The ongoing artificial intelligence (AI) revolution has the potential to change almost every line of work. As AI capabilities continue to improve in accuracy, robustness, and reach, AI may outperform and even replace human experts across many valuable tasks. Despite enormous efforts devoted to understanding AI's impact on labor and the economy and its recent success in accelerating scientific discovery and progress, we lack a systematic understanding of how advances in AI may benefit scientific research across disciplines and fields. Here we develop a measurement framework to estimate both the direct use of AI and the potential benefit of AI in scientific research by applying natural language processing techniques to 87.6 million publications and 7.1 million patents. We find that the use of AI in research appears widespread throughout the sciences, growing especially rapidly since 2015, and papers that use AI exhibit an impact premium, more likely to be highly cited both within and outside their disciplines. While almost every discipline contains some subfields that benefit substantially from AI, analyzing 4.6 million course syllabi across various educational disciplines, we find a systematic misalignment between the education of AI and its impact on research, suggesting the supply of AI talents in scientific disciplines is not commensurate with AI research demands. Lastly, examining who benefits from AI within the scientific workforce, we find that disciplines with a higher proportion of women or black scientists tend to be associated with less benefit, suggesting that AI's growing impact on research may further exacerbate existing inequalities in science. As the connection between AI and scientific research deepens, our findings may have an increasing value, with important implications for the equity and sustainability of the research enterprise.

翻译：持续发展的人工智能革命有望改变几乎所有的职业领域。随着AI在准确性、鲁棒性和应用范围上的不断提升，它可能在众多高价值任务中超越甚至取代人类专家。尽管人们已投入大量精力研究AI对劳动力和经济的影响，以及其在加速科学发现与进步方面取得的近期成功，但我们对AI进步如何惠及不同学科领域的科学研究仍缺乏系统性认知。本文通过应用自然语言处理技术分析8760万篇论文和710万项专利，构建了一套测量框架，用以估算AI在科研中的直接使用情况及其潜在效益。研究发现，AI在科学领域的应用已相当普遍，尤其自2015年以来增长迅速；使用AI的论文呈现出影响力优势，更易在学科内外获得高被引。尽管几乎所有学科都存在从AI中受益显著的子领域，但通过分析各教育学科460万份课程大纲发现，AI教育与AI对研究的影响之间系统性错位，表明科学领域的AI人才供给与研究需求不相匹配。最后，通过考察科研队伍中不同群体受益于AI的程度，我们发现女性和黑人科学家占比更高的学科倾向于受益更少，这表明AI对研究日益增长的影响可能加剧科学领域已有的不平等。随着AI与科学研究纽带的加深，我们的发现将具有日益重要的价值，对科研事业的公平性与可持续性产生关键影响。