{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:NEFGZ5HUY4Q2O46YKJKI3PHBCK","short_pith_number":"pith:NEFGZ5HU","schema_version":"1.0","canonical_sha256":"690a6cf4f4c721a773d852548dbce1129dba27b2d45cec8091cd8a1d06ae1bd5","source":{"kind":"arxiv","id":"2201.05159","version":2},"attestation_state":"computed","paper":{"title":"Structured access: an emerging paradigm for safe AI deployment","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.HC","cs.SE"],"primary_cat":"cs.AI","authors_text":"Toby Shevlane","submitted_at":"2022-01-13T19:30:16Z","abstract_excerpt":"Structured access is an emerging paradigm for the safe deployment of artificial intelligence (AI). Instead of openly disseminating AI systems, developers facilitate controlled, arm's length interactions with their AI systems. The aim is to prevent dangerous AI capabilities from being widely accessible, whilst preserving access to AI capabilities that can be used safely. The developer must both restrict how the AI system can be used, and prevent the user from circumventing these restrictions through modification or reverse engineering of the AI system. Structured access is most effective when i"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2201.05159","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2022-01-13T19:30:16Z","cross_cats_sorted":["cs.HC","cs.SE"],"title_canon_sha256":"7c08a7948fd3d1f4090fc4490d8aa2c403076fc9ba56d18fc1da97716d6068a8","abstract_canon_sha256":"7cd9503c2cca5695f87a1671f3a4007db0f587a8a791c59f01d6b12393e12111"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:13:12.198480Z","signature_b64":"iKCJjaCAmggCnYj32Af2KKQIzLee6K3wsdiX0sDh2EWS3B+f7tjFMlTbqvOKxTayq80w9ERPB8qpjNIM3pWfCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"690a6cf4f4c721a773d852548dbce1129dba27b2d45cec8091cd8a1d06ae1bd5","last_reissued_at":"2026-07-05T04:13:12.197997Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:13:12.197997Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Structured access: an emerging paradigm for safe AI deployment","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.HC","cs.SE"],"primary_cat":"cs.AI","authors_text":"Toby Shevlane","submitted_at":"2022-01-13T19:30:16Z","abstract_excerpt":"Structured access is an emerging paradigm for the safe deployment of artificial intelligence (AI). Instead of openly disseminating AI systems, developers facilitate controlled, arm's length interactions with their AI systems. The aim is to prevent dangerous AI capabilities from being widely accessible, whilst preserving access to AI capabilities that can be used safely. The developer must both restrict how the AI system can be used, and prevent the user from circumventing these restrictions through modification or reverse engineering of the AI system. Structured access is most effective when i"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2201.05159","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2201.05159/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2201.05159","created_at":"2026-07-05T04:13:12.198053+00:00"},{"alias_kind":"arxiv_version","alias_value":"2201.05159v2","created_at":"2026-07-05T04:13:12.198053+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2201.05159","created_at":"2026-07-05T04:13:12.198053+00:00"},{"alias_kind":"pith_short_12","alias_value":"NEFGZ5HUY4Q2","created_at":"2026-07-05T04:13:12.198053+00:00"},{"alias_kind":"pith_short_16","alias_value":"NEFGZ5HUY4Q2O46Y","created_at":"2026-07-05T04:13:12.198053+00:00"},{"alias_kind":"pith_short_8","alias_value":"NEFGZ5HU","created_at":"2026-07-05T04:13:12.198053+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2306.12001","citing_title":"An Overview of Catastrophic AI Risks","ref_index":29,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/NEFGZ5HUY4Q2O46YKJKI3PHBCK","json":"https://pith.science/pith/NEFGZ5HUY4Q2O46YKJKI3PHBCK.json","graph_json":"https://pith.science/api/pith-number/NEFGZ5HUY4Q2O46YKJKI3PHBCK/graph.json","events_json":"https://pith.science/api/pith-number/NEFGZ5HUY4Q2O46YKJKI3PHBCK/events.json","paper":"https://pith.science/paper/NEFGZ5HU"},"agent_actions":{"view_html":"https://pith.science/pith/NEFGZ5HUY4Q2O46YKJKI3PHBCK","download_json":"https://pith.science/pith/NEFGZ5HUY4Q2O46YKJKI3PHBCK.json","view_paper":"https://pith.science/paper/NEFGZ5HU","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2201.05159&json=true","fetch_graph":"https://pith.science/api/pith-number/NEFGZ5HUY4Q2O46YKJKI3PHBCK/graph.json","fetch_events":"https://pith.science/api/pith-number/NEFGZ5HUY4Q2O46YKJKI3PHBCK/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/NEFGZ5HUY4Q2O46YKJKI3PHBCK/action/timestamp_anchor","attest_storage":"https://pith.science/pith/NEFGZ5HUY4Q2O46YKJKI3PHBCK/action/storage_attestation","attest_author":"https://pith.science/pith/NEFGZ5HUY4Q2O46YKJKI3PHBCK/action/author_attestation","sign_citation":"https://pith.science/pith/NEFGZ5HUY4Q2O46YKJKI3PHBCK/action/citation_signature","submit_replication":"https://pith.science/pith/NEFGZ5HUY4Q2O46YKJKI3PHBCK/action/replication_record"}},"created_at":"2026-07-05T04:13:12.198053+00:00","updated_at":"2026-07-05T04:13:12.198053+00:00"}