EMPIRICAL VALIDATION; FAIRNESS; FORMAL FOUNDATION; PERSONALIZATIONS; STANDARD MACHINES; TRANSPARENCY MECHANISM;

LEARNING ALGORITHMS;

EID: 84987644106     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/SP.2016.42     Document Type: Conference Paper

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