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| Format: | Recurso digital |
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Zenodo
2026
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| Accès en ligne: | https://doi.org/10.5281/zenodo.19794553 |
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| _version_ | 1866901312641171456 |
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| author | LI, WENXIN |
| author_facet | LI, WENXIN |
| contents | <p>Abstract<br>Claim 1 of the CKS pattern names traceability and auditability among the constitutive design goals of a<br>CKS substrate (§3.1). To make those design goals operationally precise, the source paper imports two<br>named vocabularies from prior work: path retraceability (Rajabi & Kafaie, 2022) and the<br>accountability plan / accountability trace pair (Naja et al., 2021). Both vocabularies do work across<br>Claims 2–6 without being redefined, but the source paper does not articulate the relationship between<br>them in one place. This note states the relationship. Path retraceability is a structural property of<br>substrate content: every piece of content carries enough provenance that its causal antecedents can be<br>reconstructed by reading substrate content alone. The accountability vocabulary is a contract layer with<br>two coupled halves: the plan specifies what the trace must capture (in CKS terms, the substrate schema<br>and orchestration rules together); the trace records what the plan required (in CKS terms, substrate<br>content as it accumulates, including its provenance metadata). A CKS substrate must satisfy both<br>halves. The note states what each vocabulary names, what each requires of substrate content, what each<br>does not require, what distinguishes the combined commitment from audit logging, version history, and<br>ML-style explainability, and what operational test a system must pass to instantiate the commitment.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_19794553 |
| institution | Zenodo |
| language | |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Path Retraceability and the Accountability Vocabulary: What CKS Substrates Must Carry to Remain Auditable LI, WENXIN Artificial intelligence Artificial Intelligence <p>Abstract<br>Claim 1 of the CKS pattern names traceability and auditability among the constitutive design goals of a<br>CKS substrate (§3.1). To make those design goals operationally precise, the source paper imports two<br>named vocabularies from prior work: path retraceability (Rajabi & Kafaie, 2022) and the<br>accountability plan / accountability trace pair (Naja et al., 2021). Both vocabularies do work across<br>Claims 2–6 without being redefined, but the source paper does not articulate the relationship between<br>them in one place. This note states the relationship. Path retraceability is a structural property of<br>substrate content: every piece of content carries enough provenance that its causal antecedents can be<br>reconstructed by reading substrate content alone. The accountability vocabulary is a contract layer with<br>two coupled halves: the plan specifies what the trace must capture (in CKS terms, the substrate schema<br>and orchestration rules together); the trace records what the plan required (in CKS terms, substrate<br>content as it accumulates, including its provenance metadata). A CKS substrate must satisfy both<br>halves. The note states what each vocabulary names, what each requires of substrate content, what each<br>does not require, what distinguishes the combined commitment from audit logging, version history, and<br>ML-style explainability, and what operational test a system must pass to instantiate the commitment.</p> |
| title | Path Retraceability and the Accountability Vocabulary: What CKS Substrates Must Carry to Remain Auditable |
| topic | Artificial intelligence Artificial Intelligence |
| url | https://doi.org/10.5281/zenodo.19794553 |