Trustworthy Health Evidence in the Age of Generative AI: GEO as a New Capacity for Digital Health Governance
1. World Digital Technology Academy; 2. Yealth Technology
Session 269
Generative AI is changing how people seek health information: from searching and browsing multiple ranked results to asking open-ended questions and receiving a single synthesized answer directly from AI. This fundamental shift in user behavior raises an urgent, underaddressed global health governance challenge. If trustworthy evidence, evidence-based public health guidance, and rigorously validated institutional knowledge are not well represented in AI-generated responses, unreliable, commercially motivated, or even harmful misinformation may increasingly shape public health understanding, individual clinical choices, and national policy debates.
Unlike traditional Search Engine Optimization (SEO) built for open web search rankings, Generative Engine Optimization (GEO) is a new approach tailored to how generative AI retrieves and selects information for end users. Bad actors are already exploiting this gap, using "AI poisoning" to optimize low-quality or false health content to be prioritized by AI models, while gold-standard evidence from public health agencies and evidence-based research often remains unstructured and invisible to AI crawlers.
This panel will discuss GEO not as a tool for commercial promotion, but as an emerging public interest strategy for strengthening trustworthy health information ecosystems. The session will explore how governments, international organizations, and health institutions can build new capacity to improve the visibility, accuracy, and responsible transfer of validated evidence into AI-mediated public knowledge. It will center equity, addressing how ungoverned GEO widens global health inequities for low- and middle-income countries in the Global South, and how collaborative GEO infrastructure can close this gap. Speakers will share practical, actionable insights, and discuss how GEO can support digital health transformation, public health infrastructure, evidence-based knowledge translation, and global strategies for responsible trustworthy AI in health.
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C3. Access to information and knowledge
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C4. Capacity building
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C7. ICT applications: benefits in all aspects of life — E-health
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C8. Cultural diversity and identity, linguistic diversity and local content
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C10. Ethical dimensions of the Information Society
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C11. International and regional cooperation
C3 (Access to information): It structures trusted evidence to be prioritized by AI, countering harmful misinformation and ensuring equitable access to accurate health knowledge.
·C4 (Capacity building): It builds multi-stakeholder capacity for AI-era knowledge translation, including training for public health institutions and digital health literacy for the public.
·C7 (E-health): It creates public health digital infrastructure for AI, including early warning systems for misinformation and standardized integration of evidence into AI-mediated health advice.
·C8 (Cultural and linguistic diversity): It elevates locally validated, context-appropriate health content from Global South countries, preserving local knowledge in AI responses.
·C10 (Ethical dimensions): It prioritizes public interest over commercial gain, ensuring evidence-based guidance outranks unvalidated content, and protects vulnerable populations from harmful misinformation.
·C11 (International cooperation): It is a multi-stakeholder global initiative partnering with LMICs, sharing open standards and coordinating cross-border action against AI health misinformation.
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Goal 3: Ensure healthy lives and promote well-being for all
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Goal 9: Build resilient infrastructure, promote sustainable industrialization and foster innovation
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Goal 10: Reduce inequality within and among countries
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Goal 12: Ensure sustainable consumption and production patterns
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Goal 17: Revitalize the global partnership for sustainable development
SDG 3 (Good Health and Well-being): It stops GEO-optimized harmful health misinformation from crowding out evidence-based guidance in AI responses, ensuring the public consistently accesses accurate, life-saving health information when using generative AI, directly improving public health outcomes.
·SDG 9 (Innovation and Infrastructure): It builds pioneering AI-native digital health infrastructure — including open AI-accessible evidence formats, standardized trust certification and public APIs — filling the gap of health-specific GEO standards and driving responsible innovation in digital health governance.
·SDG 10 (Reduced Inequalities): It centers equity by partnering with Global South low- and middle-income countries to build local GEO capacity, elevating their locally validated, context-appropriate health content in AI responses, countering the dominance of commercial content that widens global health gaps.
·SDG 12 (Responsible Consumption): It suppresses spread of low-quality, misleading commercial health content that drives harmful overconsumption of unproven products, empowering users to make informed, responsible health choices.
·SDG 17 (Global Partnerships): It is a multi-stakeholder global initiative that shares open standards and tools freely, bringing together governments, experts and global funders to tackle the cross-border challenge of AI health misinformation collectively.
- Objective 1: Close all digital divides and accelerate progress across the Sustainable Development Goals
- Objective 3: Foster an inclusive, open, safe and secure digital space that respects, protects and promotes human rights
- Objective 4: Advance responsible, equitable and interoperable data governance approaches
- Objective 5: Enhance international governance of artificial intelligence for the benefit of humanity