Recognizing the promise of AI to improve patient care and support the professionals, systems, and loved ones that care for them, we came together as a diverse and interdisciplinary group to build a home for people seeking to harness these new capabilities to improve lives. AI in healthcare is still in its infancy, so collaboration among multiple stakeholders is essential to defining the values, purpose, and practices necessary to ensure that these technologies help, not harm.
Lives are at stake in healthcare. In this industry, we have a responsibility to make certain that the benefits of any innovation outweigh the risks. For every person. We believe that by working together with multiple stakeholders, including technology innovators, academic research teams, healthcare organizations, government agencies, and patients, we can help to drive the development and broad adoption of approaches that guarantee the safe and effective use of AI. We recognize that creating an ecosystem where we fully realize the promise of AI to transform patient care requires the embrace of diverse voices, needs, and expertise.
We created the Coalition for Health AI (CHAI™) to welcome a diverse array of stakeholders to listen, learn, and collaborate to drive the development, evaluation, and appropriate use of AI in healthcare. Keeping patients, including their families and communities, as the focus of attention, CHAI™ exists to:
- Engage a diverse set of stakeholders across the healthcare ecosystem to inform broadly applicable best practices for the development and deployment of AI applications in healthcare.
- Champion the responsible use of AI in healthcare, building on efforts with AI safety, reliability, transparency, and equity being pursued more broadly for AI applications.
- Ensure that best practices are established from the outset with equity and fairness – including opportunities for traditionally underserved communities – embedded without compromise.
- Spearhead the development of approaches for testing and evaluation of AI systems by promoting discovery, experimentation, and sharing of work in AI in healthcare, including methods that leverage “traditional” machine learning and more recent developments in generative AI.
- Advance a set of technical measures and metrics that can be used across a variety of use-cases in health with community consensus.
- Support health systems (both larger, e.g., academic medical centers and lower resourced health systems), health plans, medical device manufacturers, and biopharma companies with information on best practices, measures, and toolkits for the testing and evaluation of AI applications in healthcare.
