Background: Since the middle of the twentieth century, Artificial Intelligence (AI) technologies have evolved rapidly, with Generative Artificial Intelligence (GenAI) moving the field forward in 2022. As part of a broader digital revolution, GenAI tools have become integrated into everyday life. More than two decades ago, AI was predicted to be a useful decision tool alongside human judgement within complex or unstructured settings. At this current time, AI is even more impactful with the ability to reshape decision making. Nutrition-related decision making occurs frequently within people’s everyday life, where they make approximately 200 food decisions per day. Increasingly, GenAI is used to assist individuals in accessing and interpreting nutrition information. Increasingly, GenAI is used to assist individuals in accessing and interpreting nutrition information. Further, some studies have shown how GenAI systems can support individual adherence and engagement with nutrition interventions, enhancing autonomy. As the public is becoming increasingly dependent on AI-supported decision-making tools, experts argue that aspects of transparency and accountability should also be strengthened. Current literature highlights, the need for stronger governance, regulatory standards and evidenced based guidelines, to support responsible use and minimise public risk. Aim: To examine the role of GenAI in public health nutrition information seeking and decision making and identify how literacy levels influence interpretation and application of GenAI generated output and explore opportunities for governance frameworks and guidance to support safe, ethical and equitable use. Methods: A multiphase mixed-methods study in sequential stages. Phase 1: Scoping review to map existing literature and identify knowledge gaps. Phase 2: Quantitative and qualitative surveys to examine patterns of GenAI use, trust and distrust, information evaluation and literacy levels. Participants will be presented with nutrition information case scenarios to assess their ability to identify misinformation, evaluate information credibility and distinguish between human generated and AI generated content. Phase 3: Qualitative interviews to gain a deeper understanding on how individuals engage with, interpret, evaluate and trust GenAI for nutrition decision making. Phase 4: Co-design workshops to inform the development of recommendations and governance frameworks that support the safe, ethical and equitable use. Expected contribution: To support the development of evidence informed public health guidance, governance frameworks and literacy focused strategies, supporting safe, ethical and equitable use of GenAI for nutrition related decision making.
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