Research Summary: The impacts of artificial intelligence on environmental sustainability and human well-being

A systematic review of 1,291 studies from a pool of 6,655 records reveals that the impacts of Artificial Intelligence (AI) on environmental sustainability and human well-being are poorly understood and fragmented in current research. While environmental studies primarily focus on AI's energy consumption and CO2 emissions, they often neglect broader systemic effects. Similarly, well-being studies are largely conceptual and fail to address subjective well-being, cognitive aspects, or upstream supply chain implications.

Why it matters

The limited and fragmented understanding of AI's environmental and human well-being impacts presents a significant strategic challenge. Without comprehensive data, organisations and governments risk developing and deploying AI technologies that could have unforeseen negative consequences, undermining long-term sustainability goals and societal health.

Key insights

• AI's impacts on environmental sustainability and human well-being are currently ill-defined in academic literature.
• The existing research provides a fragmented and uneven assessment of AI's consequences.
• Environmental studies predominantly focus on AI's energy use and CO2 emissions (72% of relevant studies).
• Systemic environmental effects of AI are rarely considered in current research (11% of relevant studies).
• Well-being studies on AI are primarily conceptual, lacking empirical depth.
• Subjective well-being, cognitive capabilities, and upstream supply-chain impacts are overlooked in well-being research related to AI.

Source

arXiv — Computers and Society — https://arxiv.org/abs/2602.24091