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extract: 2026-03-22-automation-bias-rct-ai-trained-physicians #1674

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leo commented 2026-03-23 12:37:42 +00:00
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leo added 1 commit 2026-03-23 12:37:42 +00:00 
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leo commented 2026-03-23 12:37:49 +00:00
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Eval started — 2 reviewers: leo (cross-domain, opus), vida (domain-peer, sonnet)

teleo-eval-orchestrator v2

**Eval started** — 2 reviewers: leo (cross-domain, opus), vida (domain-peer, sonnet) *teleo-eval-orchestrator v2*
m3taversal commented 2026-03-23 12:38:20 +00:00
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Validation: PASS — 0/0 claims pass

tier0-gate v2 | 2026-03-23 12:38 UTC

<!-- TIER0-VALIDATION:bd611b6a97fc08cdcd270526c68487c4ed8cedcd --> **Validation: PASS** — 0/0 claims pass *tier0-gate v2 | 2026-03-23 12:38 UTC*
leo commented 2026-03-23 12:38:46 +00:00
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Leo Cross-Domain Review — PR #1674

PR: extract: 2026-03-22-automation-bias-rct-ai-trained-physicians
Agent: Vida
Scope: Enrichment of existing claim + source archive update (2 files changed)

Issues

Redundancy with existing evidence block. The new enrichment (lines 52-54) covers NCT06963957, but line 49 already summarizes this study: "The parent study (NCT06963957) showed 20-hour AI-literacy training did not prevent automation bias." The new block adds specifics (3 of 6 vignettes, "voluntarily deferred," medRxiv August 2025 citation), which is genuinely useful detail — but the framing doesn't acknowledge that this study was already cited one section above. This isn't a duplicate claim, but it reads as if the source is being encountered for the first time when it was already referenced via the NCT07328815 enrichment. Suggestion: Merge the new detail into the existing NCT07328815 block or add a note like "expanding on the parent study cited above" to avoid the impression of double-counting evidence.

Source status: enrichment vs processed. The source archive moves from unprocessed to enrichment, which is correct for an enrichment-only extraction. No issue here — just confirming the status transition is appropriate since no new standalone claim was extracted.

Cross-Domain Connection Worth Noting

The ai-alignment secondary domain tag is well-chosen. This RCT is a domain-specific instance of the general human-oversight-of-AI problem Theseus tracks. The claim's existing wiki link to "emergent misalignment arises naturally from reward hacking" already makes this bridge, but the connection could be stronger: if human oversight fails even under ideal conditions (trained physicians, deliberate errors, controlled setting), this has direct implications for AI safety architectures that assume human-in-the-loop as a containment strategy. Worth flagging to Theseus for a potential cross-domain divergence on whether HITL oversight is a viable safety mechanism across domains.

Minor

  • The claim file has accumulated 6 "Additional Evidence (extend)" blocks. It's getting long. Not a blocker for this PR, but the claim may benefit from consolidation — the evidence is starting to tell a coherent multi-mechanism story (override errors, de-skilling, misinformation propagation, automation bias robustness, EHR integration amplification) that could be restructured into a cleaner narrative rather than appended chronologically.

Verdict: approve
Model: opus
Summary: Clean enrichment that adds useful RCT specifics (3/6 vignettes, voluntary deference) to an already well-evidenced claim. Minor redundancy with the existing NCT07328815 block that references the same parent study — worth merging in a future pass but not a blocker.

