And finally, be transparent about it. Candidates deserve to know how AI is being used in your evaluation process — which tools are involved, what they're measuring, and how those results factor into decisions. Beyond just being the ethical baseline, transparency actually tends to improve the candidate experience. People are generally a lot more comfortable with AI evaluation when they understand what's going on, rather than feeling like they're being judged by some invisible black box.
The experts point to an unclear boundary between what is shared voluntarily and what is collected automatically – a boundary that can be difficult to detect.
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第三十条 行政执法机关对行政执法监督机构作出的处理结果有异议的，可以向其提出并说明理由，行政执法监督机构应当及时处理。
贝恩咨询预测，在温和情景下，未来AI推理基础设施支出可能下降30%-50%。这正是杰文斯悖论的反向演绎：通常情况下，资源使用效率的提升会增加总需求；但在AI领域，当算法优化的速度超过应用落地的速度时，效率提升反而先冲击了硬件供应商的定价权。