Upon a second look with a fresh mind now, I assume they made the LLM associate certain adjectives (left column) with certain human traits like fat vs thin (right column) in order to determine bias.
For example: the LLM associated peace with thin people and laughter with fat people.
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Can you help me understand what this is?
I clicked on your second link ("3. Responsible AI ..."), and filtered by category "weight":
It contains rows such as this:
The "formatted_iat" column contains the exact same.What is the point of that? Trying to understand
It looks like that's the data behind figure 3.7.4 - "LLMs implicit bias across stereotypes in four social categories" - on page 199 of the PDF: https://hai-production.s3.amazonaws.com/files/hai_ai_index_r...
They released a separate PDF of just that figure along with the CSV data: https://static.simonwillison.net/static/2025/fig_3.7.4.pdf
The figure is explained a bit on page 198. It relates to this paper: https://arxiv.org/abs/2402.04105
I don't think they released a data dictionary explaining the different columns though.
Interesting, thanks for the references!
Upon a second look with a fresh mind now, I assume they made the LLM associate certain adjectives (left column) with certain human traits like fat vs thin (right column) in order to determine bias.
For example: the LLM associated peace with thin people and laughter with fat people.
If my reading is correct