health care and ai Executive summary
In 2024, the Brookings Center for Technology Innovation launched The AI Equity Lab (“The Lab”) to explore interdisciplinary and cross-sector approaches for responsible, ethical, and inclusive design of autonomous models in consequential issue areas, including health care, journalism, education, criminal justice, and financial services. To advance the goals of The Lab, interdisciplinary and cross-sector working groups were established and convened by the health care, education, and journalism sector to develop purposeful and pragmatic solutions to enhance the access and adoption to artificial intelligence (AI), while considering the potential harms of discrimination and modeling errors. 1 The Health and AI Working Group (“Working Group”) of The AI Equity Lab was comprised of 14 interdisciplinary and cross-sector health experts who were tasked with exploring key themes related to AI’s application in health and providing recommendations to ensure it is designed and deployed inclusively for underrepresented and medically vulnerable communities. Over the course of four online convenings, the Working Group focused on four key areas: AI opportunities and barriers related to underrepresented communities.
Existing legislative and regulatory policies to protect patients from harmful and unethical uses of AI.
Pragmatic programs and public policies to advance more inclusive AI models.
Other pioneering actions and best practices to ensure responsible and ethical use of AI in health care.
The composition of the participating experts included technologists, health practitioners, primary and secondary care professionals, patient advocates, and industry leaders, who will be referred to as Working Group Experts (WGEs) throughout the paper (see Appendix One for the list of participants). Upon completion of the four sessions, the WGEs identified strategies for framing how practitioners and technologists should engage with AI in health care and offered recommendations on ways the sector can meaningfully advance the design and distribution of more inclusive technologies. In particular, the group proposed that policymakers and key stakeholders consider the following strategies: Prioritize the accessibility of required infrastructure to implement various use cases of AI in health care and measure the opportunities and risks of adoption in more detail.
Accelerate AI literacy and awareness among patients, […]
Health and AI: Advancing responsible and ethical AI for all communities
