Equity, Inclusion & the Digital Language Divide

Fri, 01 Nov 2024 00:00:00 +0000

The benefits and harms of generative AI are not distributed equally. This project examines how AI systems disproportionately impact long-tail users—speakers of underserved languages and members of marginalized communities who are often excluded from model training and evaluation. By quantifying these disparities and analyzing how generative AI amplifies existing inequities in the information ecosystem, this work makes the case that equitable AI is not optional but essential. It bridges AI for Social Good with Safe and Ethical AI, centering the voices and needs of communities that current technologies routinely overlook.

Related Publications:

Generative AI Disproportionately Harms Long Tail Users (2024, Computer)
The Longtail Impact of Generative AI on Disinformation (2024, IEEE IS)
Detecting False Claims in Low-Resource Regions (2022, ACL) — cross-listed
BLUFF (2026) — cross-listed

Generative AI Disproportionately Harms Long Tail Users

Fri, 01 Nov 2024 00:00:00 +0000

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This work examines how Generative AI systems disproportionately impact longtail users, highlighting critical equity concerns in AI deployment.

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Digital Inequality | Jason S. Lucas

Equity, Inclusion & the Digital Language Divide

Generative AI Disproportionately Harms Long Tail Users