Imagine the following scenario: A university student needs a reading list for an essay on primitive art. In one version of the story, he asks a professor. In another he asks ChatGPT. He then plans to gather public feedback through short surveys, all unpaid, and strangers are asked how many they would fill out.
People who were told the reading list came from a professor, were more likely to sign up for the survey. The student, the essay and the request were identical, and he lost about one survey’s worth of goodwill because of where his reading list came from.
That experiment is one of eight studies in a paper by Jianning Dang and Li Liu, published in the Journal of Personality and Social Psychology. Psychologists have spent years documenting “AI aversion,” the tendency to distrust an algorithm’s judgment even when it matches or beats that of a human expert. Dang and Liu asked the obvious next question, which is whether that distrust transfers to the person using the tool. Across 2,317 participants in the U.K. and China, it did.
What they measured
The design was pretty much the same across studies. Participants read a short scenario in which someone sought advice from either an AI tool or a human expert including a hiring manager screening video interviews, a person choosing a wedding gift for a friend, a student, a patient, and a primary school teacher preparing reading materials. They then rated that person on two sets of traits related to dehumanization. “Human nature” traits such as friendly, sociable and trusting are the ones that separate us from machines. “Human uniqueness” traits such as rational and mature are the ones that separate us from animals.
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Across the board, when a person consulted AI instead of a human expert, they were dehumanized more. In the wedding gift experiment, for example, the person who asked ChatGPT for gift ideas scored lower on the humanness scale. In most of the studies the gap was wider on the emotional traits than on the rational ones.
The first study shows this most clearly, where 200 U.K. participants wrote a free-form description of a hiring manager named James, covering what he thinks, feels and intends. Those who had read that James used a recruiting algorithm used fewer words like “feel” and “care”. Words like “plan” and “think” appeared at the same rate in both groups. Respondents in the study were willing to grant the AI user a working mind with such rational traits, but they were less sure about his emotional states.
In addition, participants liked the AI user less, but the humanness gap held after controlling for liking. It also held regardless of how much experience or knowledge participants had with AI, so unfamiliarity is a poor explanation.