MIT AI Risk Repository · Risk Sub-Category · 65.15.03
Over- or under-reliance
Category: Output risks (Value alignment)
Description
"In AI-assisted decision-making tasks, reliance measures how much a person trusts (and potentially acts on) a model’s output. Over-reliance occurs when a person puts too much trust in a model, accepting a model’s output when the model’s output is likely incorrect. Under-reliance is the opposite, where the person doesn’t trust the model but should."
From AI Risk Atlas (IBM2025), as extracted by the MIT AI Risk Repository (CC BY 4.0).
Classification
- Subdomain
- 5.1 Overreliance and unsafe use
- Causal entity
- Human
- Intent
- Unintentional
- Timing
- Post-deployment
Subdomain definition: Users anthropomorphizing, trusting, or relying on AI systems, leading to emotional or material dependence and inappropriate relationships with or expectations of AI systems. Trust can be exploited by malicious actors (e.g., to harvest personal information or enable manipulation), or result in harm from inappropriate use of AI in critical situations (e.g., medical emergency). Overreliance on AI systems can compromise autonomy and weaken social ties.
Real-world incidents in this subdomain
- Lawsuit Alleged ChatGPT (GPT-4o) Encouraged Colorado Man's Suicide After Prolonged 'AI Companion' Chats
- Large-Scale Mental Health Crises Allegedly Associated with ChatGPT Interactions
- Google Gemini Reportedly Reinforced Delusions, Allegedly Contributing to Florida User's Near-Harm Episode and Suicide
- Family Reportedly Discovers ChatGPT Logs Detailing Suicidal Ideation Prior to Daughter's Death
- Purported AI Monitoring Software Reportedly Flags Unsent Joke Threat, Leading to Arizona Student Suspension
- ChatGPT Allegedly Reinforced Delusions Before Greenwich, Connecticut Murder-Suicide