The Potential of AI and ChatGPT in Improving Agricultural Injury and Illness Surveillance Programming and Dissemination

ABSTRACT

Generative Artificial Intelligence (AI) provides unprecedented opportunities to improve injury surveillance systems in many ways, including the curation and publication of information related to agricultural injuries and illnesses. This editorial explores the feasibility and implication of ChatGPT integration in an international sentinel agricultural injury surveillance system, AgInjuryNews, highlighting that AI integration may enhance workflows by reducing human and financial resources and increasing outputs. In the coming years, text intensive natural language reports in AgInjuryNews and similar systems could be a rich source for data for ChatGPT or other more customized and fine-tuned LLMs. By harnessing the capabilities of AI and NLP, teams could potentially streamline the process of data analysis, report generation, and public dissemination, ultimately contributing to improved agricultural injury prevention efforts, well beyond any manually driven efforts.

KEYWORDS:

• Agricultural injury
• artificial intelligence
• ChatGPT
• surveillance

Disclosure statement

The authors have no personal or financial conflicts of interest to disclose.

Contributions

All authors contributed to the conception or design of the work and writing of the manuscript.

Institution and ethics approval and informed consent

No human subjects were involved in this project.

Additional information

Funding

Funding support was provided through the National Farm Medicine Center, Marshfield Clinic Research Institute, and National Children’s Center for Rural and Agricultural Health and Safety through the National Institute for Occupational Safety and Health Cooperative Agreement U54 OH009568.