The effects of robotics and artificial intelligence (AI) on the job market are matters of great social concern. Economists and technology experts are debating at what rate, and to what extent, technology could be used to replace humans in occupations, and what actions could mitigate the unemployment that would result. To this end, it is important to predict which jobs could be automated in the future and what workers could do to move to occupations at lower risk of automation. Here, we calculate the automation risk of almost 1000 existing occupations by quantitatively assessing to what extent robotics and AI abilities can replace human abilities required for those jobs. Furthermore, we introduce a method to find, for any occupation, alternatives that maximize the reduction in automation risk while minimizing the retraining effort. We apply the method to the U.S. workforce composition and show that it could substantially reduce the workers’ automation risk, while the associated retraining effort would be moderate. Governments could use the proposed method to evaluate the unemployment risk of their populations and to adjust educational policies. Robotics companies could use it as a tool to better understand market needs, and members of the public could use it to identify the easiest route to reposition themselves on the job market.

中文翻译：

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如何通过评估工作自动化风险和弹性替代方案来与机器人竞争

机器人技术和人工智能 (AI) 对就业市场的影响是社会高度关注的问题。经济学家和技术专家正在讨论以何种速度和在何种程度上可以使用技术替代人类从事职业，以及哪些行动可以减轻可能导致的失业。为此，重要的是要预测未来哪些工作可以自动化，以及工人可以做些什么来转向自动化风险较低的职业。在这里，我们通过定量评估机器人技术和人工智能能力在多大程度上可以取代这些工作所需的人类能力来计算近 1000 个现有职业的自动化风险。此外，我们介绍了一种方法，可以为任何职业找到能够最大限度地降低自动化风险同时最大限度地减少再培训工作的替代方案。我们将该方法应用于美国劳动力构成，并表明它可以大大降低工人的自动化风险，而相关的再培训工作将是适度的。政府可以使用建议的方法来评估其人口的失业风险并调整教育政策。机器人公司可以将其用作更好地了解市场需求的工具，公众可以使用它来确定在就业市场上重新定位自己的最简单途径。