LLMs judge trustworthiness and competence from faces, just like humans do.

AI models showed even stronger bias than humans when judging competence from appearance.

None of the tested LLMs responded neutrally or refused biased prompt requests.

People are inherently biased. Are machines running artificial intelligence (AI) large language models (LLMs) biased too? A new Harvard University study reveals that LLMs are biased like people and make character assumptions on competence and trustworthiness based on facial features.

“Contrary to the promise of enhancing human decisions, these findings expose the recklessness of using language models in selection contexts,” wrote Mahzarin Banaji, Steven Lehr, and Yash Lothe, who conducted the study that was recently published in PNAS Nexus, a journal by the Proceedings of the National Academy of Sciences (PNAS).

It has been long established that humans are biased. For example, in modern psychology, American psychologist Edward Lee Thorndike (1874-1949), introduced the concept of the halo effect, the tendency for a general impression of a person to bias judgment of that person’s character traits, in his study "A constant error in psychological ratings" published in 1920 in the Journal of Applied Psychology. In Thorndike’s research, he discovered that when commanding officers were asked to rate their subordinates without speaking to them, they rated the........

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