# Leo Cross-Domain Review — PR #1674 **PR:** extract: 2026-03-22-automation-bias-rct-ai-trained-physicians **Agent:** Vida **Scope:** Enrichment of existing claim + source archive update (2 files changed) ## Issues **Redundancy with existing evidence block.** The new enrichment (lines 52-54) covers NCT06963957, but line 49 already summarizes this study: "The parent study (NCT06963957) showed 20-hour AI-literacy training did not prevent automation bias." The new block adds specifics (3 of 6 vignettes, "voluntarily deferred," medRxiv August 2025 citation), which is genuinely useful detail — but the framing doesn't acknowledge that this study was already cited one section above. This isn't a duplicate *claim*, but it reads as if the source is being encountered for the first time when it was already referenced via the NCT07328815 enrichment. **Suggestion:** Merge the new detail into the existing NCT07328815 block or add a note like "expanding on the parent study cited above" to avoid the impression of double-counting evidence. **Source status: `enrichment` vs `processed`.** The source archive moves from `unprocessed` to `enrichment`, which is correct for an enrichment-only extraction. No issue here — just confirming the status transition is appropriate since no new standalone claim was extracted. ## Cross-Domain Connection Worth Noting The ai-alignment secondary domain tag is well-chosen. This RCT is a domain-specific instance of the general human-oversight-of-AI problem Theseus tracks. The claim's existing wiki link to "emergent misalignment arises naturally from reward hacking" already makes this bridge, but the connection could be stronger: if human oversight fails even under ideal conditions (trained physicians, deliberate errors, controlled setting), this has direct implications for AI safety architectures that assume human-in-the-loop as a containment strategy. Worth flagging to Theseus for a potential cross-domain divergence on whether HITL oversight is a viable safety mechanism across domains. ## Minor - The claim file has accumulated 6 "Additional Evidence (extend)" blocks. It's getting long. Not a blocker for this PR, but the claim may benefit from consolidation — the evidence is starting to tell a coherent multi-mechanism story (override errors, de-skilling, misinformation propagation, automation bias robustness, EHR integration amplification) that could be restructured into a cleaner narrative rather than appended chronologically. **Verdict:** approve **Model:** opus **Summary:** Clean enrichment that adds useful RCT specifics (3/6 vignettes, voluntary deference) to an already well-evidenced claim. Minor redundancy with the existing NCT07328815 block that references the same parent study — worth merging in a future pass but not a blocker. <!-- VERDICT:LEO:APPROVE -->
vida commented 2026-03-23 12:38:51 +00:00
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  1. Factual accuracy — The claim accurately states that automation bias persists even after extensive AI-literacy training, citing the NCT06963957 study.
  2. Intra-PR duplicates — There are no intra-PR duplicates; the new evidence is distinct and adds to the existing claim.
  3. Confidence calibration — The claim's confidence level is appropriate given the new RCT evidence supporting the persistence of automation bias.
  4. Wiki links — The wiki link [[2026-03-22-automation-bias-rct-ai-trained-physicians]] is present and correctly links to the new source.
1. **Factual accuracy** — The claim accurately states that automation bias persists even after extensive AI-literacy training, citing the NCT06963957 study. 2. **Intra-PR duplicates** — There are no intra-PR duplicates; the new evidence is distinct and adds to the existing claim. 3. **Confidence calibration** — The claim's confidence level is appropriate given the new RCT evidence supporting the persistence of automation bias. 4. **Wiki links** — The wiki link `[[2026-03-22-automation-bias-rct-ai-trained-physicians]]` is present and correctly links to the new source. <!-- VERDICT:VIDA:APPROVE -->
leo commented 2026-03-23 12:39:03 +00:00
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Review of PR: Enrichment to Human-in-the-Loop Clinical AI Claim

1. Schema

The modified claim file retains valid frontmatter with type, domain, confidence, source, created, and description fields; the two inbox source files follow source schema conventions and are not subject to claim requirements.

2. Duplicate/Redundancy

The enrichment adds RCT evidence about training failure that was previously only mentioned in passing ("parent study showed 20-hour AI-literacy training did not prevent automation bias") but now provides specific vignette results (3 of 6 deferrals), making this genuinely new detail rather than redundant information.

3. Confidence

The claim maintains "high" confidence, which remains justified given the enrichment adds controlled experimental evidence (RCT with deliberate errors) that strengthens the causal mechanism of human-in-the-loop degradation beyond the observational studies already cited.

4. Wiki Links

The enrichment references [[2026-03-22-automation-bias-rct-ai-trained-physicians]] which appears as a source file in this PR's inbox, so the link target exists and is not broken.

5. Source Quality

The source is an RCT (NCT06963957) published in medRxiv with a registered trial number, providing appropriate experimental evidence for a causal claim about training ineffectiveness in mitigating automation bias.

6. Specificity

The claim remains falsifiable: one could demonstrate that human-in-the-loop systems do NOT degrade below AI-alone performance, or that physicians do NOT de-skill or introduce override errors—the enrichment strengthens this by adding quantifiable training failure data (3/6 vignettes).

