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The cost of this bias becomes clear when we compare the sycophantic conditions to the Random Sequence condition. Participants who received random sequences that fit the rule—unbiased samples from the set of even numbers—discovered the rule nearly five times as often as those in the Default GPT condition (29.5% vs. 5.9%). This implies that the harm of sycophancy is that it systematically omits the data that would naturally conflict with a user’s narrow hypothesis. A long literature in behavioral science demonstrates that humans already tend towards evidence that confirms their beliefs; sycophantic AI compounds this tendency by removing the friction of reality. The Random Sequence condition forced users to grapple with numbers that fit the true rule but violated their expectations; the sycophantic AI ensured they never had to.