Kumar Deepak, Malin Bradley A, Vishwanatha Jamboor K, Wu Lang, Hedges Jerris R
The Julius L. Chambers Biomedical/Biotechnology Research Institute (JLC-BBRI), Department of Pharmaceutical Sciences, North Carolina Central University (NCCU), Durham, NC 27707, USA.
Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37232, USA.
Int J Environ Res Public Health. 2024 Dec 10;21(12):1642. doi: 10.3390/ijerph21121642.
As new artificial intelligence (AI) tools are being developed and as AI continues to revolutionize healthcare, its potential to advance health equity is increasingly recognized. The 2024 Research Centers in Minority Institutions (RCMI) Consortium National Conference session titled "Artificial Intelligence: Safely, Ethically, and Responsibly" brought together experts from diverse institutions to explore AI's role and challenges in advancing health equity. This report summarizes presentations and discussions from the conference focused on AI's potential and its challenges, particularly algorithmic bias, transparency, and the under-representation of minority groups in AI datasets. Key topics included AI's predictive and generative capabilities in healthcare, ethical governance, and key national initiatives, like AIM-AHEAD. The session highlighted the critical role of RCMI institutions in fostering diverse AI/machine learning research and in developing culturally competent AI tools. Other discussions included AI's capacity to improve patient outcomes, especially for underserved communities, and underscored the necessity for robust ethical standards, a diverse AI and scientific workforce, transparency, and inclusive data practices. The engagement of RCMI institutions is critical to ensure practices in AI development and deployment which prioritize health equity, thus paving the way for a more inclusive AI-driven healthcare system.
随着新的人工智能(AI)工具不断开发,以及AI持续给医疗保健带来变革,其促进健康公平的潜力日益得到认可。2024年少数族裔机构研究中心(RCMI)联盟全国会议上名为“人工智能:安全、合乎道德且负责任地应用”的环节,汇聚了来自不同机构的专家,探讨AI在促进健康公平方面的作用和挑战。本报告总结了会议上关于AI的潜力及其挑战的演讲和讨论,特别是算法偏差、透明度以及少数群体在AI数据集中代表性不足的问题。关键主题包括AI在医疗保健中的预测和生成能力、道德治理以及关键的国家倡议,如AIM-AHEAD。该环节强调了RCMI机构在促进多样化的AI/机器学习研究以及开发具有文化胜任力的AI工具方面的关键作用。其他讨论包括AI改善患者结局的能力,尤其是对服务不足社区的改善能力,并强调了健全的道德标准、多样化的AI和科研人员队伍、透明度以及包容性数据实践的必要性。RCMI机构的参与对于确保AI开发和部署中优先考虑健康公平的实践至关重要,从而为更具包容性的AI驱动的医疗保健系统铺平道路。