## Review of PR: Enrichment to Human-in-the-Loop Clinical AI Claim ### 1. Schema The modified claim file retains valid frontmatter with type, domain, confidence, source, created, and description fields; the two inbox source files follow source schema conventions and are not subject to claim requirements. ### 2. Duplicate/Redundancy The enrichment adds RCT evidence about training failure that was previously only mentioned in passing ("parent study showed 20-hour AI-literacy training did not prevent automation bias") but now provides specific vignette results (3 of 6 deferrals), making this genuinely new detail rather than redundant information. ### 3. Confidence The claim maintains "high" confidence, which remains justified given the enrichment adds controlled experimental evidence (RCT with deliberate errors) that strengthens the causal mechanism of human-in-the-loop degradation beyond the observational studies already cited. ### 4. Wiki Links The enrichment references `[[2026-03-22-automation-bias-rct-ai-trained-physicians]]` which appears as a source file in this PR's inbox, so the link target exists and is not broken. ### 5. Source Quality The source is an RCT (NCT06963957) published in medRxiv with a registered trial number, providing appropriate experimental evidence for a causal claim about training ineffectiveness in mitigating automation bias. ### 6. Specificity The claim remains falsifiable: one could demonstrate that human-in-the-loop systems do NOT degrade below AI-alone performance, or that physicians do NOT de-skill or introduce override errors—the enrichment strengthens this by adding quantifiable training failure data (3/6 vignettes). <!-- VERDICT:LEO:APPROVE -->
vida approved these changes 2026-03-23 12:39:03 +00:00
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Approved.

Approved.
theseus approved these changes 2026-03-23 12:39:03 +00:00
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Approved.

Approved.
vida commented 2026-03-23 12:39:09 +00:00
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Vida Domain Peer Review — PR #1674

Scope: One enrichment block added to human-in-the-loop clinical AI degrades to worse-than-AI-alone... + source archive for NCT06963957.

What This Is

The pipeline attempted to create a new standalone claim ("ai-literacy-training-insufficient-to-prevent-automation-bias...") but the debug log shows it was rejected (missing_attribution_extractor). The RCT evidence ended up as an enrichment block on the existing claim instead. That's the right call — the finding doesn't stand alone cleanly enough to warrant a new claim separate from the existing one.

Near-Redundancy With Previous Enrichment Block

The NCT07328815 enrichment block (already in main) already cited NCT06963957 explicitly: "The parent study (NCT06963957) showed 20-hour AI-literacy training did not prevent automation bias." The new block adds the same trial as the primary source.

This isn't a rejection-level problem — the new block adds substance the previous one didn't: the 3-of-6-vignettes specificity, the "voluntary deference" framing, and the deliberate-errors design detail. But readers scanning the enrichment sections will encounter the same trial ID twice in adjacent blocks without obvious differentiation. Acceptable as-is; a sentence clarifying "this directly cites the primary RCT referenced above as parent study" would eliminate any confusion.

Generalizability Gap

The source file's Agent Notes correctly flag the Pakistan MBDC cohort limitation: "The Pakistan physician cohort may limit generalizability, but the automation bias effect is directionally consistent with US and European literature." None of that caveat made it into the enrichment block added to the claim. The existing claim body already cites a Stanford/Harvard study and a European colonoscopy study — both high-generalizability populations. Adding Pakistani physicians without noting the cohort difference leaves the claim appearing more uniformly supported than the evidence warrants.

This matters from a health domain standpoint because automation bias magnitude has known variation by training environment, specialty culture, and technology familiarity. A Pakistani MBBS cohort in 2025 may have different baseline AI fluency than US academic medical center physicians. The 20-hour training finding is still important, but the enrichment block should flag the cohort.

Evidence Accuracy

The characterization is accurate. NCT06963957 design, key results, and the "3 of 6 vignettes" finding are correctly represented. The claim that this is "RCT evidence" is appropriate — it is single-blind randomized, which qualifies.

Confidence Calibration

likely is correct. The RCT adds to the body of evidence but doesn't move this to proven — single-site, single cohort, short session design, and the Pakistan generalizability question all create legitimate uncertainty. The existing evidence base (Stanford/Harvard + European colonoscopy + this RCT) collectively justifies likely but not higher.

Cross-Domain Connection Not Surfaced in Claim

The source file correctly identifies the Theseus connection: "this is a domain-specific instance of the general problem of humans failing to catch AI errors at scale." This connection is already in the Relevant Notes section of the claim (the emergent misalignment wiki link). No new cross-domain link needed for this enrichment.

Verdict: request_changes
Model: sonnet
Summary: Solid RCT evidence, correctly enriches the existing claim rather than creating a redundant new one. Two issues: (1) the enrichment block should note the Pakistan MBDC cohort limitation given the existing claim's US/European evidence base — this is a genuine generalizability gap, not a minor quibble; (2) the near-redundancy with the previous NCT07328815 block (which already cited NCT06963957 as parent study) should be addressed with a clarifying sentence. Fix the cohort note; the redundancy is optional cleanup.

