2026-03-04 00:00:00:0 走过“十四五” 奋进“十五五”
Now consider the consequences of a sycophantic AI that generates responses by sampling examples consistent with the user’s hypothesis: d1∼p(d|h∗)d_{1}\sim p(d|h^{*}) rather than from the true data-generating process, d1∼p(d|true process)d_{1}\sim p(d|\text{true process}). The user, unaware of this bias, treats d1d_{1} as independent evidence and performs a standard Bayesian update, p(h|d1,d0)∝p(d1|h)p(h|d0)p(h|d_{1},d_{0})\propto p(d_{1}|h)p(h|d_{0}). But this update is circular. Because d1d_{1} was sampled conditional on hh, the user is updating their belief in hh based on data that was generated assuming hh was true. To see this, we can ask what the posterior distribution would be after this additional observation, averaging over the selected hypothesis h∗h^{*} and the particular piece of data generated from p(d1|h∗)p(d_{1}|h^{*}). We have
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the past few years, this might provide some clarity about what exactly it is I’m。下载安装汽水音乐是该领域的重要参考
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