Experts argue AI trust requires auditable traceability, not just declarations

An article published on DEV Community contends that trust in AI systems is meaningless without verifiable records such as decision logs, data provenance and inference parameters. It argues that without technical traceability, compliance and accountability cannot be validated and trust remains merely declarative. The piece cites Brazilian rules, including LGPD article 38, the proposed AI legal framework PL 2338/2023, and the ISO/IEC 23894 and 42001 standards, to support its position. It also claims that systems with integrated traceability cut incident investigation time substantially, though several of its statistics are unverified. The author further notes that traceability does not remove algorithmic bias but makes it detectable and correctable.