Fetching the paper…
Reading the bibliography…
Predictive models are increasingly deployed for the purpose of determining access to services such as credit, insurance, and employment.
Crafting papers on machine learning
Langley, P · 2000
Earlier work this paper cites.
Big-data computing: Creating revolutionary breakthroughs in commerce, science and society, 2008
Bryant, Randal, Katz, Randy H, and Lazowska, Edward D · 2008
Earlier work this paper cites.
Discrimination-aware data mining
Pedreshi, Dino, Ruggieri, Salvatore, and Turini, Franco · 2008
Earlier work this paper cites.
Three naive bayes approaches for discrimination-free classification
Calders, Toon and Verwer, Sicco · 2010
Earlier work this paper cites.
Fairness-aware learning through regularization approach
Kamishima, Toshihiro, Akaho, Shotaro, and Sakuma, Jun · 2011
Cited alongside, same era.
Big data: A revolution that will transform how we live, work, and think
Mayer-Schönberger, Viktor and Cukier, Kenneth · 2013
Cited alongside, same era.
Zemel, Rich, Wu, Yu, Swersky, Kevin, Pitassi, Toni, and Dwork, Cynthia · 2013
Cited alongside, same era.
Big data’s disparate impact
Barocas, Solon and Selbst, Andrew D · 2014
Cited alongside, same era.
Big data and due process: Toward a framework to redress predictive privacy harms
Crawford, Kate and Schultz, Jason · 2014
Later among the works it cites.
Certifying and removing disparate impact
Friedler, Sorelle, Scheidegger, Carlos, and Venkatasubramanian, Suresh · 2014
Later among the works it cites.
A multidisciplinary survey on discrimination analysis
Romei, Andrea and Ruggieri, Salvatore · 2014
Later among the works it cites.
Auditing black-box models by obscuring features
Adler, Philip, Falk, Casey, Friedler, Sorelle A, Rybeck, Gabriel, Scheidegger, Carlos, Smith, Brandon, and Venkatasubramanian, Suresh · 2016
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…