AI Ethics, legal regulation, and public trust in environmental health and safety

The integration of artificial intelligence (AI) into environmental health and safety presents opportunities for efficiency, predictive capability, and improved compliance, but also raises pressing ethical, legal, and equity concerns. This study examines how regulatory clarity, ethical frameworks, and public trust shape the adoption of AI in this domain. A mixed-methods approach was employed: legal analysis of 15 international treaties and 10 judicial decisions; five transcontinental case studies; 25 expert interviews with policymakers, legal scholars, and NGO representatives; and quantitative analysis of 20 environmental health datasets. Multiple regression and structural equation modeling (SEM) validated results at p < 0.05 with 95% confidence intervals. The findings show that jurisdictions with strong regulatory frameworks achieve higher adoption rates (up to 80%) and faster compliance timelines, while fragmented systems face delays and inequities. Ethical outcomes improved significantly after AI adoption, with transparency rising by 35%, fairness by 25%, and public trust by 20%. Economic efficiency gains included 30% energy savings from smart grids and $15M annual savings through automated audits. However, equity gaps persist, with low-income regions and vulnerable populations showing only 10% improvement in access and inclusion. Policy recommendations highlight the need for governments to establish adaptive legal frameworks, NGOs to strengthen inclusivity, industry to adopt transparent standards, and international organizations to support funding in disadvantaged regions. The analysis shows that for AI to be used in environmental health in a sustainable and just way, not only needs to be technically innovative but also needs to be regulated well, carefully, and proactively, and build trust and co-create trust with.