Adverse Environmental and Public Health Effects of Artificial Intelligence: A Comprehensive Review

The rapid global expansion of artificial intelligence (AI), particularly generative models, drives energy-intensive data centers with substantial environmental and public health costs. The present review synthesizes evidence confirming contributions of AI to greenhouse gas emissions, freshwater depletion, e-waste, and air pollution from fossil-powered grids. Public health risks include algorithmic bias exacerbating disparities, AI-generated misinformation/deepfakes eroding trust, privacy loss, mental health harms, and job displacement impacting social determinants. These burdens disproportionately affect marginalized communities via environmental justice failures and biased algorithms. Mitigation demands life-cycle assessments, renewable energy mandates, circular hardware economies, bias audits, and policies prioritizing health equity. Sustainable AI requires coordinated action across stakeholders.