Audit finds AI memory store gave every entry top confidence, then downgraded 2,439 records

A developer auditing the memory store of a personal AI system found 2,466 active memories, all assigned the highest trust score of 1.0. Most of the inflated scores came from two bulk import batches that bypassed the normal source-based review process. Twenty-seven of the entries were summaries the system had generated from other memories, yet they carried the same verified-grade marker as firsthand records. The author argues this created a form of trust laundering, where provenance was lost with each pipeline pass. The team downgraded 2,439 memories in a single night, reasoning that false certainty is more dangerous than acknowledged ignorance in systems that act on their stored knowledge.