An ad hoc planning committee will organize and convene a public workshop to discuss how artificial intelligence (AI) and machine learning (ML) can be leveraged to advance environmental health research and inform decisions. The workshop will explore emerging applications and evidence on the use of AI and machine learning to improve data processing methods, predictive models, and discovery in environmental health. The workshop will also examine the implications of AI and machine learning for decision-making, considering factors that may affect confidence in decisions, such as a clearly defined scientific process and workflow, bias in available data, algorithmic transparency and interpretability, and the capability to detect false results. The workshops will include presentations and panel discussions on the use of AI and ML for important environmental health topics such as:

• Characterizing and monitoring sources of pollution
• Predicting chemical toxicity
• Identifying hazards
• Estimating human exposures
• Understanding relationships between exposures and biological effects

The presentations and discussions at the workshop will be documented in a workshop proceedings, written by a designated rapporteur in accordance with institutional guidelines.