标题： 破坏性人工智能创新对美国职业的影响 显示英文标题

标题： The Potential Impact of Disruptive AI Innovations on U.S. Occupations

摘要： 人工智能的迅速崛起即将颠覆劳动力市场。 然而，人工智能并非一个整体；其影响取决于创新的性质以及它所影响的工作。 虽然计算方法正在出现，但目前尚无共识如何系统地衡量一项创新的颠覆潜力。 在这里，我们计算了3,237项美国人工智能专利（2015-2022年）的颠覆指数，并将其与工作任务联系起来，以区分“整合性”人工智能创新，这些创新强化现有结构，以及“颠覆性”人工智能创新，这些创新会改变现有结构。 我们的分析显示，整合性人工智能主要针对体力、常规和单独的任务，这些任务在中西部和中部地区的制造业和建筑业中很常见。 相比之下，颠覆性人工智能影响的是不可预测和脑力任务，尤其是在沿海的科技行业。 令人惊讶的是，我们还发现颠覆性人工智能 disproportionately 影响那些已经面临熟练劳动力短缺的地区，这表明颠覆性人工智能技术可能在工人稀缺的地方加速变化，而不是取代过剩的劳动力。 最终，整合性人工智能似乎延续了当前的自动化趋势，而颠覆性人工智能将改变复杂的脑力工作，协作任务是一个明显的例外。 显示英文摘要

摘要： The rapid rise of AI is poised to disrupt the labor market. However, AI is not a monolith; its impact depends on both the nature of the innovation and the jobs it affects. While computational approaches are emerging, there is no consensus on how to systematically measure an innovation's disruptive potential. Here, we calculate the disruption index of 3,237 U.S. AI patents (2015-2022) and link them to job tasks to distinguish between "consolidating" AI innovations that reinforce existing structures and "disruptive" AI innovations that alter them. Our analysis reveals that consolidating AI primarily targets physical, routine, and solo tasks, common in manufacturing and construction in the Midwest and central states. By contrast, disruptive AI affects unpredictable and mental tasks, particularly in coastal science and technology sectors. Surprisingly, we also find that disruptive AI disproportionately affects areas already facing skilled labor shortages, suggesting disruptive AI technologies may accelerate change where workers are scarce rather than replacing a surplus. Ultimately, consolidating AI appears to extend current automation trends, while disruptive AI is set to transform complex mental work, with a notable exception for collaborative tasks.