Fetching the paper…
Reading the bibliography…
Machine learning can provide predictions with disparate outcomes, in which subgroups of the population (e.g., defined by age, gender, or other sensitive attributes) are systematically disadvantaged.
The interpretation of interaction in contingency tables
Edward H Simpson. 1951 · 1951
Earlier work this paper cites.
1974-10. U.S.C. §1691 ff.: Equal Credit Opportunity Act
US Congress. 1974-10 · 1974
Earlier work this paper cites.
Sex bias in graduate admissions: Data from Berkeley
Peter J Bickel, Eugene A Hammel, and J William O’Connell. 1975 · 1975
Earlier work this paper cites.
An exploratory technique for investigating large quantities of categorical data
Gordon V Kass. 1980 · 1980
Earlier work this paper cites.
Classification and Regression Trees
Leo Breiman, Jerome Friedman, Charles J. Stone, and R.A. Olshen. 1984 · 1984
Earlier work this paper cites.
A guide to chi-squared testing . Vol. 280
Priscilla E Greenwood and Michael S Nikulin. 1996 · 1996
Earlier work this paper cites.
On the asymptotic theory of permutation statistics
Helmut Strasser and Christian Weber. 1999 · 1999
Earlier work this paper cites.
Unbiased recursive partitioning: A conditional inference framework
Torsten Hothorn, Kurt Hornik, and Achim Zeileis. 2006 · 2006
Earlier work this paper cites.
A comparison of the Benjamini-Hochberg procedure with some Bayesian rules for multiple testing
Małgorzata Bogdan, Jayanta K Ghosh, and Surya T Tokdar. 2008 · 2008
Earlier work this paper cites.
An introduction to recursive partitioning: rationale, application, and characteristics of classification and regression trees, bagging, and random forests
Carolin Strobl, James Malley, and Gerhard Tutz. 2009 · 2009
Earlier work this paper cites.
Subgroup analysis via recursive partitioning
Xiaogang Su, Chih-Ling Tsai, Hansheng Wang, David M Nickerson, and Bogong Li. 2009 · 2009
Earlier work this paper cites.
Fairness through awareness
Cynthia Dwork, Moritz Hardt, Toniann Pitassi, Omer Reingold, and Richard Zemel. 2012 · 2012
Earlier work this paper cites.
UCI machine learning repository
Kevin Bache and Moshe Lichman. 2013 · 2013
Earlier work this paper cites.
False discovery rate control is a recommended alternative to Bonferroni-type adjustments in health studies
Mark E Glickman, Sowmya R Rao, and Mark R Schultz. 2014 · 2014
Earlier work this paper cites.
Fifty years of classification and regression trees
Wei-Yin Loh. 2014 · 2014
Earlier work this paper cites.
Opinion: Why intersectionality can’t wait
Kimberlé Crenshaw. 2015 · 2015
Earlier work this paper cites.
ctree: Conditional inference trees
Torsten Hothorn, Kurt Hornik, and Achim Zeileis. 2015 · 2015
Earlier work this paper cites.
Make algorithms accountable
Julia Angwin. 2016 · 2016
Earlier work this paper cites.
How we analyzed the COMPAS recidivism algorithm
Julia Angwin, Jeff Larson, Surya Mattu, and Lauren Kirchner. 2016 · 2016
Cited alongside, same era.
Big data’s disparate impact
Solon Barocas and Andrew D. Selbst. 2016 · 2016
Cited alongside, same era.
On the (im) possibility of fairness
Sorelle A Friedler, Carlos Scheidegger, and Suresh Venkatasubramanian. 2016 · 2016
Cited alongside, same era.
Regulation EU 2016/679 of the European Parliament and of the Council of 27 April 2016, Article 22
GDPR. 2016 · 2016
Cited alongside, same era.
Equality of opportunity in supervised learning
Moritz Hardt, Eric Price, and Nathan Srebro. 2016 · 2016
Cited alongside, same era.
A comparative study of fairness-enhancing interventions in machine learning
Sorelle A Friedler, Carlos Scheidegger, Suresh Venkatasubramanian, Sonam Choudhary, Evan P Hamilton, and Derek Roth. 2019 · 2019
Later among the works it cites.
