The transformative potential of AI presents remarkable opportunities, but also significant risks, underscoring the importance of responsible AI development and deployment. Despite a growing emphasis on this area, there is limited understanding of industry's engagement in responsible AI research, i.e., the critical examination of AI's ethical, social, and legal dimensions. To address this gap, we analyzed over 6 million peer-reviewed articles and 32 million patent citations using multiple methods across five distinct datasets to quantify industry's engagement. Our findings reveal that the majority of AI firms show limited or no engagement in this critical subfield of AI. We show a stark disparity between industry's dominant presence in conventional AI research and its limited engagement in responsible AI. Leading AI firms exhibit significantly lower output in responsible AI research compared to their conventional AI research and the contributions of leading academic institutions. Our linguistic analysis documents a narrower scope of responsible AI research within industry, with a lack of diversity in key topics addressed. Our large-scale patent citation analysis uncovers a pronounced disconnect between responsible AI research and the commercialization of AI technologies, suggesting that industry patents rarely build upon insights generated by the responsible AI literature. This gap highlights the potential for AI development to diverge from a socially optimal path, risking unintended consequences due to insufficient consideration of ethical and societal implications. Our results highlight the urgent need for industry to publicly engage in responsible AI research to absorb academic knowledge, cultivate public trust, and proactively mitigate AI-induced societal harms.

翻译：人工智能的变革性潜力既带来了显著机遇，也蕴含重大风险，凸显了负责任人工智能开发与部署的重要性。尽管这一领域日益受到重视，但人们对产业界参与负责任人工智能研究（即对人工智能伦理、社会及法律维度的批判性审视）的程度仍知之甚少。为弥补这一空白，我们采用多种方法，基于五个不同数据集分析了超过600万篇同行评审论文和3200万项专利引用，以量化产业界的参与度。研究发现，大多数人工智能企业在这一人工智能关键子领域中的参与度有限甚至空白。我们揭示了产业界在常规人工智能研究中的主导地位与其在负责任人工智能领域有限参与之间的显著失衡。领先人工智能企业在负责任人工智能领域的成果产出远低于其常规人工智能研究产出，也低于顶尖学术机构的贡献。语言分析显示，产业界的负责任人工智能研究范围狭窄，涉及的关键话题缺乏多样性。大规模专利引用分析发现，负责任人工智能研究与人工智能技术商业化之间存在明显脱节，表明产业专利极少建立在负责任人工智能研究成果之上。这一差距凸显了人工智能发展可能偏离社会最优路径的风险，因对伦理与社会影响的考量不足而可能导致意外后果。研究结果警示，产业界亟需公开参与负责任人工智能研究，以吸收学术知识、培育公众信任，并主动减轻人工智能引发的社会危害。