{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:YHY5UAYMRPCNVJZW2HFSL4LZPE","short_pith_number":"pith:YHY5UAYM","schema_version":"1.0","canonical_sha256":"c1f1da030c8bc4daa736d1cb25f179792fe15d2e19cc5b9302bee9414ade81aa","source":{"kind":"arxiv","id":"1907.01671","version":1},"attestation_state":"computed","paper":{"title":"Quantifying Algorithmic Biases over Time","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CY","authors_text":"Ishaan Singh, Vivek K. Singh","submitted_at":"2019-07-02T22:44:12Z","abstract_excerpt":"Algorithms now permeate multiple aspects of human lives and multiple recent results have reported that these algorithms may have biases pertaining to gender, race, and other demographic characteristics. The metrics used to quantify such biases have still focused on a static notion of algorithms. However, algorithms evolve over time. For instance, Tay (a conversational bot launched by Microsoft) was arguably not biased at its launch but quickly became biased, sexist, and racist over time. We suggest a set of intuitive metrics to study the variations in biases over time and present the results f"},"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":"1907.01671","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CY","submitted_at":"2019-07-02T22:44:12Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"7f7f22e14bee34a5ea15e97d355104fa70395b379c6e61c468bf41abf20f7213","abstract_canon_sha256":"920f171c9b5f252ccf22e1a312ff0356e3e29f4f69b9277dd765a57418086403"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:41:35.539248Z","signature_b64":"0kQ+aXR+xFs6ljPIfrhECoQgLgBAGbmOMZaiBD7T1zvy4ekzku09v6ShtFtb1kk6hjOzLWdu7dScIOglf329Aw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c1f1da030c8bc4daa736d1cb25f179792fe15d2e19cc5b9302bee9414ade81aa","last_reissued_at":"2026-05-17T23:41:35.538745Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:41:35.538745Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Quantifying Algorithmic Biases over Time","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CY","authors_text":"Ishaan Singh, Vivek K. Singh","submitted_at":"2019-07-02T22:44:12Z","abstract_excerpt":"Algorithms now permeate multiple aspects of human lives and multiple recent results have reported that these algorithms may have biases pertaining to gender, race, and other demographic characteristics. The metrics used to quantify such biases have still focused on a static notion of algorithms. However, algorithms evolve over time. For instance, Tay (a conversational bot launched by Microsoft) was arguably not biased at its launch but quickly became biased, sexist, and racist over time. We suggest a set of intuitive metrics to study the variations in biases over time and present the results f"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.01671","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":""},"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":"1907.01671","created_at":"2026-05-17T23:41:35.538803+00:00"},{"alias_kind":"arxiv_version","alias_value":"1907.01671v1","created_at":"2026-05-17T23:41:35.538803+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.01671","created_at":"2026-05-17T23:41:35.538803+00:00"},{"alias_kind":"pith_short_12","alias_value":"YHY5UAYMRPCN","created_at":"2026-05-18T12:33:33.725879+00:00"},{"alias_kind":"pith_short_16","alias_value":"YHY5UAYMRPCNVJZW","created_at":"2026-05-18T12:33:33.725879+00:00"},{"alias_kind":"pith_short_8","alias_value":"YHY5UAYM","created_at":"2026-05-18T12:33:33.725879+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/YHY5UAYMRPCNVJZW2HFSL4LZPE","json":"https://pith.science/pith/YHY5UAYMRPCNVJZW2HFSL4LZPE.json","graph_json":"https://pith.science/api/pith-number/YHY5UAYMRPCNVJZW2HFSL4LZPE/graph.json","events_json":"https://pith.science/api/pith-number/YHY5UAYMRPCNVJZW2HFSL4LZPE/events.json","paper":"https://pith.science/paper/YHY5UAYM"},"agent_actions":{"view_html":"https://pith.science/pith/YHY5UAYMRPCNVJZW2HFSL4LZPE","download_json":"https://pith.science/pith/YHY5UAYMRPCNVJZW2HFSL4LZPE.json","view_paper":"https://pith.science/paper/YHY5UAYM","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1907.01671&json=true","fetch_graph":"https://pith.science/api/pith-number/YHY5UAYMRPCNVJZW2HFSL4LZPE/graph.json","fetch_events":"https://pith.science/api/pith-number/YHY5UAYMRPCNVJZW2HFSL4LZPE/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/YHY5UAYMRPCNVJZW2HFSL4LZPE/action/timestamp_anchor","attest_storage":"https://pith.science/pith/YHY5UAYMRPCNVJZW2HFSL4LZPE/action/storage_attestation","attest_author":"https://pith.science/pith/YHY5UAYMRPCNVJZW2HFSL4LZPE/action/author_attestation","sign_citation":"https://pith.science/pith/YHY5UAYMRPCNVJZW2HFSL4LZPE/action/citation_signature","submit_replication":"https://pith.science/pith/YHY5UAYMRPCNVJZW2HFSL4LZPE/action/replication_record"}},"created_at":"2026-05-17T23:41:35.538803+00:00","updated_at":"2026-05-17T23:41:35.538803+00:00"}