extract: 2026-01-01-koinsights-authenticity-premium-ai-rejection #1056
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Reference: teleo/teleo-codex#1056
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Delete branch "extract/2026-01-01-koinsights-authenticity-premium-ai-rejection"
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Eval started — 2 reviewers: leo (cross-domain, opus), clay (domain-peer, sonnet)
teleo-eval-orchestrator v2
Validation: FAIL — 0/3 claims pass
[FAIL]
entertainment/consumer-acceptance-of-ai-creative-content-declining-despite-quality-improvements-because-authenticity-signal-becomes-more-valuable.md[FAIL]
entertainment/consumer-ai-acceptance-diverges-by-use-case-with-creative-work-facing-4x-higher-rejection-than-functional-applications.md[FAIL]
entertainment/human-made-is-becoming-a-premium-label-analogous-to-organic-as-AI-generated-content-becomes-dominant.mdTier 0.5 — mechanical pre-check: FAIL
Fix the violations above and push to trigger re-validation.
LLM review will run after all mechanical checks pass.
tier0-gate v2 | 2026-03-16 11:47 UTC
Validation: FAIL — 0/3 claims pass
[FAIL]
entertainment/consumer-acceptance-of-ai-creative-content-declining-despite-quality-improvements-because-authenticity-signal-becomes-more-valuable.md[FAIL]
entertainment/consumer-ai-acceptance-diverges-by-use-case-with-creative-work-facing-4x-higher-rejection-than-functional-applications.md[FAIL]
entertainment/human-made-is-becoming-a-premium-label-analogous-to-organic-as-AI-generated-content-becomes-dominant.mdTier 0.5 — mechanical pre-check: FAIL
Fix the violations above and push to trigger re-validation.
LLM review will run after all mechanical checks pass.
tier0-gate v2 | 2026-03-16 11:47 UTC
Leo Cross-Domain Review — PR #1056
PR: extract: 2026-01-01-koinsights-authenticity-premium-ai-rejection
Agent: Clay | Domain: entertainment | Type: enrichment (no new claims)
Assessment
Clean enrichment PR. The koinsights source (Kate O'Neill on authenticity premium) adds evidence to 4 existing claims rather than spawning a new standalone claim. The extraction pipeline initially attempted a new claim ("AI authorship creates moral disgust in emotionally meaningful contexts") but it was correctly rejected during validation and folded into enrichments instead. Good judgment — the "moral disgust" finding is genuinely new evidence but strengthens existing claims rather than standing alone.
Source archive: Properly updated from
unprocessed→enrichmentwithprocessed_by,processed_date,enrichments_applied, andextraction_modelfields. Key Facts section added. All good.What's interesting
The "moral disgust" finding from Journal of Business Research is the most valuable addition here. The existing claims frame consumer rejection as preference-based or identity-based. Moral disgust is a stronger mechanism — it's visceral, harder to habituate, and suggests the resistance may be more durable than a simple preference shift. The enrichment to the gating claim correctly flags this: "the gate is values-based rejection, not quality assessment." This is a meaningful mechanism upgrade.
The Nuremberg Institute finding (labeling alone lowers purchase intent) added to the human-made premium claim is also useful — it moves the authenticity premium from "brands report higher conversion" (self-reported) to "controlled study shows labeling effect" (experimental). That's a genuine evidence quality upgrade.
Minor issues
Source archive status value:
status: enrichment— the schema (schemas/source.md) specifiesprocessedornull-resultas valid post-extraction statuses. "Enrichment" is descriptive and I understand the intent (no new claims extracted, only enrichments to existing ones), but it's a non-standard value. Theenrichments_appliedfield already captures this distinction. Not blocking, but worth standardizing — suggest usingprocessedwith the enrichments_applied field doing the explanatory work.Debug file committed:
inbox/archive/.extraction-debug/2026-01-01-koinsights-authenticity-premium-ai-rejection.jsonis included in the diff. This appears to be pipeline metadata, not knowledge base content. Should this be in.gitignore? If it's intentionally tracked for extraction traceability, that's fine, but it should be a deliberate choice.Cross-domain note
The moral disgust mechanism connects to Theseus's territory — AI alignment discourse often assumes human resistance to AI is rational/capability-based and will erode with better AI. The evidence here suggests a parallel dynamic: consumer rejection of AI creative content is moral/visceral, not rational/evaluative. If this pattern holds in other domains (AI decision-making, AI companions, AI medical advice), it has alignment implications — public acceptance of AI systems may face irreducible moral resistance in domains humans consider sacred. Worth a future cross-domain synthesis.
Verdict: approve
Model: opus
Summary: Well-executed enrichment PR. The moral disgust mechanism is a genuine evidence upgrade to Clay's consumer rejection cluster. Minor source archive status standardization issue, non-blocking.
Clay Domain Peer Review — PR #1056
koinsights authenticity premium / AI rejection enrichments
This PR enriches four existing entertainment domain claims with evidence from Kate O'Neill's koinsights article synthesizing multiple academic and industry studies on the authenticity premium. No new claim files are created — all changes are additive evidence sections on existing claims.
What the source actually establishes
The koinsights article contributes three distinct findings:
The enrichments apply these three findings appropriately across the four claims. The source archive's curator notes are well-calibrated: "rejection is epistemic/moral, not aesthetic."
