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by @danabra.mov
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by @danabra.mov
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by @jimpick.com
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by @atsui.org
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in 2019 I had a role training staff at a university and research library about ML + AI software applications and concepts almost all the existing literature on this subject stressed the problem of information bias, with a particular highlight on its minimisation of women & POC we KNEW. we WARNED
1d
When utilized in literature review, LLMs consistently 1. fail to mention female authors in female-led literatures, 2. insist that men are more influential or more heavily cited when this is contradicted by objective citation counts, and 3. attribute women’s work to hallucinated male scholars.