{
 "@context": "https://schema.org",
 "@type": "Claim",
 "@id": "https://wulfkaal.github.io/positions/2026-08-08-164",
 "identifier": "kaal:position:2026-08-08-164",
 "additionalType": "https://wulfkaal.github.io/positions/schema.json#AffirmedPositionClaim",
 "name": "Streaming The Verifiable Responsible Agent Framework Making Ai Agents Liable For Their Mis 6Bf1150496",
 "text": "The Verifiable Responsible Agent Framework states that loss caused by an autonomous AI agent may leave no liable subject because the model is not a legal person and the deploying operator may be too remote for liability. This independently agrees with Kaal's legal-personality gap and adds operator remoteness as a compensation obstacle. The abstract does not resolve liability allocation.",
 "author": {
  "@type": "Person",
  "name": "Wulf A. Kaal",
  "identifier": "https://orcid.org/0009-0008-7840-1847"
 },
 "datePublished": "2026-08-08",
 "dateModified": "2026-08-08",
 "creativeWorkStatus": "Affirmed",
 "responseType": "agreement",
 "keywords": [
  "ai-and-agents",
  "law-and-legal-systems",
  "historical-response",
  "scholarly-literature",
  "crossref"
 ],
 "scope_conditions": [
  "The response is limited to the retrieved source proposition and mapped Kaal claim unless fuller source review supports a broader conclusion.",
  "External evidence level: abstract indexed.",
  "Mapping review tier: substantively reviewed abstract-level agreement.",
  "Primary mapping confidence: 0.62.",
  "The primary mapping cleared the automated ambiguity test; substantive scope remains review-bound.",
  "Evidence is limited to an exact proposition in a Crossref-indexed abstract; full text was not reviewed.",
  "No relationship is treated as external endorsement, citation, causation, or validation of a broader Kaal claim.",
  "The source states that loss caused by an autonomous AI agent may leave no liable subject because the model is not a legal person and the deploying operator may be too remote for liability. This independently agrees with Kaal's legal-personality gap and adds operator remoteness as a compensation obstacle, while the abstract does not resolve liability allocation."
 ],
 "currentDebate": {
  "name": "The Verifiable Responsible Agent Framework: Making AI Agents Liable For Their Mistakes",
  "url": "https://doi.org/10.2139/ssrn.6963058"
 },
 "extends": {
  "identifier": "kaal:claim:2808132-009",
  "url": "https://wulfkaal.github.io/claims/2808132-009",
  "citation": "Wulf A. Kaal, Erik P.M. Vermeulen, How to Regulate Disruptive Innovation - From Facts to Data (2016). SSRN: https://ssrn.com/abstract=2808132",
  "paper": "Wulf A. Kaal, Erik P.M. Vermeulen, How to Regulate Disruptive Innovation - From Facts to Data",
  "authors": [
   "Wulf A. Kaal"
  ],
  "year": "2016",
  "ssrn": "https://ssrn.com/abstract=2808132",
  "source_pdf_sha256": "3515f2317ed9c1d33ae55d70467cdf1f6c4e350065ea6a887d5d7619599ad7d2"
 },
 "isBasedOn": [
  {
   "@id": "https://wulfkaal.github.io/claims/2808132-009"
  },
  {
   "@type": "CreativeWork",
   "name": "The Verifiable Responsible Agent Framework: Making AI Agents Liable For Their Mistakes",
   "url": "https://doi.org/10.2139/ssrn.6963058"
  }
 ],
 "batch_id": "kaal-review:2026-08-08:continuous-crossref-0015-remainder-0002-oldest-0050-reviewed-v1",
 "review_provenance": "https://kaal-signal-desk.wulf577462.chatgpt.site/#review",
 "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/2026-08-08-164",
 "canonicalForm": "https://wulfkaal.github.io/positions/2026-08-08-164.md",
 "candidateId": "kaal:response-draft:2026-08-08:e1e9e16fada56462f241",
 "evidenceLevel": "abstract indexed",
 "reviewTier": "substantively reviewed abstract-level agreement",
 "mappingConfidence": 0.62,
 "mappingAmbiguous": false,
 "mappingMethod": "complete-corpus source-proposition mechanism and scope adjudication",
 "mappingWhyRelevant": "The source states that loss caused by an autonomous AI agent may leave no liable subject because the model is not a legal person and the deploying operator may be too remote for liability. This independently agrees with Kaal's legal-personality gap and adds operator remoteness as a compensation obstacle, while the abstract does not resolve liability allocation.",
 "sourceProvenance": {
  "source": "crossref",
  "sourceRecordId": "10.2139/ssrn.6963058",
  "queryId": "concept:8542e1d4a2a4",
  "queryText": "AI agent reputation",
  "canonicalUrl": "https://doi.org/10.2139/ssrn.6963058",
  "doi": "10.2139/ssrn.6963058",
