Large language models develop novel social biases through adaptive exploration

Posted by paimapi 13 hours ago

Large language models develop novel social biases through adaptive exploration(openreview.net)

170 points | 88 commentspage 3

alescalaios 1 hour ago|

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lucaprata 3 hours ago||

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ct520 9 hours ago||

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stingraycharles 12 hours ago||

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lhk931122 10 hours ago||

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BoingBoomTschak 12 hours ago||

> Following psychological tradition, we define bias as behaviors that tilt away from equality

Is this a joke?

ezwoodland 11 hours ago||

How else would you define bias if not an offset from equality or zero mean?

For example, the b in y=mx+b

zahlman 11 hours ago||

> How else would you define bias if not an offset from equality or zero mean?

As an offset from what the ground truth justifies. Suppose the researchers had decided to load the dice when creating the fake sample data; an unbiased analyst should seek to discover the extent of that, not insist on reporting equality.

AnimalMuppet 10 hours ago||

Well, in this study, they explicitly had equality - all four groups were as likely to succeed. So any difference in hiring was actual bias (or statistical noise).

zb3 12 hours ago||

No, this is the religion here

FailMore 12 hours ago|

Because it's hard to find the time to read an academic paper I had an agent summarise it in a few slides:

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]

zahlman 11 hours ago||

It's cool that you're making a seemingly useful bit of software, but this reads like spam. "I had an agent summarize this" isn't particularly relevant to your opinion of it, unless you think the summary may have been misleading; so it comes across as a poor excuse to introduce your self-promotion.

I agree that "context nudging" is a thing. ChatGPT often seems to try really hard to connect ideas back to things I said earlier in the conversation even when it really shouldn't be relevant. But I would call that a matter of "wisdom" more than "intelligence".

fc417fc802 11 hours ago||

> what I kind of call, "context nudging" - where a droplet of an idea in an agent's context pushes its direction/output significantly

I like this description. I constantly notice that how I ask a question strongly impacts the quality and technical merit of the answer I receive which similarly leads me to question any claims of generalization. It should go without saying that they're still incredibly useful tools when wielded properly.