{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:SQ7EVAIB4K3MSSCIW2BS2BYEAI","short_pith_number":"pith:SQ7EVAIB","schema_version":"1.0","canonical_sha256":"943e4a8101e2b6c94848b6832d0704023920cc5e3a9814aff8b2480349c051f1","source":{"kind":"arxiv","id":"2111.09478","version":1},"attestation_state":"computed","paper":{"title":"Software Engineering for Responsible AI: An Empirical Study and Operationalised Patterns","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SE"],"primary_cat":"cs.AI","authors_text":"Conrad Sanderson, David Douglas, Jon Whittle, Liming Zhu, Qinghua Lu, Xiwei Xu","submitted_at":"2021-11-18T02:18:27Z","abstract_excerpt":"Although artificial intelligence (AI) is solving real-world challenges and transforming industries, there are serious concerns about its ability to behave and make decisions in a responsible way. Many AI ethics principles and guidelines for responsible AI have been recently issued by governments, organisations, and enterprises. However, these AI ethics principles and guidelines are typically high-level and do not provide concrete guidance on how to design and develop responsible AI systems. To address this shortcoming, we first present an empirical study where we interviewed 21 scientists and "},"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":"2111.09478","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2021-11-18T02:18:27Z","cross_cats_sorted":["cs.SE"],"title_canon_sha256":"6d25b34260b66e05e55503c1ab92a1e70142dff0154e13768a685ed0394d70bb","abstract_canon_sha256":"c22cc674691ea8f196510585501e8c3ce9ecf4f38c9c0a8bdd384871b2983b69"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:42:15.250883Z","signature_b64":"g+Q8Xx+Aisl8zjYwKn7MzJCWxVcNpVLylEeHQytdPGQH6MnyeQju176uO5AWJDJfoPYusQh25HxSH5+aRwqoAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"943e4a8101e2b6c94848b6832d0704023920cc5e3a9814aff8b2480349c051f1","last_reissued_at":"2026-07-05T04:42:15.250378Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:42:15.250378Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Software Engineering for Responsible AI: An Empirical Study and Operationalised Patterns","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SE"],"primary_cat":"cs.AI","authors_text":"Conrad Sanderson, David Douglas, Jon Whittle, Liming Zhu, Qinghua Lu, Xiwei Xu","submitted_at":"2021-11-18T02:18:27Z","abstract_excerpt":"Although artificial intelligence (AI) is solving real-world challenges and transforming industries, there are serious concerns about its ability to behave and make decisions in a responsible way. Many AI ethics principles and guidelines for responsible AI have been recently issued by governments, organisations, and enterprises. However, these AI ethics principles and guidelines are typically high-level and do not provide concrete guidance on how to design and develop responsible AI systems. To address this shortcoming, we first present an empirical study where we interviewed 21 scientists and "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2111.09478","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/2111.09478/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":"2111.09478","created_at":"2026-07-05T04:42:15.250439+00:00"},{"alias_kind":"arxiv_version","alias_value":"2111.09478v1","created_at":"2026-07-05T04:42:15.250439+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2111.09478","created_at":"2026-07-05T04:42:15.250439+00:00"},{"alias_kind":"pith_short_12","alias_value":"SQ7EVAIB4K3M","created_at":"2026-07-05T04:42:15.250439+00:00"},{"alias_kind":"pith_short_16","alias_value":"SQ7EVAIB4K3MSSCI","created_at":"2026-07-05T04:42:15.250439+00:00"},{"alias_kind":"pith_short_8","alias_value":"SQ7EVAIB","created_at":"2026-07-05T04:42:15.250439+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/SQ7EVAIB4K3MSSCIW2BS2BYEAI","json":"https://pith.science/pith/SQ7EVAIB4K3MSSCIW2BS2BYEAI.json","graph_json":"https://pith.science/api/pith-number/SQ7EVAIB4K3MSSCIW2BS2BYEAI/graph.json","events_json":"https://pith.science/api/pith-number/SQ7EVAIB4K3MSSCIW2BS2BYEAI/events.json","paper":"https://pith.science/paper/SQ7EVAIB"},"agent_actions":{"view_html":"https://pith.science/pith/SQ7EVAIB4K3MSSCIW2BS2BYEAI","download_json":"https://pith.science/pith/SQ7EVAIB4K3MSSCIW2BS2BYEAI.json","view_paper":"https://pith.science/paper/SQ7EVAIB","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2111.09478&json=true","fetch_graph":"https://pith.science/api/pith-number/SQ7EVAIB4K3MSSCIW2BS2BYEAI/graph.json","fetch_events":"https://pith.science/api/pith-number/SQ7EVAIB4K3MSSCIW2BS2BYEAI/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/SQ7EVAIB4K3MSSCIW2BS2BYEAI/action/timestamp_anchor","attest_storage":"https://pith.science/pith/SQ7EVAIB4K3MSSCIW2BS2BYEAI/action/storage_attestation","attest_author":"https://pith.science/pith/SQ7EVAIB4K3MSSCIW2BS2BYEAI/action/author_attestation","sign_citation":"https://pith.science/pith/SQ7EVAIB4K3MSSCIW2BS2BYEAI/action/citation_signature","submit_replication":"https://pith.science/pith/SQ7EVAIB4K3MSSCIW2BS2BYEAI/action/replication_record"}},"created_at":"2026-07-05T04:42:15.250439+00:00","updated_at":"2026-07-05T04:42:15.250439+00:00"}