Equality, Equity, and Algorithms: Learning from Justice Rosalie Abella

Author:

Minow Martha1

Affiliation:

1. 300th Anniversary University Professor, Harvard University, Cambridge, MA, United States.

Abstract

In the United States, employers, schools, and governments can face two competing legal requirements regarding racial classifications: on the one hand, there are legal restrictions against conscious uses of racial classifications, and on the other hand, there are rules forbidding racially disparate impacts. Growing use of machine learning and other predictive algorithmic tools heightens this tension as employers and other actors use tools that make choices about contrasting definitions of equality and anti-discrimination; design algorithmic practices against explicit or implicit uses of certain personal characteristics associated with historic discrimination; and address inaccuracies and biases in the data and algorithmic practices. Justice Rosalie Abella’s approach to equality issues, highly influential in Canadian law, offers guidance by directing decision makers to (a) acknowledge and accommodate differences in people’s circumstances and identities; (b) resist attributing to personal choice the patterns and practices of society, including different starting points and opportunities; and (c) resist consideration of race or other group identities as justification when used to harm historically disadvantaged groups, but permit such consideration when intended to remedy historic exclusions or economic disadvantages.

Publisher

University of Toronto Press Inc. (UTPress)

Subject

Law,Sociology and Political Science

Reference81 articles.

1. Canada,Report of the Commission on Equality in Employment(Ottawa: Minister of Supply and Services Canada, 1984) [Employment Equity Report] (Rosalie Abella, comm.). A journalist recently noted that the ‘Abella Commission’ was given only one commissioner, one year to work, and one million dollars when, shortly thereafter, a commission on the sealing industry received seven commissioners, two years to work, and seven million dollars. Paul Wells, ‘Rosie Abella Said She’d Answer Questions When She Turned 75,’ Maclean’s (15 June 2021), online: [Wells, ‘Rosie Abella’].

2. See Cathy O'Neil, Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy (New York: Broadway Books, 2016) at 3

3. Solon Barocas & Andrew D Selbst, 'Big Data's Disparate Impact' (2016) 104 Cal L Rev 671 at 674-5

4. Danielle Keats Citron & Frank Pasquale, 'The Scored Society: Due Process for Automated Predictions' (2014) 89 Wash L Rev 1 at 13-16

5. James Grimmelmann & Daniel Westreich, 'Incomprehensible Discrimination' (2016) 7 Cal L Rev Online 164 at 169 (noting one commentator's argument that, under the current constitutional order, data mining is 'permitted to exacerbate existing inequalities in difficult-to-counter ways')

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Integrating AI in Higher Education;Advances in Educational Technologies and Instructional Design;2024-04-19

2. Algorithmic Governance and Social Vulnerability: A Value Analysis of Equality and Trust;SSRN Electronic Journal;2024

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