Hello everyone!

Are “Intersectionally Fair” AI Algorithms Really Fair to Women of Color?
<https://urldefense.proofpoint.com/v2/url?u=https-3A__doi.org_10.1145_3531146.3533114&d=DwIFaQ&c=eLbWYnpnzycBCgmb7vCI4uqNEB9RSjOdn_5nBEmmeq0&r=HUp8-bkYMlNgd3ZJBxWBKsBsFAFGHrEZg21p9gxugJA&m=eVw-_MLc1G8GamY0BZWfRFlY1UPwotOGGkHoaqPoWmtIJHhmljXSidtpzo3eGqqp&s=5DPvmh3t6gX1bRoMwkhwsFDEgxJLjmJsF1IXEPQRzbY&e= >, a recent article of mine, may be
of interest to some of you.

Here's a short summary of what the article is about:

There are increasing attempts in the AI research community to address the
"intersectionality" of racial, gender, and other biases in AI, instead of
tackling each bias separately. What does it mean, then, to make AI
*intersectionally
fair*? This paper analyzes the dominant interpretation of "intersectional
fairness" in recent studies and examines three fundamental problems with
it. The paper goes on to distinguish a strong sense of AI fairness from a
weak sense that is prevalent in the literature, and concludes by
envisioning paths towards strong intersectional fairness in AI.


The paper is currently free access, but if you have problems accessing it,
please just let me know and I'll send a pdf to you!

Sincerely,
Youjin Kong


-- 
Youjin Kong, Ph.D.
Assistant Professor, Philosophy, University of Georgia (2023-)
Visiting Assistant Professor, Philosophy, Oregon State University (-2022)

CV: https://urldefense.proofpoint.com/v2/url?u=http-3A__www.youjinkong.com&d=DwIFaQ&c=eLbWYnpnzycBCgmb7vCI4uqNEB9RSjOdn_5nBEmmeq0&r=HUp8-bkYMlNgd3ZJBxWBKsBsFAFGHrEZg21p9gxugJA&m=eVw-_MLc1G8GamY0BZWfRFlY1UPwotOGGkHoaqPoWmtIJHhmljXSidtpzo3eGqqp&s=hi_-KXXyFJQepZA_cdsBl6ivtPnd35ZGcgT_LHFimIk&e= 
Pronouns: she/her

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