%% This BibTeX bibliography file was created using BibDesk. %% http://bibdesk.sourceforge.net/ %% Created for Laine, Riku P at 2019-08-02 09:38:23 +0300 %% Saved with string encoding Unicode (UTF-8) @inproceedings{DBLP:conf/icml/Kusner0LS19, author = {Matt J. Kusner and Chris Russell and Joshua R. Loftus and Ricardo Silva}, title = {Making Decisions that Reduce Discriminatory Impacts}, booktitle = {{ICML}}, series = {Proceedings of Machine Learning Research}, volume = {97}, pages = {3591--3600}, publisher = {{PMLR}}, year = {2019} } @inproceedings{tolan2019why, Acmid = {3326705}, Address = {New York, NY, USA}, Author = {Tolan, Song\"{u}l and Miron, Marius and G\'{o}mez, Emilia and Castillo, Carlos}, Booktitle = {Proceedings of the Seventeenth International Conference on Artificial Intelligence and Law}, Date-Added = {2019-08-02 06:37:23 +0000}, Date-Modified = {2019-08-02 06:38:23 +0000}, Doi = {10.1145/3322640.3326705}, Isbn = {978-1-4503-6754-7}, Keywords = {algorithmic bias, algorithmic fairness, criminal recidivism, machine learning, risk assessment}, Location = {Montreal, QC, Canada}, Numpages = {10}, Pages = {83--92}, Publisher = {ACM}, Series = {ICAIL '19}, Title = {Why Machine Learning May Lead to Unfairness: Evidence from Risk Assessment for Juvenile Justice in Catalonia}, Url = {http://doi.acm.org/10.1145/3322640.3326705}, Year = {2019}, Bdsk-Url-1 = {http://doi.acm.org/10.1145/3322640.3326705}, Bdsk-Url-2 = {http://dx.doi.org/10.1145/3322640.3326705}} @article{pearl2010introduction, Author = {Pearl, Judea}, Date-Added = {2019-08-02 06:37:23 +0000}, Date-Modified = {2019-08-02 06:37:23 +0000}, Journal = {The international journal of biostatistics}, Number = {2}, Publisher = {De Gruyter}, Title = {An introduction to causal inference}, Volume = {6}, Year = {2010}} @inproceedings{lakkaraju2017selective, Acmid = {3098066}, Address = {New York, NY, USA}, Author = {Lakkaraju, Himabindu and Kleinberg, Jon and Leskovec, Jure and Ludwig, Jens and Mullainathan, Sendhil}, Booktitle = {Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining}, Date-Added = {2019-08-02 06:37:23 +0000}, Date-Modified = {2019-08-02 06:37:23 +0000}, Doi = {10.1145/3097983.3098066}, Isbn = {978-1-4503-4887-4}, Keywords = {evaluating machine learning algorithms, selective labels, unmeasured confounders, unobservables}, Location = {Halifax, NS, Canada}, Numpages = {10}, Pages = {275--284}, Publisher = {ACM}, Series = {KDD '17}, Title = {The Selective Labels Problem: Evaluating Algorithmic Predictions in the Presence of Unobservables}, Url = {http://doi.acm.org/10.1145/3097983.3098066}, Year = {2017}, Bdsk-Url-1 = {http://doi.acm.org/10.1145/3097983.3098066}, Bdsk-Url-2 = {http://dx.doi.org/10.1145/3097983.3098066}} @article{jung2018algorithmic, Author = {Jung, Jongbin and Shroff, Ravi and Feller, Avi and Goel, Sharad}, Date-Added = {2019-08-02 06:37:23 +0000}, Date-Modified = {2019-08-02 06:37:23 +0000}, Journal = {arXiv preprint arXiv:1805.01868}, Title = {Algorithmic decision making in the presence of unmeasured confounding}, Year = {2018}} @article{dearteaga2018learning, Author = {De-Arteaga, Maria and Dubrawski, Artur and Chouldechova, Alexandra}, Date-Added = {2019-08-02 06:37:23 +0000}, Date-Modified = {2019-08-02 06:37:23 +0000}, Journal = {arXiv preprint arXiv:1807.00905}, Title = {Learning under selective labels in the presence of expert consistency}, Year = {2018}}