Fairness in algorithmic decision making: An excursion through the lens of causality
Aria Khademi, Sanghack Lee, David Foley, and Vasant Honavar. 2019 · 2019
Later among the works it cites.
Ethical implications and accountability of algorithms
Kirsten Martin. 2019 · 2019
Later among the works it cites.
Fairly evaluating and scoring items in a data set
Abolfazl Asudeh and HV Jagadish. 2020 · 2020
Later among the works it cites.
FlipTest: Fairness testing via optimal transport
Emily Black, Samuel Yeom, and Matt Fredrikson. 2020 · 2020
Later among the works it cites.
Intersectionality
Patricia Hill Collins and Sirma Bilge. 2020 · 2020
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Zhe Zhang and Daniel B Neill. 2016 · 2016
Cited alongside, same era.
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments
Alexandra Chouldechova. 2017 · 2017
Cited alongside, same era.
Fairer and more accurate, but for whom?
Alexandra Chouldechova and Max G’Sell. 2017 · 2017
Cited alongside, same era.
Algorithmic bias in autonomous systems. In IJCAI
David Danks and Alex John London. 2017 · 2017
Cited alongside, same era.
Inherent Trade-Offs in the Fair Determination of Risk Scores
Jon Kleinberg, Sendhil Mullainathan, and Manish Raghavan. 2017 · 2017
Cited alongside, same era.
Counterfactual fairness
Matt J Kusner, Joshua R Loftus, Chris Russell, and Ricardo Silva. 2017 · 2017
Cited alongside, same era.
On fairness and calibration
Geoff Pleiss, Manish Raghavan, Felix Wu, Jon Kleinberg, and Kilian Q Weinberger. 2017 · 2017
Cited alongside, same era.
Evaluating fairness using permutation tests
Cyrus DiCiccio, Sriram Vasudevan, Kinjal Basu, Krishnaram Kenthapadi, and Deepak Agarwal. 2020 · 2020
Later among the works it cites.
Mitigating bias in algorithmic hiring: Evaluating claims and practices
Manish Raghavan, Solon Barocas, Jon Kleinberg, and Karen Levy. 2020 · 2020
Later among the works it cites.
Fair class balancing: Enhancing model fairness without observing sensitive attributes
Shen Yan, Hsien-te Kao, and Emilio Ferrara. 2020 · 2020
Later among the works it cites.
Fairness-Aware Training of Decision Trees by Abstract Interpretation. In ACM International Conference on Information & Knowledge Management (CIKM)
Francesco Ranzato, Caterina Urban, and Marco Zanella. 2021 · 2021
Later among the works it cites.
The Chinese approach to artificial intelligence: an analysis of policy, ethics, and regulation
Huw Roberts, Josh Cowls, Jessica Morley, Mariarosaria Taddeo, Vincent Wang, and Luciano Floridi. 2021 · 2021
Later among the works it cites.
Underdiagnosis bias of artificial intelligence algorithms applied to chest radiographs in under-served patient populations
Laleh Seyyed-Kalantari, Haoran Zhang, Matthew McDermott, Irene Y Chen, and Marzyeh Ghassemi. 2021 · 2021
Later among the works it cites.
The cost of fairness in AI: Evidence from e-commerce
Moritz von Zahn, Stefan Feuerriegel, and Niklas Kuehl. 2021 · 2021
Later among the works it cites.
Algorithmic fairness in business analytics: Directions for research and practice
Maria De-Arteaga, Stefan Feuerriegel, and Maytal Saar-Tsechansky. 2022 · 2022
Closest in time.
Bringing artificial intelligence to business management
Stefan Feuerriegel, Yash Raj Shrestha, Georg von Krogh, and Ce Zhang. 2022 · 2022
Closest in time.
Post-selection inference
Arun K Kuchibhotla, John E Kolassa, and Todd A Kuffner. 2022 · 2022
Closest in time.
Algorithmic Accountability Act
117th Congress. 2022 · 2023
Closest in time.