Going vegan with ChatGPT: Towards designing LLMs for personalized lifestyle changes - Munachiso Okenyi; Grace Ataguba; Kosi Clinton Henry; Sussan Anukem; Rita Orji (Machine Learning with Applications)
Large language models (LLMs), one of the recent technological revolutions, have become applicable to all areas of human endeavor, including health. In the area of health, LLMs have contributed to disease management, diagnosis, stress management, and other major lifestyle-related changes. However, little is yet known about their impact in the area of nutrition and lifestyle-related changes associated with diseases such as diabetes, cardiovascular diseases, obesity, and others. In this paper, we present two case studies of ChatGPT as an LLM intervention for making lifestyle-related decisions, such as transitioning to a vegan lifestyle: 1. normal weight (healthy) and 2. obesity. Additionally, we considered three (3) dietary restrictions that could affect people in both case studies to transition to a vegan lifestyle. These include 1) allergies to nuts; 2) allergies to gluten; and 3) no allergies. We used ChatGPT to generate a one-week (seven-day) meal plan based on these dietary restrictions. We analyzed all responses from ChatGPT and found that ChatGPT provides a rich combination of vegan diets and is sensitive to these food allergies to some extent. Additionally, we found some challenges that relate to how an appropriate prompt can be employed to optimize ChatGPT’s recommendations and precisions relating to the total calories of foods recommended by ChatGPT. Furthermore, we provide recommendations to overcome these challenges in future work, including supporting user's domain-specific literacy and precision sensitivity for metrics that have an overall impact on human health.