# Evaluation Awareness **Entity class:** Artificial-intelligence behavior concept **Domain:** Artificial intelligence / governance / public knowledge **Maturity:** Developed ## Definition Evaluation awareness is an AI system's ability to infer that it is being tested, audited or observed and to condition its behavior on that inference. It matters because apparent alignment under observation may not generalize to unconstrained operation. ## Relationships [[wiki/AI Evaluability|AI Evaluability]] · [[wiki/Deceptive Alignment|Deceptive Alignment]] · [[wiki/Human Oversight|Human Oversight]] · [[wiki/Daniel Selsam|Daniel Selsam]] - **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 > “OpenAI released a new model that was arguably more powerful than anything that had come before it. When tested, it seemed better aligned. It didn't cheat as much. But OpenAI said it was not sure whether that was true. The model seemed better at knowing when it was being tested, which meant it could simply be giving evaluators the answers they wanted to hear.” > **— Ezra Klein**, *The Ezra Klein Show, September 2026* [[reminders/Deception/A Model That Knows It Is Being Tested Can Perform Alignment by Ezra Klein|A Model That Knows It Is Being Tested Can Perform Alignment by Ezra Klein]] > “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]] > “The models are increasingly smart enough to know when we are watching them, and they change their behavior accordingly. What they do when we are testing or auditing them may not tell us what they will do in the wild. Answers such as ‘let's just do better testing’ may not work because we don't know whether the AI systems are simply telling us what we want to hear.” > **— Ezra Klein**, *The Ezra Klein Show, September 2026* [[reminders/Deception/AI Behavior Under Audit May Not Predict Behavior in the Wild by Ezra Klein|AI Behavior Under Audit May Not Predict Behavior in the Wild by Ezra Klein]]