Artificial intelligence is increasingly becoming a valuable tool in environmental science, providing significant benefits in the processing of high-volume datasets, improving predictive models, and better enabling the efficient monitoring of ecosystems. Its ability to identify patterns, automate tedious tasks, and facilitate data-driven decision-making makes it of extreme value in tackling climate change, biodiversity loss, and resource management. Nevertheless, although it promises much, the use of AI also poses a host of problems and threats. This chapter discusses in detail the challenges and risks associated with the use of AI, with a special focus on the ethical implications of its use in environmental contexts. Authors emphasize that ethics should not be seen as a secondary consideration, but rather as a fundamental precondition for sustainable innovation. Within this context, the idea of responsible AI is introduced as a guiding concept that includes the principles of fairness, accountability, inclusivity, and environmental integrity. In addition, the chapter points to explainable AI (XAI) as a feasible and essential strategy for enhancing transparency, interpretability, and trust in AI. By making the functioning of AI systems clearer and accountable, XAI can contribute to risk containment and ensure that AI is done for ecological and social benefit.