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Artificial intelligence is increasingly being trusted to help employers screen CVs, rank candidates and even conduct early-stage interviews. The promise is simple: AI can process thousands of applications quickly, reduce administrative workloads and, in theory, make hiring decisions more objective than humans. According to a recent review by MIT Technology, based on the 2024 study published in the Journal of Experimental Psychology titled “Costly Exploration Produces Stereotypes With Dimensions of Warmth and Competence”, large language models (LLMs) may not only inherit human biases from the data they are trained on but also develop entirely new stereotypes based on their own experiences. Rather than simply reflecting existing prejudice, these systems can create fresh patterns of discrimination as they attempt to optimise decision-making over time.The findings are particularly significant because businesses are rapidly integrating AI into recruitment. If these systems begin making assumptions about groups of applicants after only a handful of hiring decisions, they could gradually reinforce unfair employment practices without any explicit human instruction.The research, conducted by scientists at Princeton University and the University of Chicago, builds on earlier psychological work showing how stereotypes can emerge from repeated decision-making. It suggests that the same learning strategies that make AI effective at solving complex problems can also make it unusually prone to stereotyping job candidates.