AI-specific risks

Challenges and potential harms unique to artificial intelligence technologies that extend beyond those typically addressed by conventional risk management frameworks. These include, but are not limited to, issues arising from AI system complexity and opacity ('black box' problems), heavy reliance on data quality, representativeness, and freedom from bias, dynamic learning and adaptation leading to emergent behaviors, contextual sensitivity, algorithmic bias, fairness and discrimination concerns, robustness and reliability limitations, security vulnerabilities, privacy violations, safety risks from malfunctions, and challenges in human oversight and control. Environmental impacts and broader societal and ethical concerns are also considered.