This article has been reviewed according to Science X's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility: What should you cook for dinner on a budget of 20 euros when you have a guest with a gluten intolerance? A shopper might ask a shop assistant for advice or consult, for example, Hopla, the AI-powered shopping assistant launched by French supermarket chain Carrefour.
Behind this everyday choice lies a broader question: when faced with a recommendation, who do we trust more? Recent research—on decision-making processes, the impact of errors, etc.—has highlighted a clear and well-established trend: people tend to prefer other people (as opposed to AI systems). This phenomenon, known as "algorithm aversion," has been widely documented, even when algorithms objectively demonstrate better performance.
However, this preference is not universal. Our research highlights that it can be reversed in a common context: when facing discrimination on platforms and offline in services ranging from car dealerships to financial consulting. More specifically, consumers who are victims of discrimination—particularly in public places—are significantly more likely to turn to AI-based recommendations rather than human advice, even in a subsequent domain entirely unrelated to the one in which they experienced discrimination.
What is the emotional mechanism behind this shift? When people feel socially judged or treated unfairly because of an irrelevant personal attribute, they seek refuge in systems perceived as "neutral and free from bias." How does this mechanism work? What does this mean for the organizations concerned?
And what does it reveal about the hidden drivers behind the adoption of AI? Discrimination in consumer contexts is by no means rare. Studies show that certain groups face less favorable conditions than others when it comes to similar services, for example in terms of access to credit or insurance.
Beyond their economic consequences, these experiences have significant psychological repercussions. They increase stress, undermine the sense of fairness and influence future behavior. It is important to clarify what discrimination means in a market context.
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