AI and Climate Justice: Ethical Risks of Predictive Models in Environmental Policies

The increasing implementation of predictive artificial intelligence (AI) models in environmental policies poses critical challenges for climate justice, particularly concerning equity and the rights of vulnerable communities. This article analyzes the ethical risks associated with the use of AI in environmental decision-making by examining how these systems can perpetuate existing inequalities or generate new forms of exclusion. Through a systematic literature review of articles in Spanish and English indexed in Scopus between 2018 and 2022, four central thematic axes were identified: algorithmic biases and territorial discrimination, opacity in climate governance, displacement of political responsibilities, and exclusion of local knowledge in predictive models. The results reveal that, although AI can optimize the management of natural resources and mitigate climate change, its application without ethical regulation tends to favor actors with greater technological and economic power, marginalizing populations historically affected by the environmental crisis. It is concluded that it is necessary to develop governance frameworks that prioritize algorithmic transparency, community participation, and accountability to ensure that AI-based solutions do not deepen existing climate injustices.