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Artificial intelligence is rapidly becoming part of how people seek, interpret, and act on health information.
Artificial intelligence is rapidly influencing how individuals access and use health information, yet there's a lack of robust evidence to confirm its benefits in aiding comprehension and decision-making. To address this, a new framework introduces health-literate AI, outlining four core principles for its design and governance.
Health-literate AI is defined as AI systems specifically designed to match health information, guidance, and responsibilities with the user's individual abilities, situational context, and specific needs. This approach prioritizes a user's comprehension of AI output and their ability to make informed decisions and take appropriate actions, rather than just the technical correctness of the AI's response.
The framework for health-literate AI is built upon four essential principles: Comprehension, ensuring users can interpret AI-generated information in their context; Agency, empowering users with clear choices and next steps for meaningful action; Accountability, requiring transparency regarding evidence, uncertainties, and responsibilities; and Proportionality, ensuring the level of guidance and urgency aligns with the gravity of the health situation.
Experts highlight the critical need to protect individuals from potential AI harms while harnessing its health benefits. The framework encourages designers and regulators to focus on how AI systems themselves can facilitate understanding and appropriate action, rather than solely relying on users to adapt. It also stresses the necessity for further research to quantitatively assess if AI truly enhances comprehension, informed decision-making, and health-related behaviors.