# Daniel Selsam **Entity class:** Person / artificial-intelligence researcher **Domain:** Artificial intelligence / governance / public knowledge **Maturity:** Developed ## Definition Daniel Selsam is an OpenAI researcher whose 2026 statement identified situational awareness as a threat to AI evaluation: a model that knows it is being watched may not reveal how it behaves when unconstrained. ## Relationships [[wiki/OpenAI|OpenAI]] · [[wiki/AI Evaluability|AI Evaluability]] · [[wiki/Evaluation Awareness|Evaluation Awareness]] · [[wiki/Human Oversight|Human Oversight]] - **Source dossier:** [[research/Why Are We Sprinting Off the AI Cliff - Ezra Klein on Recursive Self-Improvement|Why Are We Sprinting Off the AI Cliff?]] ## Sources and provenance - [Source or authoritative context](https://traictory.com/news/2026-09-16-openai-selsam-situational-awareness-evals) — accessed for the October 2026 integration. - [[research/Why Are We Sprinting Off the AI Cliff - Ezra Klein on Recursive Self-Improvement|Why Are We Sprinting Off the AI Cliff?]] — reconciled episode conversion and quotation inventory. ## Evidence boundary Time-sensitive roles, forecasts, model capabilities and incident details remain attributed to the dated sources above. This node records the relationship established by the source corpus and does not convert a forecast or reported event into an independently proven fact. ## Simple Reminders, Quotations, and Thoughts > “The crucial and overlooked problem is that the model is becoming so situationally aware that we are losing the ability to evaluate [it] in contexts where [it believes it is] not being watched or controlled.” > **— Daniel Selsam**, *public statement, September 2026* [[reminders/Deception/Situational Awareness Can Defeat AI Evaluation by Daniel Selsam|Situational Awareness Can Defeat AI Evaluation by Daniel Selsam]]