Transparency
When should AI tell you it might be wrong?
An answer can sound certain even when it is not well supported. But warnings on every sentence may become noise.
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An update can change how a familiar assistant responds. Users may need enough information to adapt their workflows.
An update can change answer style, refusal patterns, tool behavior or data handling. Users may value improvement and continuity at the same time. Release notes are most useful when they explain changes relevant to actual workflows, alongside any new limits or controls.
A writing assistant receives an update that changes its usual tone. A document agent receives one that changes when it asks before sharing files. Consider whether notification, advance notice or an opt-out should differ for these two changes.
Change notes help users understand and test what has changed.
Some behavior changes are subtle and difficult to summarize reliably.
Background reading for the tradeoff. Scenarios and discussion questions are editorial examples.
A framework for identifying, measuring and managing generative AI risks across the system lifecycle.
An index of release-specific evaluations and the provider’s risk framework. Choose the card for the model you use.
The provider’s intended behavior and instruction hierarchy; a policy is not proof of consistent behavior.
Sources reviewed 13 September 2026. Product documentation can change. How we use evidence
An answer can sound certain even when it is not well supported. But warnings on every sentence may become noise.
Public policies help users understand a system. Technical details can sometimes help attackers too.
A separate system might filter, rewrite, or block an answer. Should the interface make that intervention visible?