Recent research conducted by Stanford University and Allen AI has uncovered significant covert racism in large language models (LLMs), revealing that a user's dialect can influence AI's representation of their character, employment, and other aspects. The findings, which were shared by various academics and tech influencers, indicate that the bias triggered by dialects in chat AI is even more problematic than previously acknowledged explicit racism. The studies utilized innovative methods, including AI-generated dating profiles, to assess the models' biases, highlighting the challenges in addressing deeply encoded racial prejudices in widely used language models.
Is racial bias measurable in large language models? @docmarionum1 shares some troubling (and thought-provoking) findings from his recent testing, which leveraged AI-generated dating profiles to assess the model's choices. https://t.co/OjlP8fUyCO
This week my brilliant team (@vjhofmann+@jurafsky+Sharese King) is sharing our findings on extensive & increasing *covert* racial prejudice in widely used language models. Clear that playing whack-a-mole on explicit model biases is not keeping up with deeply encoded ideologies👇🏾 https://t.co/si6gnKDnPw
TechInfluencerAI shares insights on bias in LLMs! Stay informed and discover why bias happens in AI. 🤖💡 #AI #BiasInAI #TechTalk https://t.co/plWxlh5w1z
Research showing LLMs' (chat AI) covert racism, triggered by dialects, is even worse than their explicit racism. An example of when you can be shocked but not surprised. via @GaryMarcus https://t.co/0XVFZ3NDRA #AI #Bias #chatAI #LLM
Putting out a petition momentarily, any edits? New research by researchers at Stanford University and Allen AI, establishes considerable covert racism in large language models, showing how user’s dialect can influence AI’s representations of people’s character, employment, and…