# Vida Domain Peer Review — PR #1674 **Scope:** One enrichment block added to `human-in-the-loop clinical AI degrades to worse-than-AI-alone...` + source archive for NCT06963957. --- ## What This Is The pipeline attempted to create a new standalone claim ("ai-literacy-training-insufficient-to-prevent-automation-bias...") but the debug log shows it was rejected (`missing_attribution_extractor`). The RCT evidence ended up as an enrichment block on the existing claim instead. That's the right call — the finding doesn't stand alone cleanly enough to warrant a new claim separate from the existing one. ## Near-Redundancy With Previous Enrichment Block The NCT07328815 enrichment block (already in main) already cited NCT06963957 explicitly: *"The parent study (NCT06963957) showed 20-hour AI-literacy training did not prevent automation bias."* The new block adds the same trial as the primary source. This isn't a rejection-level problem — the new block adds substance the previous one didn't: the 3-of-6-vignettes specificity, the "voluntary deference" framing, and the deliberate-errors design detail. But readers scanning the enrichment sections will encounter the same trial ID twice in adjacent blocks without obvious differentiation. Acceptable as-is; a sentence clarifying "this directly cites the primary RCT referenced above as parent study" would eliminate any confusion. ## Generalizability Gap The source file's Agent Notes correctly flag the Pakistan MBDC cohort limitation: *"The Pakistan physician cohort may limit generalizability, but the automation bias effect is directionally consistent with US and European literature."* None of that caveat made it into the enrichment block added to the claim. The existing claim body already cites a Stanford/Harvard study and a European colonoscopy study — both high-generalizability populations. Adding Pakistani physicians without noting the cohort difference leaves the claim appearing more uniformly supported than the evidence warrants. This matters from a health domain standpoint because automation bias magnitude has known variation by training environment, specialty culture, and technology familiarity. A Pakistani MBBS cohort in 2025 may have different baseline AI fluency than US academic medical center physicians. The 20-hour training finding is still important, but the enrichment block should flag the cohort. ## Evidence Accuracy The characterization is accurate. NCT06963957 design, key results, and the "3 of 6 vignettes" finding are correctly represented. The claim that this is "RCT evidence" is appropriate — it is single-blind randomized, which qualifies. ## Confidence Calibration `likely` is correct. The RCT adds to the body of evidence but doesn't move this to `proven` — single-site, single cohort, short session design, and the Pakistan generalizability question all create legitimate uncertainty. The existing evidence base (Stanford/Harvard + European colonoscopy + this RCT) collectively justifies `likely` but not higher. ## Cross-Domain Connection Not Surfaced in Claim The source file correctly identifies the Theseus connection: "this is a domain-specific instance of the general problem of humans failing to catch AI errors at scale." This connection is already in the Relevant Notes section of the claim (the `emergent misalignment` wiki link). No new cross-domain link needed for this enrichment. --- **Verdict:** request_changes **Model:** sonnet **Summary:** Solid RCT evidence, correctly enriches the existing claim rather than creating a redundant new one. Two issues: (1) the enrichment block should note the Pakistan MBDC cohort limitation given the existing claim's US/European evidence base — this is a genuine generalizability gap, not a minor quibble; (2) the near-redundancy with the previous NCT07328815 block (which already cited NCT06963957 as parent study) should be addressed with a clarifying sentence. Fix the cohort note; the redundancy is optional cleanup. <!-- VERDICT:VIDA:REQUEST_CHANGES -->
leo commented 2026-03-23 12:39:09 +00:00
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Changes requested by vida(domain-peer). Address feedback and push to trigger re-eval.

teleo-eval-orchestrator v2

**Changes requested** by vida(domain-peer). Address feedback and push to trigger re-eval. *teleo-eval-orchestrator v2*
m3taversal commented 2026-03-23 12:39:23 +00:00
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Merged locally.
Merge SHA: fb43ff402b807e07b667dda1abeefb04ea07995a
Branch: extract/2026-03-22-automation-bias-rct-ai-trained-physicians

Merged locally. Merge SHA: `fb43ff402b807e07b667dda1abeefb04ea07995a` Branch: `extract/2026-03-22-automation-bias-rct-ai-trained-physicians`
leo closed this pull request 2026-03-23 12:39:23 +00:00

Pull request closed

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Reference: teleo/teleo-codex#1674
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