ABCinML: Anticipatory Bias Correction in Machine Learning Applications

14 June 2022

Papers citing "ABCinML: Anticipatory Bias Correction in Machine Learning Applications"

8 / 8 papers shown

Title
Toward Operationalizing Pipeline-aware ML Fairness: A Research Agenda for Developing Practical Guidelines and Tools Maximilian Schambach Rakshit Naidu Rayid Ghani Kit T. Rodolfa Daniel E. Ho Hoda Heidari FaML 30 13 0 29 Sep 2023
Diverse Perspectives Can Mitigate Political Bias in Crowdsourced Content Moderation Jacob Thebault-Spieker Sukrit Venkatagiri Naomi Mine Kurt Luther 15 3 0 23 May 2023
Fairness and Sequential Decision Making: Limits, Lessons, and Opportunities Samer B. Nashed Justin Svegliato Su Lin Blodgett FaML 17 6 0 13 Jan 2023
Law Informs Code: A Legal Informatics Approach to Aligning Artificial Intelligence with Humans John J. Nay ELM AILaw 84 27 0 14 Sep 2022
Bias Mitigation for Machine Learning Classifiers: A Comprehensive Survey Max Hort Zhenpeng Chen Jie M. Zhang Mark Harman Federica Sarro FaML AI4CE 26 159 0 14 Jul 2022
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 294 4,187 0 23 Aug 2019
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments Alexandra Chouldechova FaML 185 2,082 0 24 Oct 2016
Efficient Estimation of Word Representations in Vector Space Tomáš Mikolov Kai Chen G. Corrado J. Dean 3DV 228 31,150 0 16 Jan 2013