This study examines the role of artificial intelligence (AI) technologies in the detection and prevention of environmental crimes, along with the legal and ethical challenges they entail. The growing global dimension and multi-actor structure of environmental crimes necessitate the integration of technological tools into enforcement activities. AI, particularly through its subfields such as big data analytics, image processing, and machine learning, contributes to the early detection of crimes like illegal logging, waste dumping, and poaching. Supported by data from satellites, drones, and IoT sensors, digital systems enable faster and more effective monitoring of environmental violations. However, the use of these technologies also raises significant legal debates. Key concerns include whether digital data obtained through AI-supported systems can be considered admissible evidence, who bears legal responsibility—humans, states, or software—and how to ensure the protection of personal data. Most national and international legal frameworks lack sufficient regulations (Nuredin, 2016) regarding these new technologies. Although initiatives such as the EU Artificial Intelligence Act offer certain provisions, there is still an absence of comprehensive legislation specifically targeting environmental crimes. The study further emphasizes the intersection between environmental justice and AI ethics, advocating for the incorporation of principles such as transparency, accountability, and nondiscrimination in the design and implementation of AI systems. The integration of AI into environmental law should not be seen as a purely technical transition, but rather as a normative transformation requiring reinterpretation of legal theory. In this context, there is a pressing need for a digital environmental governance model aligned with sustainability goals, human rights, and democratic legitimacy.
Chris Beaumont (Thu,) studied this question.