Governance, Ethics, and Legal Challenges of AI Adoption in Animal Environmental Monitoring

Abstract

Artificial Intelligence (AI) is increasingly being adopted in animal environmental monitoring to support continuous observation, predictive assessment, animal welfare management, and sustainable livestock production. The integration of AI with Internet of Things (IoT) sensors, wearable devices, computer vision, and environmental monitoring platforms enables the analysis of complex relationships between environmental conditions, animal behaviour, health, and welfare. However, increasing dependence on AI introduces significant governance, ethical, and legal challenges that must be addressed for responsible and trustworthy adoption. This study examines key concerns associated with AI-enabled animal environmental monitoring, including data governance, ownership, privacy, cybersecurity, algorithmic transparency, explainability, bias, fairness, accountability, human oversight, animal welfare, legal liability, and regulatory compliance. It further presents a responsible AI adoption framework integrating data governance, model validation, ethical and risk assessment, stakeholder accountability, human supervision, continuous monitoring, and auditability throughout the AI lifecycle. The study emphasizes that predictive accuracy alone is insufficient for determining the suitability of AI systems, particularly when automated recommendations influence animal health, welfare, and environmental management decisions. Responsible adoption requires balancing technological innovation with ethical safeguards, regulatory requirements, transparent decision-making, and professional judgement. The proposed perspective supports the development of trustworthy, accountable, and sustainable AI-enabled animal environmental monitoring systems.