Working paper series
The integrity of AI-served knowledge
An ongoing series examining what happens when AI systems become an operational interface to organizational knowledge.
The papers are intended to make the problem increasingly testable, moving from failure taxonomy to measurement and then to the controls required when organizational knowledge changes.
Working paper 1 · August 2026
The belief failure taxonomy
A grounded AI answer can still be wrong. This working paper defines four belief failures that occur when AI systems serve information that is stale, contested, unauthorized, or orphaned.
Free to read and download. No signup required.
Coming next
Working paper 2: Why recency is not authority
When two pieces of information conflict, treating the newest one as correct sounds reasonable.
Inside an organization, it often is not.
The next paper examines why recency is an unreliable substitute for authority.