Keen bosses, strange mistakes and a looming threat: workers on training AI to do their jobs

· · 来源:dev资讯

Now, if you do all of this and your team still only promotes the person who builds the most elaborate system… that’s useful information too. It tells you something about where you work. Some cultures genuinely value simplicity. Others say they do, but reward the opposite. If you’re in the second kind, you can either play the game or find a place where good judgment is actually recognized. But at least you’ll know which one you’re in.

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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.

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