{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:TUX4M5AXWRLQ444G7FS6ZKJ2MH","short_pith_number":"pith:TUX4M5AX","schema_version":"1.0","canonical_sha256":"9d2fc67417b4570e7386f965eca93a61c64fca2a8ac39328e3a0fc09a2d2e268","source":{"kind":"arxiv","id":"2506.18133","version":1},"attestation_state":"computed","paper":{"title":"Aggregated Individual Reporting for Post-Deployment Evaluation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CY","authors_text":"Benjamin Recht, Inioluwa Deborah Raji, Irene Y. Chen, Jessica Dai","submitted_at":"2025-06-22T18:36:13Z","abstract_excerpt":"The need for developing model evaluations beyond static benchmarking, especially in the post-deployment phase, is now well-understood. At the same time, concerns about the concentration of power in deployed AI systems have sparked a keen interest in 'democratic' or 'public' AI. In this work, we bring these two ideas together by proposing mechanisms for aggregated individual reporting (AIR), a framework for post-deployment evaluation that relies on individual reports from the public. An AIR mechanism allows those who interact with a specific, deployed (AI) system to report when they feel that t"},"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":"2506.18133","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CY","submitted_at":"2025-06-22T18:36:13Z","cross_cats_sorted":[],"title_canon_sha256":"9edecfca40b1bd213243b0e3e6a182720b2bc709187b49566fc9f69c89b19dd7","abstract_canon_sha256":"4bc79b8a62a57014c4a58b385031df4d6d3b50508b5ab85b3302cd1455bb687d"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:25:29.379158Z","signature_b64":"mT3BwZsoD3xAdnmsg3C9Djng2yOPNnrvZqnc8CN7JRvjCO5UT+e8amtDXX92la/E2Cdm6FO55K0B95BrevG4Bg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9d2fc67417b4570e7386f965eca93a61c64fca2a8ac39328e3a0fc09a2d2e268","last_reissued_at":"2026-07-05T11:25:29.378705Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:25:29.378705Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Aggregated Individual Reporting for Post-Deployment Evaluation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CY","authors_text":"Benjamin Recht, Inioluwa Deborah Raji, Irene Y. Chen, Jessica Dai","submitted_at":"2025-06-22T18:36:13Z","abstract_excerpt":"The need for developing model evaluations beyond static benchmarking, especially in the post-deployment phase, is now well-understood. At the same time, concerns about the concentration of power in deployed AI systems have sparked a keen interest in 'democratic' or 'public' AI. In this work, we bring these two ideas together by proposing mechanisms for aggregated individual reporting (AIR), a framework for post-deployment evaluation that relies on individual reports from the public. An AIR mechanism allows those who interact with a specific, deployed (AI) system to report when they feel that t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.18133","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/2506.18133/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":"2506.18133","created_at":"2026-07-05T11:25:29.378764+00:00"},{"alias_kind":"arxiv_version","alias_value":"2506.18133v1","created_at":"2026-07-05T11:25:29.378764+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.18133","created_at":"2026-07-05T11:25:29.378764+00:00"},{"alias_kind":"pith_short_12","alias_value":"TUX4M5AXWRLQ","created_at":"2026-07-05T11:25:29.378764+00:00"},{"alias_kind":"pith_short_16","alias_value":"TUX4M5AXWRLQ444G","created_at":"2026-07-05T11:25:29.378764+00:00"},{"alias_kind":"pith_short_8","alias_value":"TUX4M5AX","created_at":"2026-07-05T11:25:29.378764+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2606.05750","citing_title":"Three Years of r/ChatGPT: Societal Impact Evaluations from Social Media Data","ref_index":4,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/TUX4M5AXWRLQ444G7FS6ZKJ2MH","json":"https://pith.science/pith/TUX4M5AXWRLQ444G7FS6ZKJ2MH.json","graph_json":"https://pith.science/api/pith-number/TUX4M5AXWRLQ444G7FS6ZKJ2MH/graph.json","events_json":"https://pith.science/api/pith-number/TUX4M5AXWRLQ444G7FS6ZKJ2MH/events.json","paper":"https://pith.science/paper/TUX4M5AX"},"agent_actions":{"view_html":"https://pith.science/pith/TUX4M5AXWRLQ444G7FS6ZKJ2MH","download_json":"https://pith.science/pith/TUX4M5AXWRLQ444G7FS6ZKJ2MH.json","view_paper":"https://pith.science/paper/TUX4M5AX","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2506.18133&json=true","fetch_graph":"https://pith.science/api/pith-number/TUX4M5AXWRLQ444G7FS6ZKJ2MH/graph.json","fetch_events":"https://pith.science/api/pith-number/TUX4M5AXWRLQ444G7FS6ZKJ2MH/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/TUX4M5AXWRLQ444G7FS6ZKJ2MH/action/timestamp_anchor","attest_storage":"https://pith.science/pith/TUX4M5AXWRLQ444G7FS6ZKJ2MH/action/storage_attestation","attest_author":"https://pith.science/pith/TUX4M5AXWRLQ444G7FS6ZKJ2MH/action/author_attestation","sign_citation":"https://pith.science/pith/TUX4M5AXWRLQ444G7FS6ZKJ2MH/action/citation_signature","submit_replication":"https://pith.science/pith/TUX4M5AXWRLQ444G7FS6ZKJ2MH/action/replication_record"}},"created_at":"2026-07-05T11:25:29.378764+00:00","updated_at":"2026-07-05T11:25:29.378764+00:00"}