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.
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When we investigated these pages, there were some clear indicators that something was wrong. The biggest one is that the Microsoft login flow isn't hosted on a Microsoft domain. While websites can use Microsoft as an authorization source, this normally involves redirecting to a Microsoft-controlled page and then back to the original site once authorization is complete. That's not what's happening here. Beyond that, none of the secondary interface elements work. "Create a new account," "Sign in options," "Can't access your account?" all either do nothing when clicked or redirect back to the current page. This is something we see over and over: phishing kits only implement the happy path where the victim enters their credentials without clicking anything else. Finally, the error messages are wrong. We went through a legitimate Microsoft auth flow and recorded the error states (for example, entering a non-existent email) and compared them to what the phishing page displayed. The language didn't match.
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本报北京3月2日电 中共中央政治局委员、外交部长王毅2日应约同伊朗外长阿拉格齐通电话。