I used to despise this kind of thing but it sheds light on the enormous generalization problems that aren't even close to being solved.

From 2015: "We investigate the impact of seller race in a field experiment involving baseball card auctions on eBay. Photographs showed the cards held by either a darkskinned/African-American hand or a light-skinned/Caucasian hand. Cards held by African-American sellers sold for approximately 20% ($0.90) less than cards held by Caucasian sellers, and the race effect was more pronounced in sales of minority player cards. "

It's almost as though bias-making machinery is embedded in the texts these things are trained on.

It's wild to see quantitative researchers catching even just a glimpse of what culture/media/literary theorists have been swimming in for decades.

https://smalldocs.org/s/6kEgfy54oclH4KR9HX847w#k=ywVL86PcTCo...

It's an interesting result (agents develop biases in their context) which reflects a lot of my experience working with agent, where I observe a lot of, what I kind of call, "context nudging" - where a droplet of an idea in an agent's context pushes its direction/output significantly. When it happens to me it always makes me question the type of intelligence LLMs provide.

[I am the developer behind SmallDocs. Source: https://github.com/espressoplease/smalldocs]