Algorithmic Exclusion

13 Pages Posted: 7 Jun 2022

See all articles by Kendra Albert

Kendra Albert

Harvard Law School

Maggie Delano

Engineering Department, Swarthmore College

Date Written: May 27, 2022

Abstract

Is it “bias” if a system designer, purposefully or not, excludes a group from an algorithm’s development? No. Should the goal of “AI ethics” be to ensure that everyone is included in algorithmic systems? Also no.

In this chapter, we argue that the term “algorithmic exclusion” more accurately represents the way algorithmic systems engage with marginalized populations, but that even so, the goal should not necessarily be to include everyone. We define two subtypes of algorithmic exclusion (direct and indirect) and discuss how algorithmic exclusion relates to “category-based erasure.” We then discuss how answering questions of inclusion/exclusion must be done in relationship to who benefits from technologies.

Keywords: algorithmic exclusion, AI ethics, disparate impact, predatory inclusion, erasure, data violence

Suggested Citation

Albert, Kendra and Delano, Maggie, Algorithmic Exclusion (May 27, 2022). Available at SSRN: https://ssrn.com/abstract=4122529 or http://dx.doi.org/10.2139/ssrn.4122529

Kendra Albert (Contact Author)

Harvard Law School ( email )

1563 Massachusetts Ave
Cambridge, MA 02138
United States

Maggie Delano

Engineering Department, Swarthmore College ( email )

500 College Ave
Swarthmore, PA 19081
United States

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