Preliminary exploration of ChatGPT-4 shows the potential of generative artificial intelligence for culturally tailored, multilingual antimicrobial resistance awareness messaging.

Objective: Antimicrobial resistance (AMR), a global threat driven by factors such as improper antimicrobial use in humans and animals, is projected to cause 10 million annual deaths by 2050. For behavior change, public health messages must be tailored for diverse audiences. Generative AI may have the potential to create culturally and linguistically suited AMR awareness messages. This study assesses ChatGPT-4's capability for crafting such content.

Methods: 4 veterinary public health professionals from diverse linguistic and cultural backgrounds identified top AMR contributors and audiences in their countries. A fifth person developed and refined ChatGPT-4 prompts to create AMR awareness content in US English, Ukrainian, Luganda, Ugandan English, Yoruba, and Nigerian Pidgin, using behavior change models. The content was rated for accuracy, applicability, language, cultural fit, originality, clarity, persuasiveness, and overall quality.

Results: ChatGPT-4 created 2 content types (long and short) per language for social media, television ads, and WhatsApp. Quality ranged from poor to excellent. Shorter content outperformed longer ones. Performance varied across languages, with abysmal results for Yoruba and excellent for Pidgin. Problematic issues like simplistic language and inappropriate terminology were identified.

Conclusions: ChatGPT-4 has the potential to generate content and training aids. However, the varied quality requires professional verification. Future research should optimize prompts and incorporate expert and audience insights for better results. These preliminary findings should be interpreted cautiously due to the small sample size and subjectivity.

Clinical Relevance: ChatGPT-4 can quickly create tailored content for global AMR awareness. More research is needed to explore generative AI for One Health messaging.