Limited human oversight in decisions

Mitigation strategy

1. Establish Structured Human-in-the-Loop (HITL) Systems Design and implement HITL architectures that strategically embed human judgment into the automation flow, not merely as an exception process. This requires defining clear *decision tiers* (e.g., straight-through processing, quick human verification, expert review) with explicit thresholds and routing logic based on the AI's confidence score, rule-based risk evaluation, or potential business/ethical impact, thereby ensuring proportionate human oversight for high-stakes decisions. 2. Implement Explainable AI (XAI) for Transparency and Accountability Integrate XAI techniques to transform opaque automation into a controllable system. This includes utilizing model interpretability methods to provide human overseers with a clear, concise rationale for AI-generated decisions. Simultaneously, enforce a durable *audit trail* that records all model inputs, intermediate human steps, and final outcomes to establish clear traceability and accountability for interventions and decisions, satisfying both compliance and quality assurance needs. 3. Ensure Human Competence and Veto Authority Mandate that natural persons assigned to oversight are *competent*, possessing the requisite training to understand the AI system's capabilities, limitations, and potential for automation bias. Crucially, the system design must provide simple, effective *human-machine interface tools* that grant the final human operator explicit and real-time authority to disregard, override, or interrupt the AI's output (e.g., a 'stop' function) to prevent or minimize risks to fundamental rights or safety.