One of the promises of artificial intelligence is that it will mimic, and perhaps even improve, on human thinking. One of those hoped-for improvements was that AI would not exhibit human biases. Turns out that in one area, AI can indeed mimic human thinking, and it's in that field of bias. As Harvard psychologist Mahzarin Banaji -- one of the creators of the widely used implicit bias test -- explains in this Social Science Bites podcast, AI platforms both mimic human bias and even amplify it.
In her second appearance on the podcast series, Banaji tells interviewer David Edmonds that even she was surprised how overtly bias shows up in AI results. She recalls her jaw dropping after she queried a large language model about what biases it might have, and it replied "I am a white male," and then how, a month later when queried the same thing it came back with a lengthy 'correct' answer about how it could be biased.
"[W]hat stunned me, and why I began to work on these LLMs, is because it became clear that the creators of these models were actually doing us a massive disservice by creating in these machines two kinds of thought: what the machine knows that it's learned, and now what the machine is going to say, which I'll just call LLM hypocrisy."
Banaji is the Richard Clarke Cabot Professor of Social Ethics in the Department of Psychology at Harvard, a position she has held since 2002. She is also the first Carol K. Pforzheimer Professor at the Radcliffe Institute for Advanced Study, and the George A. and Helen Dunham Cowan Chair in Human Dynamics at the Santa Fe Institute. A former president of the Association of Psychology Science (2010-11), she was named William James Fellow by the APS and is also a fellow of the American Academy of Political and Social Science, the Society for Experimental Psychologists, Society for Experimental Social Psychology, and the American Academy of Arts and Sciences.