{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:DJAKLGPL2HI3TCMJWJHQNWEGEY","short_pith_number":"pith:DJAKLGPL","schema_version":"1.0","canonical_sha256":"1a40a599ebd1d1b98989b24f06d886260903043d39b2ce2d0c2ddcf55cf13c20","source":{"kind":"arxiv","id":"2507.11548","version":2},"attestation_state":"computed","paper":{"title":"Fairness Is Not Enough: Auditing Competence and Intersectional Bias in AI-powered Resume Screening","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.CL"],"primary_cat":"cs.CY","authors_text":"Kevin T Webster","submitted_at":"2025-07-11T16:57:13Z","abstract_excerpt":"The increasing use of generative AI for resume screening is predicated on the assumption that it offers an unbiased alternative to biased human decision-making. However, this belief fails to address a critical question: are these AI systems fundamentally competent at the evaluative tasks they are meant to perform?\n  This study investigates the question of competence through a two-part audit of eight major AI platforms. Experiment 1 confirmed complex, contextual racial and gender biases, with some models penalizing candidates merely for the presence of demographic signals. Experiment 2, which e"},"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":"2507.11548","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CY","submitted_at":"2025-07-11T16:57:13Z","cross_cats_sorted":["cs.AI","cs.CL"],"title_canon_sha256":"5645aa9791011049167c5f23c3816f7241396aff3777b43dca46f493cb5203e5","abstract_canon_sha256":"f7b3d7ba0d05f6f08a7f9df18754f3cc19dedd048607d862472be6b46f9b91ff"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:38:31.967010Z","signature_b64":"EgxX4BV4s/AirTBHZMqAZuR8da+s/lE/1YKuaPw2rQkeK99rRxYrNUgkBcerNEQu+rAQxdZ8R0XnjjTCUmHmCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1a40a599ebd1d1b98989b24f06d886260903043d39b2ce2d0c2ddcf55cf13c20","last_reissued_at":"2026-07-05T11:38:31.966555Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:38:31.966555Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Fairness Is Not Enough: Auditing Competence and Intersectional Bias in AI-powered Resume Screening","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.CL"],"primary_cat":"cs.CY","authors_text":"Kevin T Webster","submitted_at":"2025-07-11T16:57:13Z","abstract_excerpt":"The increasing use of generative AI for resume screening is predicated on the assumption that it offers an unbiased alternative to biased human decision-making. However, this belief fails to address a critical question: are these AI systems fundamentally competent at the evaluative tasks they are meant to perform?\n  This study investigates the question of competence through a two-part audit of eight major AI platforms. Experiment 1 confirmed complex, contextual racial and gender biases, with some models penalizing candidates merely for the presence of demographic signals. Experiment 2, which e"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.11548","kind":"arxiv","version":2},"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/2507.11548/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":"2507.11548","created_at":"2026-07-05T11:38:31.966614+00:00"},{"alias_kind":"arxiv_version","alias_value":"2507.11548v2","created_at":"2026-07-05T11:38:31.966614+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.11548","created_at":"2026-07-05T11:38:31.966614+00:00"},{"alias_kind":"pith_short_12","alias_value":"DJAKLGPL2HI3","created_at":"2026-07-05T11:38:31.966614+00:00"},{"alias_kind":"pith_short_16","alias_value":"DJAKLGPL2HI3TCMJ","created_at":"2026-07-05T11:38:31.966614+00:00"},{"alias_kind":"pith_short_8","alias_value":"DJAKLGPL","created_at":"2026-07-05T11:38:31.966614+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/DJAKLGPL2HI3TCMJWJHQNWEGEY","json":"https://pith.science/pith/DJAKLGPL2HI3TCMJWJHQNWEGEY.json","graph_json":"https://pith.science/api/pith-number/DJAKLGPL2HI3TCMJWJHQNWEGEY/graph.json","events_json":"https://pith.science/api/pith-number/DJAKLGPL2HI3TCMJWJHQNWEGEY/events.json","paper":"https://pith.science/paper/DJAKLGPL"},"agent_actions":{"view_html":"https://pith.science/pith/DJAKLGPL2HI3TCMJWJHQNWEGEY","download_json":"https://pith.science/pith/DJAKLGPL2HI3TCMJWJHQNWEGEY.json","view_paper":"https://pith.science/paper/DJAKLGPL","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2507.11548&json=true","fetch_graph":"https://pith.science/api/pith-number/DJAKLGPL2HI3TCMJWJHQNWEGEY/graph.json","fetch_events":"https://pith.science/api/pith-number/DJAKLGPL2HI3TCMJWJHQNWEGEY/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/DJAKLGPL2HI3TCMJWJHQNWEGEY/action/timestamp_anchor","attest_storage":"https://pith.science/pith/DJAKLGPL2HI3TCMJWJHQNWEGEY/action/storage_attestation","attest_author":"https://pith.science/pith/DJAKLGPL2HI3TCMJWJHQNWEGEY/action/author_attestation","sign_citation":"https://pith.science/pith/DJAKLGPL2HI3TCMJWJHQNWEGEY/action/citation_signature","submit_replication":"https://pith.science/pith/DJAKLGPL2HI3TCMJWJHQNWEGEY/action/replication_record"}},"created_at":"2026-07-05T11:38:31.966614+00:00","updated_at":"2026-07-05T11:38:31.966614+00:00"}