As AI enters health care, are we ready?

by Ariana Costakes, CUNY Graduate School of Public Health and Health Policy

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Artificial intelligence is rapidly becoming part of how people seek, interpret and act on health information. Yet the technology is advancing faster than the evidence needed to determine whether these systems actually help people understand what matters, make informed health decisions and know what to do next.

A new perspective published in the journal Nature Human Behaviour and led by University of Alabama professor Rebecca K. Ivic, with CUNY SPH distinguished lecturer Scott C. Ratzan and Emory University School of Medicine professor emerita Ruth M. Parker, introduces the concept of health-literate artificial intelligence and proposes four principles for designing and governing AI-mediated health communication: comprehension, agency, accountability and proportionality.

"We are deploying AI into health contexts faster than we are building the evidence needed to know whether it actually helps people understand, decide and act," Ivic says.

As AI systems are used to answer questions about symptoms, summarize health guidance, interpret risk and support decisions, they may provide technically plausible responses while failing to communicate how urgent a situation is, how certain the information is, what alternatives exist, when professional care is needed and when to seek human judgment and dialogue for appropriate decision-making.

The authors define health-literate AI as AI designed to align information, guidance and responsibility with users' abilities, contexts and needs. The framework shifts attention beyond whether AI produces information that is technically accurate or explainable to whether people can understand what that information means, make informed decisions and determine what to do next.

The four components are:

• Comprehension: Can people interpret AI output in relation to their language, prior knowledge, and circumstances?
• Agency: Does the information support meaningful and informed action, including clear choices and next steps?
• Accountability: Are evidence, uncertainty, limitations, and responsibility visible?
• Proportionality: Does the amount and urgency of guidance match the stakes of the situation?

Together, these components provide a basis for considering whether AI-mediated communication is fit for purpose in health-relevant settings.

"Given all the discussion and warnings about the potential harms of AI, we need expert thinking, research and analysis that protects people from potential harms while realizing the promise of this new technology for health," Ratzan says.

"Is AI in health care the holy grail or the tower of Babel?" Parker asks. "In medicine, there are immediate questions: Can all people understand and safely use what these systems tell them in order to improve health outcomes? Is its use cost-effective and also aligned with our human values?"

The framework builds on decades of health literacy research that has increasingly examined not only individuals' skills but also how governments, organizations and systems make health information easier or harder to understand and use. For more than 30 years, Parker and Ratzan have contributed substantially to this body of work, including research on health literacy as a systems and policy concern. Ivic proposes a novel model for today's digital information environment, examining how platforms, institutions and emerging technologies shape the production, interpretation and use of health information.

Rather than placing the burden entirely on individuals to interpret increasingly complex automated information, health-literate AI asks how the design and governance of AI systems themselves can support understanding and informed action. The authors also challenge designers to envision how AI could help operationalize affordability of health care, a long-standing, well-acknowledged goal that we have not achieved.

"This model gives researchers, developers and regulators a shared way to address a more consequential question," Ivic says. "The question is not simply whether AI can generate an answer, but whether people can understand it, use it and act on it appropriately. Health-literate AI should do more of the work of making quality health information understandable, actionable and accountable, with design and governance working together to advance responsible AI in health."

The authors argue that this is particularly important in high-stakes or ambiguous situations. AI systems should distinguish among informing, advising and deciding and make those roles clear to users. When automated output is insufficient, systems should also identify when human judgment, clinical evaluation or ethical deliberation is needed.

"The goal is not to make people better at navigating increasingly complex AI," Ivic says. "It is to give the field a way to begin measuring whether that is actually happening."

The perspective argues that health literacy should not simply require people to adapt to increasingly complex technologies. As AI becomes an increasingly important intermediary between people and health information, the systems themselves should be designed around the people who must understand and use them.

The authors call for adoption of the principles of health-literate AI to inform design, evaluation, research and governance across health-relevant AI ecosystems. They also point to an important evidence gap: More research is needed to determine whether AI actually improves comprehension, informed decision-making and health-related action.

"AI in health care no doubt offers opportunities for innovation, but more research, guardrails and regulation are needed to ensure its benefits clearly outweigh its risks," Parker says. "Its design and use need to enhance users' abilities to understand and make decisions that improve health, are affordable and are consistently aligned with our human values."

Publication details

Rebecca K. Ivic et al, Building health-literate artificial intelligence, Nature Human Behaviour (2026). DOI: 10.1038/s41562-026-02595-1

Journal information: Journal of Health Communication , Nature Human Behaviour

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