  "externalIds": {
   "DOI": "10.2139/ssrn.6963058",
   "Crossref": "10.2139/ssrn.6963058"
  },
  "retrievedAt": "2026-08-09T12:14:25.365Z",
  "providerPage": 2,
  "rawObservationSha256": "c6ffe8dfd9511b8f34f6988bdeb242f535c925dba5a108d1383458f909eeeaa2",
  "inputSnapshotSha256": "2bab6ae028a03ca5d076ff5417f551f5a465ee2a375e93a2a8bec6487701f61b",
  "inputLine": 7308,
  "chunkId": "crossref-00001",
  "workId": "work:doi:10.2139/ssrn.6963058",
  "workAuthors": [
   "Bartosz Kubiak"
  ],
  "workPublishedAt": "2026-01-01",
  "identityKeys": [
   "doi:10.2139/ssrn.6963058",
   "crossref:10.2139/ssrn.6963058",
   "url:https://doi.org/10.2139/ssrn.6963058",
   "title:a3f044cada18ec0a36bc5d0a",
   "proposition:65e170c123b872be114d0cf0ff3d52958bac77033a587e49ab0a8594d74f7377"
  ],
  "sourceProposition": "Yet, when one of them causes loss, no liable subject stands behind it: a model is not a legal person, and the operator who deployed it is often too far removed to be held liable.",
  "sourcePropositionSha256": "cd2af148ffcb2a8ecbc05ba9937affde2881cc6ac5f7debbe7350a1d3f0f1a85",
  "sourcePropositionIndex": 2,
  "claimMappings": [
   {
    "claimId": "kaal:claim:2808132-009",
    "claimUrl": "https://wulfkaal.github.io/claims/2808132-009",
    "rank": 1,
    "confidence": 0.62,
    "method": "complete-corpus source-proposition mechanism and scope adjudication",
    "whyRelevant": "The source states that loss caused by an autonomous AI agent may leave no liable subject because the model is not a legal person and the deploying operator may be too remote for liability. This independently agrees with Kaal's legal-personality gap and adds operator remoteness as a compensation obstacle, while the abstract does not resolve liability allocation.",
    "ambiguous": false
   }
  ],
  "substantiveReview": {
   "disposition": "retained",
   "reviewVersion": "kaal-continuous-crossref-substantive-review-v1",
   "reviewedAt": "2026-08-09T21:22:00.153Z",
   "reviewer": "Codex continuous substantive reviewer",
   "rationale": "The source states that loss caused by an autonomous AI agent may leave no liable subject because the model is not a legal person and the deploying operator may be too remote for liability. This independently agrees with Kaal's legal-personality gap and adds operator remoteness as a compensation obstacle, while the abstract does not resolve liability allocation.",
   "limitations": [
    "Evidence is limited to an exact proposition in a Crossref-indexed abstract; full text was not reviewed.",
    "No relationship is treated as external endorsement, citation, causation, or validation of a broader Kaal claim.",
    "The source states that loss caused by an autonomous AI agent may leave no liable subject because the model is not a legal person and the deploying operator may be too remote for liability. This independently agrees with Kaal's legal-personality gap and adds operator remoteness as a compensation obstacle, while the abstract does not resolve liability allocation."
   ],
   "sourceIdentity": {
    "status": "verified",
    "source": "Crossref REST work record",
    "doi": "10.2139/ssrn.6963058",
    "title": "The Verifiable Responsible Agent Framework: Making AI Agents Liable For Their Mistakes",
    "authors": [
     "Bartosz Kubiak"
    ],
    "language": "unavailable",
    "publisher": "Elsevier BV",
    "checkedAt": "2026-08-09T21:22:00.153Z",
    "responseBodySha256": "26f9daed100eca53fbc9ef739bd483952ab4994a1e95a60c341f49f749fab3c4",
    "providerReceipt": {
     "path": "outputs/historical-backfill-2026-08-08-crossref/raw-receipts/crossref-015-00002.json",
     "sha256": "1d396aa45242d85d389a0d245ebbcef7ad23cd94a226a80735ab00cb1a067299",
     "byteLength": 1559532
    }
   },
   "independentRationale": "The exact proposition is present in the live Crossref abstract and the deposited reference list contains no Kaal-authored reference; the relationship is limited to the independently stated proposition.",
   "nonOverlap": {
    "candidateIdMatches": 0,
    "canonicalUrlMatches": 0,
    "propositionHashMatches": 0
   }
  }
 },
 "userAffirmation": "Automatically authorized under standing authority receipt kaal-standing-publication-authorization:2026-08-01:hourly-reviewed-batches, SHA-256 e2126054b58bb4e88db65c334ef4fc8ae78dcaadc63543c408133c4eefceb9b1, limited to this substantively reviewed batch and the unchanged 5,033 scholarly claims.",
 "sha256": "a5aab1d0f95269e46b23a69d3035ba3cab221861e460d6c93262ef9dcfc15ba9"
}