Beyond the battlefield: The ethical implications and regulatory challenges of using Autonomous AI Systems for Environmental Security and Resource Protection

As Artificial Intelligence (AI) transitions from military and industrial domains to environmental science, a fundamental shift toward data-driven methodologies is reshaping planetary protection. However, this transition frequently imports battlefield logic into conservation, utilizing autonomous systems-such as drones and machine learning algorithms-that introduce complex ethical and regulatory challenges. This paper presents a conceptual synthesis of Human-Centered AI (HCAI) frameworks and ecological security perspectives to address these risks. We identify critical friction points, including anthropocentric biases that neglect non-human wellbeing, a responsibility gap in autonomous decision-making, privacy infringements through surveillance, and the paradoxical environmental footprint of AI computing. To mitigate these risks, we propose three actionable recommendations: incorporating non-anthropocentric metrics into ethical AI standards; harmonizing transboundary regulatory frameworks to align with global standards like the EU AI Act; and mandating strictly defined human-in-the-loop protocols for all autonomous environmental interventions.