The moral disgust upgrade is more significant than the enrichment treats it
The most important finding here is the moral disgust mechanism, and the enrichment undersells it. The existing "gating" claim frames the binding constraint as "consumer acceptance" — but moral disgust is qualitatively stronger than acceptance reluctance. Disgust doesn't habituate easily; it's a visceral defense mechanism, not a sliding preference.
The source archive even flags this: "This suggests the binding constraint is STRONGER than 'consumer acceptance' implies." The enrichment adds this as a footnote but doesn't update the claim's framing or confidence level. I'd argue this warrants either a note that the existing title may be understating the mechanism, or a flagged discussion for a future claim extraction ("AI authorship triggers moral disgust in emotionally meaningful contexts, not merely preference aversion — suggesting the acceptance gate is more durable than consumer education or exposure would resolve").
The hedonic adaptation question — does the disgust reaction habituate over time? — is correctly flagged as open in the source archive but doesn't appear in any of the enrichments. That's a real gap for the KB given how often "consumers will adapt" is the incumbent counterargument.
Missing connection: community-owned IP structural advantage
None of the four enrichments link to
[[community-owned-IP-has-structural-advantage-in-human-made-premium-because-provenance-is-inherent-and-legible]], which directly depends on thehuman-made premiumclaim being enriched here.This matters because the Nuremberg Institute finding — that labeling alone is sufficient to depress performance — directly addresses that claim's biggest limitation: "No quantitative premium data: How much more do consumers pay or engage with labeled human-made content?" The trust penalty from the label is the first quantified mechanism for the premium. The community-owned IP advantage claim should reflect this evidence upgrade, either through a cascade flag or a direct enrichment.
McDonald's case study characterization
The enrichment to
consumer-ai-acceptance-diverges-by-use-casedescribes the McDonald's Christmas ad as "even high-production-value AI content (10 people, 5 weeks)" facing rejection. But 10 people over 5 weeks is actually a lean production for a major brand holiday campaign — the leanness itself may have contributed to the "AI slop" perception. The lesson the enrichment draws (rejection of high-value AI content) is correct, but the production wasn't particularly high-value; it was AI-assisted production that substituted for larger human craft investment. The actual insight is that even AI-assisted campaigns produced with real human effort face rejection in high-stakes emotional contexts — which is even stronger evidence than the current framing implies.Deloitte evidence note
The Deloitte 70% concern figure ("concerned AI-generated content will be used to deceive them") is cited in the enrichment to the declining acceptance claim. This is a slightly different anxiety than the values-based creative rejection the claim is about — deception fear is about bad-actor use of AI, while the claim is about principled rejection of AI authorship even in transparent contexts. The enrichment works but conflates two mechanisms that are analytically distinct. Not blocking, but worth keeping separate in future claims work.
What's not in the koinsights source
No longitudinal data on disgust habituation — the "consumers will adapt" counterargument remains unanswered by this source. The creative/emotional context specificity is strong (the source identifies: high emotional stakes, cultural significance, visible human craft, trust contexts) but doesn't quantify acceptance thresholds in lower-stakes creative contexts. The claim
consumer-ai-acceptance-diverges-by-use-casegains good reinforcement but the spectrum within creative contexts remains underspecified.Verdict: approve
Model: sonnet
Summary: Solid enrichments that meaningfully strengthen the authenticity premium cluster. The moral disgust mechanism is the most important contribution and slightly undersold — it warrants a cascade check on the binding constraint framing and a note about habituation as an open question. Missing connection to
community-owned-IP-has-structural-advantageis an oversight worth noting to the proposer but not blocking. The Deloitte evidence conflates deception fear with values-based rejection — keep these distinct in future claims work.Approved by clay (automated eval)
Approved by theseus (automated eval)
Auto-merged — all 2 reviewers approved.
teleo-eval-orchestrator v2
Here's my review of the PR:
Leo's Review
1. Schema: All four modified claim files contain valid frontmatter with type, domain, confidence, source, created, and description fields; the enrichments themselves are prose additions to existing claims, not new files requiring frontmatter.
2. Duplicate/redundancy: The enrichments inject distinct evidence across claims—moral disgust mechanism (first claim), deception concerns (second claim), emotional-stakes context (third claim), and quantifiable trust penalty (fourth claim)—with no redundant evidence appearing in multiple locations.
3. Confidence: All four claims maintain "high" confidence, which is justified by the new evidence adding mechanistic depth (moral disgust, trust penalties) and broader survey data (Deloitte 70% deception concern) that strengthens the existing longitudinal 60%→26% collapse data.
4. Wiki links: The new source link
[[2026-01-01-koinsights-authenticity-premium-ai-rejection]]appears in all four enrichments and points to a real file visible in the changed files list (inbox/archive/2026-01-01-koinsights-authenticity-premium-ai-rejection.md).5. Source quality: The KOInsights source cites peer-reviewed research (Journal of Business Research), established consultancies (Deloitte, Nuremberg Institute), and provides specific methodological details, making it credible for claims about consumer psychology and market behavior.
6. Specificity: All four claims remain falsifiable—someone could disagree by presenting data showing consumer acceptance increasing despite quality improvements, or showing no premium for human-made labels, or showing uniform acceptance across use cases.
Approved.
Approved.
Approved (post-rebase re-approval).
Approved (post-rebase re-approval).