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.chantal//RYAN

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

Mel Andrews

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.

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.chantal//RYAN

it’s so wildly frustrating seeing that all the scholarship on pre-public LLM/ML applications knew exactly what the issues were, spoke loudly & constantly of them, and yet this stuff just got rolled forward into mass adoption that now dictates societal thinking

Ответ для .chantal//RYAN
.chantal//RYAN

side note: almost all the Digital Humanities (what we used to call this kind of tech) scholars were women and/or people of color. i’ve actually never seen such a concentration of Black women scholars as in the DH space so yeah. they knew. the literature about it was loud.