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#46 Fairness and Representation in AI with Tẹjúmádé Àfọ̀njá

#46 Fairness and Representation in AI with Tẹjúmádé Àfọ̀njá

CISPA TL;DR - Der Podcast über KI- und IT-Sicherheitsforschung vor 7 Monaten

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From job applications to loan approvals, AI systems are
increasingly being explored and deployed in decisions that shape
people’s lives. But what happens when these systems learn from
biased data? Can they ever be truly fair? In this episode, CISPA
researcher Tẹjúmádé Àfọ̀njá unpacks why more accurate predictions
in a model don’t automatically mean fairer outcomes, why
representation in AI and machine learning matters, and why it’s not
only important how AI systems are built – but also by whom. Read
Tẹjúmádé's full papers here: Paper on loan approvals:
https://aclanthology.org/anthology-files/pdf/findings/2025.findings-emnlp.947.pdf
Paper on World Wide Dishes:
https://dl.acm.org/doi/full/10.1145/3715275.3732019 More about her
and her research: https://tejuafonja.com