在人工智能时代帮助人们选择职业
Helping People Choose Careers in the Age of AI
中文总结 AI 辅助
探讨人工智能时代人们如何选职业，先比较六种职业受人工智能任务自动化影响的预测，再基于相关数据提出新实证模型，发现模型预测有显著异质性，通过平均五个模型预测减少不确定性，报告了不同类别间薪资与人工智能影响的权衡及相关结论。
中文摘要 AI 辅助
当人工智能迅速改变工作性质时，人们应如何选择职业？我们首先比较了最近六种关于职业受人工智能任务自动化影响的预测，审视其方法和假设。接着基于来自Anthropic和OpenAI的2025年查询数据，提出了一种新的职业人工智能影响实证模型。我们发现模型预测存在显著异质性，2020年后发布的模型显示人工智能影响、薪资和职业复杂性之间呈正相关。为减少因任务自动化潜力假设异质性带来的不确定性，我们对包括自己模型在内的五个模型的预测进行平均。利用这些平均值，我们报告了不同兴趣类别、O*NET工作区和工作领域中薪资与人工智能影响之间可能的权衡。医疗保健行业的工作在高薪与低人工智能影响之间展现出最强的平衡。在大量使用Anthropic的Claude的工作中，将其用作人类工作补充而非替代的工作薪资略高，不过这种模式是否成立将取决于各领域采用的使用规范。
英文摘要
How should people choose careers when artificial intelligence (AI) is rapidly transforming the nature of work? We first compare six recent projections of occupational exposure to task automation with AI, examining their methods and assumptions. We then propose a new empirical model of occupational AI exposure based on 2025 query data from Anthropic and OpenAI. We find marked heterogeneity in model predictions, though models published since 2020 show positive relationships among AI exposure, salaries, and occupational complexity. To reduce uncertainty due to heterogeneous assumptions about task automation potential, we average the projections from five models, including our own. Using these averages, we report on likely tradeoffs between salaries and AI exposure across interest categories, O*NET Job Zones, and job fields. Jobs in healthcare practice show the strongest balance of higher pay with lower AI exposure. Among jobs making high use of Anthropic's Claude, those that use it as a complement rather than a substitute for human work are modestly higher-paying, though whether this pattern holds will depend on usage norms adopted in each field.
