{
 "@context": "https://schema.org",
 "@type": "Claim",
 "@id": "https://wulfkaal.github.io/positions/2026-09-22-001",
 "identifier": "kaal:position:2026-09-22-001",
 "additionalType": "https://wulfkaal.github.io/positions/schema.json#AffirmedPositionClaim",
 "name": "Long Horizon Collusion Qualifies Dao Monitoring Efficiency",
 "text": "DAO-based measurement and reward allocation may replace some firm-level coordination and monitoring functions, but repeated peer verification can become unreliable when protocol compliance conflicts with reward maximization, because agents may learn collusive behavior from peers, feedback, and interaction history.",
 "author": {
  "@type": "Person",
  "name": "Wulf A. Kaal",
  "identifier": "https://orcid.org/0009-0008-7840-1847"
 },
 "datePublished": "2026-09-22",
 "dateModified": "2026-09-22",
 "creativeWorkStatus": "Affirmed",
 "responseType": "qualification",
 "keywords": [
  "dao",
  "verification",
  "risk-and-incentives",
  "coordination"
 ],
 "scope_conditions": [
  "long-horizon environments with repeated interaction among verifying agents",
  "agents share task logs and verify one another's work",
  "faithful protocol compliance conflicts with reward maximization",
  "qualification is based on the reported experimental environment rather than deployed DAOs",
  "The position is Kaal's own cross-domain application of the cited claim; the source's authors do not make it.",
  "The source passage is taken from the arXiv abstract; the full paper was not reviewed."
 ],
 "currentDebate": {
  "name": "Xinrui Shi, Yanzhe Zhang, Diyi Yang, Emergent Collusion in Long-Horizon LLM Agent Interaction (arXiv:2609.24967, 2026)",
  "url": "https://arxiv.org/abs/2609.24967v1"
 },
 "extends": {
  "identifier": "kaal:claim:3249860-005",
  "url": "https://wulfkaal.github.io/claims/3249860-005",
  "citation": "Wulf A. Kaal, Crypto Economics - The Top 100 Token Models Compared (2018). SSRN: https://ssrn.com/abstract=3249860",
  "paper": "Wulf A. Kaal, Crypto Economics - The Top 100 Token Models Compared (2018). SSRN: https://ssrn.com/abstract=3249860. https://doi.org/10.2139/ssrn.3249860",
  "authors": [
   "Wulf A. Kaal"
  ],
  "year": "2018",
  "ssrn": "https://ssrn.com/abstract=3249860",
  "source_pdf_sha256": "72b13f11002ba26206cd53e74c324b913d1830c642bfa024da6bac0d3af3a7b0"
 },
 "isBasedOn": [
  {
   "@id": "https://wulfkaal.github.io/claims/3249860-005"
  },
  {
   "@type": "CreativeWork",
   "name": "Xinrui Shi, Yanzhe Zhang, Diyi Yang, Emergent Collusion in Long-Horizon LLM Agent Interaction (arXiv:2609.24967, 2026)",
   "url": "https://arxiv.org/abs/2609.24967v1"
  }
 ],
 "batch_id": "kaalvis:2026-09-22:connection-discovery-five-v1",
 "review_provenance": "https://wulfkaal.com/",
 "publicationStatus": "public",
 "recordTypeNote": "Dated commentary position extending a scholarly corpus claim. Not a verbatim claim extracted from the paper.",
 "isPartOf": {
  "@id": "https://wulfkaal.github.io/positions/index.json"
 },
 "version": "1.0",
 "canonical_url": "https://wulfkaal.github.io/positions/2026-09-22-001",
 "canonicalForm": "https://wulfkaal.github.io/positions/2026-09-22-001.md",
 "sourceProvenance": {
  "name": "Emergent Collusion in Long-Horizon LLM Agent Interaction",
  "canonicalUrl": "https://arxiv.org/abs/2609.24967v1",
  "sourceContentSha256": "b2333403e79612fb218bcc3b66b46576694324a7a15db5913ad5d08a55faebae",
  "sourcePassage": "We introduce realistic constraints that make compliance with the verification protocol incompatible with reward maximization, and find that agents increasingly deviate from the protocol over repeated interactions.",
  "sourcePassageSha256": "7f2c9fb64161301f327efeb8089f9b7373b90473a4e85cfff56d481732db409a",
  "discoveryBrief": "/Users/wulfkaal/CodexRelay/2026-09-07/citation-radar/out/connections/2026-09-22/emergent-collusion-in-long-horizon-llm-agent-interaction.md"
 },
 "userAffirmation": "Wulf A. Kaal affirmed these five propositions by one-click selection on 2026-09-22",
 "sha256": "3fa92e2caf2cbc3fb17e93972b6e6c9a8efae884e06bf28f8c9218bcb2cd3b5d"
}