Can AI in Health Care Be Truly Inclusive? - Summary - DentalSpire

Can AI in Health Care Be Truly Inclusive?

  • By

  • Beth Rush

  • June 22, 2026

  • 0 min

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Objective:

To explore how AI systems in healthcare can be designed to avoid perpetuating existing health and social inequities.

Approach:
    Key Findings:
    • AI in healthcare risks reproducing existing disparities unless equity, diversity, and inclusion are integrated throughout the AI life cycle.
    • The EDAI framework provides actionable guidance at micro, meso, and macro levels for integrating equity, diversity, and inclusion in health care.
    • Populations facing barriers to care are often underrepresented in datasets used to train AI systems, leading to 'invisible populations'.
    • Incorporating equity-related factors can improve AI model performance, but these considerations are rarely prioritized.
    Interpretation:

    The underprioritization of equity in AI development is often treated as optional rather than essential for safe AI development.

    Limitations:
    • Existing AI systems may not adequately address social determinants of health.
    • Implementation challenges include workforce readiness and inconsistent access to AI tools.
    Conclusion:

    The path forward for existing AI systems requires intentional strategies to ensure equitable health care delivery.

Original Source(s)

Can AI in Health Care Be Truly Inclusive?

  • by Beth Rush

  • June 22, 2026

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