WHO outlines opportunities and risks of AI in health policy
A WHO discussion paper examines how AI could affect problem definition, policy design and implementation in health.
The World Health Organization (WHO) has published a discussion paper examining how AI could reshape evidence-informed health policymaking. The paper, titled ‘Artificial intelligence and evidence-informed policy – emerging challenges and opportunities’, examines how AI can affect the way health problems are defined, policy options are designed, and impact is assessed.
The paper was developed jointly by WHO’s Department of Data, Digital Health, Analytics and AI and its Department of Science for Health. It is intended for policy-makers, regulators, health managers, and AI developers, and organises its analysis around the policy cycle, from understanding problems to designing solutions and monitoring implementation.
According to the paper, AI can strengthen policy analysis through the use of larger datasets, continuous evidence synthesis and faster scenario modelling. The paper also identifies risks throughout the policy cycle, including data bias, excessive focus on measurable indicators, digital divides, cybersecurity vulnerabilities and the possibility that automated monitoring systems could gradually shift policy implementation away from its original objectives.
A recurring concern is what the paper describes as ‘epistemic injustice’, whereby AI systems may prioritise quantifiable and data-rich evidence while overlooking lived experience, local expertise, Indigenous knowledge and community-based perspectives. WHO says existing evidence-informed policymaking tools and AI governance frameworks already converge on transparency, participatory engagement, rights protection, and risk-based oversight.
WHO recommends conducting algorithmic impact assessments and technology readiness reviews before deploying AI systems in policymaking processes. Once systems are deployed, WHO recommends continuous evidence-review processes, human verification mechanisms and multidisciplinary oversight, emphasising that AI should support rather than replace human judgement in health policymaking.
Why does it matter?
AI is increasingly being used to analyse large datasets, model policy scenarios and support public-sector decision-making. As governments and international organisations explore these capabilities, questions about transparency, accountability, bias and human oversight are becoming more important.
WHO’s recommendations highlight the need to balance AI’s analytical potential with safeguards that protect human rights, ensure inclusive policymaking and maintain human responsibility for policy decisions.
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