{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:QBGOEAP4FR7KPSNHML4IIKBTFF","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"2463a691234a1eaedfa3188b61e0820e53fc7ffe52096275211ca1e4ba935d36","cross_cats_sorted":["cs.AI","cs.CY"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.HC","submitted_at":"2021-12-02T07:02:27Z","title_canon_sha256":"6273ef46446050f419cb2183914de9081d6d71a21a1f44deb29b58a1bfd22b0e"},"schema_version":"1.0","source":{"id":"2112.01016","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2112.01016","created_at":"2026-07-05T03:37:02Z"},{"alias_kind":"arxiv_version","alias_value":"2112.01016v1","created_at":"2026-07-05T03:37:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2112.01016","created_at":"2026-07-05T03:37:02Z"},{"alias_kind":"pith_short_12","alias_value":"QBGOEAP4FR7K","created_at":"2026-07-05T03:37:02Z"},{"alias_kind":"pith_short_16","alias_value":"QBGOEAP4FR7KPSNH","created_at":"2026-07-05T03:37:02Z"},{"alias_kind":"pith_short_8","alias_value":"QBGOEAP4","created_at":"2026-07-05T03:37:02Z"}],"graph_snapshots":[{"event_id":"sha256:48408c67188ad69818c11a95ae9db1f5ec9c0767921afc07694d6af04aeb0192","target":"graph","created_at":"2026-07-05T03:37:02Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2112.01016/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Explainable AI (XAI) research has been booming, but the question \"$\\textbf{To whom}$ are we making AI explainable?\" is yet to gain sufficient attention. Not much of XAI is comprehensible to non-AI experts, who nonetheless, are the primary audience and major stakeholders of deployed AI systems in practice. The gap is glaring: what is considered \"explained\" to AI-experts versus non-experts are very different in practical scenarios. Hence, this gap produced two distinct cultures of expectations, goals, and forms of XAI in real-life AI deployments.\n  We advocate that it is critical to develop XAI ","authors_text":"Erwen Senge, Helen Jiang","cross_cats":["cs.AI","cs.CY"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.HC","submitted_at":"2021-12-02T07:02:27Z","title":"On Two XAI Cultures: A Case Study of Non-technical Explanations in Deployed AI System"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2112.01016","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:d1926ddb07529f85adacc6831ee966592c2acf987381ffe3e78fc628a91e1e48","target":"record","created_at":"2026-07-05T03:37:02Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"2463a691234a1eaedfa3188b61e0820e53fc7ffe52096275211ca1e4ba935d36","cross_cats_sorted":["cs.AI","cs.CY"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.HC","submitted_at":"2021-12-02T07:02:27Z","title_canon_sha256":"6273ef46446050f419cb2183914de9081d6d71a21a1f44deb29b58a1bfd22b0e"},"schema_version":"1.0","source":{"id":"2112.01016","kind":"arxiv","version":1}},"canonical_sha256":"804ce201fc2c7ea7c9a762f8842833294abd73b4779b07702c13043478364827","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"804ce201fc2c7ea7c9a762f8842833294abd73b4779b07702c13043478364827","first_computed_at":"2026-07-05T03:37:02.637757Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:37:02.637757Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"nTk3/HiwZ2IUYb9UHNiZcGUrueQLLsgvGoixyY7o6m3qySb9JiP54d+NH6qrRnXt5PyJZE6yNB9yDeYBmVKwDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T03:37:02.638257Z","signed_message":"canonical_sha256_bytes"},"source_id":"2112.01016","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d1926ddb07529f85adacc6831ee966592c2acf987381ffe3e78fc628a91e1e48","sha256:48408c67188ad69818c11a95ae9db1f5ec9c0767921afc07694d6af04aeb0192"],"state_sha256":"b6b34914926bd38f4978d45f62139613fdded6e242b261c874c2ce5ee5e947e5"}