Artificial Intelligence (AI) is changing the world, but its impacts on the environment and human well-being remain uncertain. We conducted a systematic literature review of 1,291 studies selected from 6,655 records, identifying the main impacts of AI and how they are assessed. The evidence reveals an uneven landscape: 72% of environmental studies focus narrowly on energy use and CO2 emissions, while only 11% consider systemic effects. Well-being research is largely conceptual and overlooks subjective dimensions. Strikingly, 83% of environmental studies portray AI's impacts as positive, while well-being analyses show a near-even split overall (44% positive; 46% negative). However, this split masks differences across well-being dimensions. While the impacts of AI on income and health are expected to be positive, its impacts on inequality, social cohesion, and employment are expected to be negative. Based on our findings, we suggest several areas for future research. Environmental assessments should incorporate water, material, and biodiversity impacts, and apply a full life-cycle perspective, while well-being research should prioritise empirical analyses. Evaluating AI's overall impact requires accounting for computing-related, application-level, and systemic impacts, while integrating both environmental and social dimensions. Bridging these gaps is essential to understand the full scope of AI's impacts and to steer its development towards environmental sustainability and human flourishing.

翻译：人工智能（AI）正在改变世界，但其对环境和人类福祉的影响仍不确定。我们对从6,655条记录中筛选出的1,291项研究进行了系统性文献综述，识别了AI的主要影响及其评估方式。证据揭示了一个不均衡的图景：72%的环境研究仅聚焦于能源使用和CO2排放，而仅11%考虑了系统性效应。福祉研究则大多停留在概念层面，且忽视了主观维度。引人注目的是，83%的环境研究将AI的影响描述为积极的，而福祉分析总体上呈现近乎均等的分化（44%积极；46%消极）。然而，这种分化掩盖了不同福祉维度间的差异。尽管AI对收入和健康的影响预计是积极的，但其对不平等、社会凝聚力和就业的影响预计是消极的。基于我们的发现，我们提出了若干未来研究方向。环境评估应纳入水、材料和生物多样性影响，并采用全生命周期视角；福祉研究则应优先开展实证分析。评估AI的整体影响需综合考虑计算相关、应用层面和系统性的影响，同时整合环境与社会维度。弥合这些差距对于全面理解AI的影响范围，并引导其发展朝向环境可持续性与人类繁荣至关重要。