Definition
Human oversight is the set of design and operational measures that keep humans in control of an AI system. It includes monitoring, review workflows, escalation paths, and the ability to override, pause, or shut down the system when needed.
Why it matters
- Safety: oversight catches failures before they cause harm.
- Professional standards: advice and decisions often require human judgment.
- Compliance: some regulatory regimes require effective oversight for certain systems.
How it works
Design controls + user training + monitoring + intervention -> oversightOversight is “meaningful” when humans have time, information, and authority to act — not when they rubber-stamp outputs.
Practical example
An AI assistant drafts research summaries, but a professional must review sources and conclusions before the output is sent to a client, with clear guidance on what to check.
Common questions
Q: Is a disclaimer enough?
A: No. Oversight is a control system: monitoring, workflows, and intervention capabilities.
Q: Does oversight mean humans must read everything?
A: Not always. Risk-based oversight can use sampling, triggers, and escalation for high-impact outputs.
Related terms
- EU AI Act — oversight obligations in some contexts
- High-Risk AI System — where controls become mandatory
- AI Risk Management — oversight as a mitigation
- Model Accountability — ownership and approvals
- Algorithmic Transparency — information needed for oversight
References
Regulation (EU) 2024/1689 (EU AI Act).