statements ยท statement-BATCH-2026-006-041
source-BATCH-2026-005-009
The authors argue that every uncompensated direct harm caused by an agentic system should remain attributable to at least one accountable human legal entity.
Statement context
- Statement type
- policy position
- Exact source locator
- Official PDF p. 3, Section 1 "Introduction", 2023 version
- Source date
- Unknown
- Role at source time
- joint authors of the agentic-AI governance paper
- Evidence character
- normative recommendation
- Scope
- Allocation of accountability for direct harms from agentic systems.
Recorded uncertainty: This is a normative position, not a statement of current law.
Indexed source: Practices for Governing Agentic AI Systems
Evidence lineage and transparency
| Relationship field | Linked identifiers |
|---|---|
| topic ids | topic-ai-agents, topic-ai-governance, topic-cybersecurity, topic-non-human-identity |
Machine review: machine checked. Human review: approved. Workflow: published.
Complete structured record
- statement id
- statement-BATCH-2026-006-041
- source id
- source-BATCH-2026-005-009
- person id
- Unknown
- institutional author
- Shavit et al. (joint paper authors)
- book edition id
- Unknown
- speaker role at source time
- joint authors of the agentic-AI governance paper
- organization at source time
- OpenAI (publisher; individual affiliations are not stated in the paper)
- statement type
- policy_position
- neutral paraphrase
- The authors argue that every uncompensated direct harm caused by an agentic system should remain attributable to at least one accountable human legal entity.
- direct quote
- Unknown
- direct quote rights note
- Unknown
- exact locator
- Official PDF p. 3, Section 1 "Introduction", 2023 version
- locator type
- pdf_page
- source date
- Unknown
- topic ids
- topic-ai-agents, topic-ai-governance, topic-cybersecurity, topic-non-human-identity
- executive role context
- role-ciso, role-cio, role-cto, role-general-counsel, role-board-director
- industry context
- cross-sector
- geographic context
- global policy context
- evidence character
- normative_recommendation
- factual verification status
- not_applicable
- statement scope
- Allocation of accountability for direct harms from agentic systems.
- uncertainty
- This is a normative position, not a statement of current law.
- extraction method
- Machine-assisted close reading of the exact verified source version; original neutral paraphrase; human review pending.
- machine extraction confidence
- 0.94
- independent agent review status
- not_started
- publication status
- published
- workflow status
- published
- machine review status
- machine_checked
- human review status
- approved
- reviewed by
- Murray Newlands
- reviewed at
- 2026-08-16T23:17:22Z
Provenance and revision history
{
"provenance": [
{
"source_url": "https://cdn.openai.com/papers/practices-for-governing-agentic-ai-systems.pdf",
"accessed_at": "2026-08-15",
"retrieval_method": "Exact verified source version inherited from BATCH-2026-005 and statement-level close reading",
"exact_locator": "Official PDF p. 3, Section 1 \"Introduction\", 2023 version",
"content_hash": "22b3a8607ed781a848b82b0bfe8e638b16cd027aac90a19b2aecf236063d0e7c",
"batch_id": "BATCH-2026-006",
"prompt_id": "OEII-STATEMENT-CODING",
"prompt_version": "2.0",
"notes": "Source eligibility inherited from source-BATCH-2026-005-009; human attribution and publication review pending."
}
],
"revision_history": [
{
"changed_at": "2026-08-16T23:17:22Z",
"changed_by": "Murray Newlands",
"summary": "Approved for the governed-identities pilot release under the exact scope, exclusions, rights treatment, and limitations recorded in issue #18.",
"batch_id": "BATCH-2026-006"
}
]
}