{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:PVQQJFE3F6BNJWKMW3VCGIQBNF","short_pith_number":"pith:PVQQJFE3","schema_version":"1.0","canonical_sha256":"7d6104949b2f82d4d94cb6ea2322016943fb8d4c0f4dd672c86c675ac22bd7d9","source":{"kind":"arxiv","id":"2502.03467","version":1},"attestation_state":"computed","paper":{"title":"Where AI Assurance Might Go Wrong: Initial lessons from engineering of critical systems","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI","cs.SE"],"primary_cat":"cs.CY","authors_text":"John Rushby, Robin Bloomfield","submitted_at":"2025-01-07T22:02:23Z","abstract_excerpt":"We draw on our experience working on system and software assurance and evaluation for systems important to society to summarise how safety engineering is performed in traditional critical systems, such as aircraft flight control. We analyse how this critical systems perspective might support the development and implementation of AI Safety Frameworks. We present the analysis in terms of: system engineering, safety and risk analysis, and decision analysis and support.\n  We consider four key questions: What is the system? How good does it have to be? What is the impact of criticality on system de"},"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":"2502.03467","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CY","submitted_at":"2025-01-07T22:02:23Z","cross_cats_sorted":["cs.AI","cs.SE"],"title_canon_sha256":"3a5f7b8d7f1b4bbc0b8e39f244733103ddb035eddd46ba1b6f265acd788337b7","abstract_canon_sha256":"afd128ec8d24b253132b35186bb5e9d6da57ebef32828c57251b717c6a58b9bf"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:10:10.792308Z","signature_b64":"CsVDQg3n26uLZNrkKPRy59uBkZJVhGoRKiBYE72WVk0bU0rkF3NyCfKqK81gjUFz/INIu5CRx8qFgIA0W9QRBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7d6104949b2f82d4d94cb6ea2322016943fb8d4c0f4dd672c86c675ac22bd7d9","last_reissued_at":"2026-07-05T10:10:10.791901Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:10:10.791901Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Where AI Assurance Might Go Wrong: Initial lessons from engineering of critical systems","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI","cs.SE"],"primary_cat":"cs.CY","authors_text":"John Rushby, Robin Bloomfield","submitted_at":"2025-01-07T22:02:23Z","abstract_excerpt":"We draw on our experience working on system and software assurance and evaluation for systems important to society to summarise how safety engineering is performed in traditional critical systems, such as aircraft flight control. We analyse how this critical systems perspective might support the development and implementation of AI Safety Frameworks. We present the analysis in terms of: system engineering, safety and risk analysis, and decision analysis and support.\n  We consider four key questions: What is the system? How good does it have to be? What is the impact of criticality on system de"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.03467","kind":"arxiv","version":1},"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/2502.03467/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":"2502.03467","created_at":"2026-07-05T10:10:10.791956+00:00"},{"alias_kind":"arxiv_version","alias_value":"2502.03467v1","created_at":"2026-07-05T10:10:10.791956+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.03467","created_at":"2026-07-05T10:10:10.791956+00:00"},{"alias_kind":"pith_short_12","alias_value":"PVQQJFE3F6BN","created_at":"2026-07-05T10:10:10.791956+00:00"},{"alias_kind":"pith_short_16","alias_value":"PVQQJFE3F6BNJWKM","created_at":"2026-07-05T10:10:10.791956+00:00"},{"alias_kind":"pith_short_8","alias_value":"PVQQJFE3","created_at":"2026-07-05T10:10:10.791956+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":2,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2605.13069","citing_title":"Not All Anquan Is the Same: A Terminological Proposal for Chinese Computer Science and Engineering","ref_index":43,"is_internal_anchor":false},{"citing_arxiv_id":"2605.13069","citing_title":"Not All Anquan Is the Same: A Terminological Proposal for Chinese Computer Science and Engineering","ref_index":43,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/PVQQJFE3F6BNJWKMW3VCGIQBNF","json":"https://pith.science/pith/PVQQJFE3F6BNJWKMW3VCGIQBNF.json","graph_json":"https://pith.science/api/pith-number/PVQQJFE3F6BNJWKMW3VCGIQBNF/graph.json","events_json":"https://pith.science/api/pith-number/PVQQJFE3F6BNJWKMW3VCGIQBNF/events.json","paper":"https://pith.science/paper/PVQQJFE3"},"agent_actions":{"view_html":"https://pith.science/pith/PVQQJFE3F6BNJWKMW3VCGIQBNF","download_json":"https://pith.science/pith/PVQQJFE3F6BNJWKMW3VCGIQBNF.json","view_paper":"https://pith.science/paper/PVQQJFE3","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2502.03467&json=true","fetch_graph":"https://pith.science/api/pith-number/PVQQJFE3F6BNJWKMW3VCGIQBNF/graph.json","fetch_events":"https://pith.science/api/pith-number/PVQQJFE3F6BNJWKMW3VCGIQBNF/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/PVQQJFE3F6BNJWKMW3VCGIQBNF/action/timestamp_anchor","attest_storage":"https://pith.science/pith/PVQQJFE3F6BNJWKMW3VCGIQBNF/action/storage_attestation","attest_author":"https://pith.science/pith/PVQQJFE3F6BNJWKMW3VCGIQBNF/action/author_attestation","sign_citation":"https://pith.science/pith/PVQQJFE3F6BNJWKMW3VCGIQBNF/action/citation_signature","submit_replication":"https://pith.science/pith/PVQQJFE3F6BNJWKMW3VCGIQBNF/action/replication_record"}},"created_at":"2026-07-05T10:10:10.791956+00:00","updated_at":"2026-07-05T10:10:10.791956+00:00"}