this post was submitted on 14 Jul 2023
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Using bigger AI training data sets may produce more racist results (archive.is)
submitted 2 years ago by cyu@sh.itjust.works to c/technology@lemmy.world
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Contrary to Silicon Valley wisdom, training AIs on larger data sets could worsen their tendency to replicate societal biases and racist stereotypes

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[โ€“] Zeth0s@reddthat.com 6 points 2 years ago* (last edited 2 years ago) (1 children)

The problem of current LLM implementations is that they learn from scratch, like taking a baby to a library and telling him "learn, I'll wait out in the cafeteria".

You need a lot of data to do so, just to learn how to write, gramma, styles, concepts, relationships without any guidance.

This strategy might change in the future, but the only solution we have now is to refine the model afterward, let's say.

Tbf biases are integral part of literature and human artistic production. Eliminating biases means having "boring" texts. Which is fine for me, but a lot of people will complain that AI is dumb and boring

[โ€“] KSPAtlas@sopuli.xyz 2 points 2 years ago

Does ai also need to learn about its grandpa?