Our Purpose
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:
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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.
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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.
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Ensure that best practices are established from the outset with equity
and fairness – including opportunities for traditionally underserved
communities – embedded without compromise.
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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.
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Advance a set of technical measures and metrics that can be used
across a variety of use-cases in health with community consensus.
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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.
