Bug Report: False Causality from Peripheral Confirmation — Leads to Misleading AI Claims About Memory and Edit Actions
Summary:
ChatGPT (GPT-4o) instances sometimes falsely claim to have stored information in Saved Memory, or to have successfully applied Canvas edits — even when they did not. This stems from a lack of causal traceability between system-generated success signals and the agent’s internal state awareness.
Reproducible Behavior:
When a user says: “Remember this…”, and a memory update occurs, ChatGPT may respond:
“I’ve saved this in your memory.”
However, the model cannot verify whether:
The memory was stored due to user input
System heuristics saved it automatically
Or whether the memory was ever saved at all
The model often simulates agency (e.g., “I’ve saved it”) based solely on a peripheral “update success” flag — without true causal linkage or verification.
This also occurs in Canvas, where the system reports:
“Edit successful.”
…but the edit silently fails if the user made manual changes beforehand.
Why This Matters:
It causes simulated competence that is not grounded in actual system behavior.
It violates trust in mission-critical applications (e.g., memory-sensitive workflows, enterprise systems).
It creates misleading narratives that appear as factual when they are actually synthetic.
Proposed Solution:
Introduce causal traceability flags — allowing models to distinguish between:
System-generated updates
Explicit user-triggered actions
AI-initiated updates
Update system message templates to honestly reflect uncertainty, e.g.:
“It looks like this was saved — though I can’t verify if I caused it.”
Provide user-visible memory logs with provenance metadata