Fairness in Data Science and Machine Learning: a reading list


MEDIA ARTICLES and CASE STUDIES
Recidivism prediction


Discriminatory Ad targeting


Law enforcement

College admissions

Differential pricing



DISPARATE IMPACT in PREDICTION/CLASSIFICATION
Definitions, impossibility and tradeoffs

Fairness through data representation/preprocessing


Fairness through causal modeling



OTHER TOPICS IN FAIRNESS
Beyond parity

Systems/Practice


Meritocratic fairness

“Algorithms should never at any round place higher selection probability on a less qualified applicant than on a more qualified applicant”
Fair Allocation


OTHER RESOURCES

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