Legal AI Risks
Legal and regulatory risks comprise in particular the unclear definition of responsibilities and accountability in case of AI failures and autonomous decisions with negative impacts (Reed, 2018; Scherer, 2016). Another great risk in this context refers to overlooking the scope of AI governance and missing out on important governance aspects, resulting in negative consequences (Gasser & Almeida, 2017; Thierer et al., 2017).
ENTITY
3 - Other
INTENT
2 - Unintentional
TIMING
3 - Other
Risk ID
mit316
Domain lineage
6. Socioeconomic and Environmental
6.5 > Governance failure
Mitigation strategy
1. Define and implement an AI Risk Management Framework (RMF) that explicitly assigns roles, responsibilities, and accountability for AI system deployment, monitoring, and failure response, ensuring clear governance structures and executive oversight. 2. Mandate a human-in-the-loop requirement for all critical, autonomous AI decisions or outputs with potentially negative impacts, coupled with professional documentation to affirm human ownership and liability for final outcomes. 3. Establish a process for continuous monitoring of evolving AI-related legal and regulatory requirements, integrating regular AI risk assessments and policy updates (such as a comprehensive AI Usage Policy) to prevent governance gaps and ensure proactive compliance across the organization.