Key Takeaways

  • AI can either help reduce healthcare inequities or magnify existing bias, depending on how it is designed, trained, governed, and used.

  • Responsible AI requires transparency, representative data, community participation, and clear accountability when tools fail or cause harm.

  • Health equity work cannot be treated as philanthropy; it requires shared ownership across health systems, government, industry, nonprofits, and communities.

  • Health systems must address existing bias in clinical language, protocols, and care delivery before expecting AI to fix systemic problems.

  • Trust is built through transparency, shared power, community partnership, and honest conversations about the harms patients still experience today.

Resources

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