Constructing categories: Moving beyond protected classes in algorithmic fairness-Reference-Cited by-同舟云学术

Constructing categories: Moving beyond protected classes in algorithmic fairness

Published:2022-03-18 Issue: Volume: Page:
ISSN:2330-1635
Container-title:Journal of the Association for Information Science and Technology
language:en
Short-container-title:Asso for Info Science & Tech

Author:

Belitz Clara¹,Ocumpaugh Jaclyn²,Ritter Steven³,Baker Ryan S.²,Fancsali Stephen E.³,Bosch Nigel¹

Affiliation:

1. School of Information Sciences University of Illinois Urbana–Champaign Champaign Illinois USA

2. Graduate School of Education University of Pennsylvania Philadelphia Pennsylvania USA

3. Carnegie Learning, Inc. Pittsburgh Pennsylvania USA

Funder

National Science Foundation of Sri Lanka

Publisher

Wiley

Subject

Library and Information Sciences,Information Systems and Management,Computer Networks and Communications,Information Systems

Link

Reference39 articles.

2. Algorithmic bias in education;Baker R. S.;International Journal of Artificial Intelligence in Education,2021

3. Big data's disparate impact;Barocas S.;California Law Review,2016

4. Information and knowledge: An evolutionary framework for information science;Bates M. J.;Information and Knowledge,2005

5. Automating procedurally fair feature selection in machine learning;Belitz C.;Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society,2021

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