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 systematic 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 analysis reveals notable heterogeneity between industry's substantial presence in conventional AI research and its comparatively modest 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 reveals a more concentrated scope of responsible AI research within industry, with fewer distinct key topics addressed. Our large-scale patent citation analysis uncovers limited linkage between responsible AI research and the commercialization of AI technologies, suggesting that industry patents infrequently draw upon insights from the responsible AI literature. These patterns raise important questions about the integration of responsible AI considerations into commercialization practices, with potential implications for the alignment of AI development with broader societal objectives. Our results highlight the need for industry to publicly engage in responsible AI research to absorb academic knowledge, cultivate public trust, and proactively address the societal dimensions of AI development.

翻译：人工智能的变革潜力带来了显著机遇，同时也伴随着重大风险，这凸显了负责任的人工智能开发与部署的重要性。尽管该领域日益受到重视，但业界对负责任人工智能研究（即对人工智能伦理、社会和法律维度的系统性考察）的参与程度，目前仍缺乏充分了解。为填补这一空白，我们利用五种不同数据集，通过多种方法分析了超过600万篇同行评议文章和3200万条专利引用，以量化业界的参与情况。我们的分析揭示了业界在传统人工智能研究中的显著存在与其在负责任人工智能研究中的相对有限参与之间存在明显的异质性。与它们在传统人工智能研究中的产出以及领先学术机构的贡献相比，领先的人工智能公司在负责任人工智能研究方面的产出显著偏低。我们的语言分析表明，业界内部的负责任人工智能研究范围更为集中，涉及的关键主题较少。我们的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的商业化之间联系有限，这表明行业专利很少借鉴负责任人工智能文献的见解。这些模式引发了关于将负责任人工智能考量融入商业化实践的重要问题，并可能对人工智能发展与更广泛社会目标的一致性产生影响。我们的研究结果强调，业界有必要公开参与负责任人工智能研究，以吸收学术知识、培养公众信任，并主动应对人工智能发展的社会维度。