{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:4IVR4FHNQ3J24A2QI2I5FECQXO","short_pith_number":"pith:4IVR4FHN","canonical_record":{"source":{"id":"2406.03292","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-06-05T14:00:46Z","cross_cats_sorted":[],"title_canon_sha256":"3e33c75278da6e1e7b47bc88e5f1febd931f354ce5d6bdd8d5d753f8f2edee98","abstract_canon_sha256":"0e6d5e348ae2e583f000e5deb45f498c6092340eec8859fc7d381d5d5c7e102e"},"schema_version":"1.0"},"canonical_sha256":"e22b1e14ed86d3ae03504691d29050bb8f6ec9aebd6ce4deeb2162a935d1754b","source":{"kind":"arxiv","id":"2406.03292","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.03292","created_at":"2026-07-05T08:27:54Z"},{"alias_kind":"arxiv_version","alias_value":"2406.03292v1","created_at":"2026-07-05T08:27:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.03292","created_at":"2026-07-05T08:27:54Z"},{"alias_kind":"pith_short_12","alias_value":"4IVR4FHNQ3J2","created_at":"2026-07-05T08:27:54Z"},{"alias_kind":"pith_short_16","alias_value":"4IVR4FHNQ3J24A2Q","created_at":"2026-07-05T08:27:54Z"},{"alias_kind":"pith_short_8","alias_value":"4IVR4FHN","created_at":"2026-07-05T08:27:54Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:4IVR4FHNQ3J24A2QI2I5FECQXO","target":"record","payload":{"canonical_record":{"source":{"id":"2406.03292","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-06-05T14:00:46Z","cross_cats_sorted":[],"title_canon_sha256":"3e33c75278da6e1e7b47bc88e5f1febd931f354ce5d6bdd8d5d753f8f2edee98","abstract_canon_sha256":"0e6d5e348ae2e583f000e5deb45f498c6092340eec8859fc7d381d5d5c7e102e"},"schema_version":"1.0"},"canonical_sha256":"e22b1e14ed86d3ae03504691d29050bb8f6ec9aebd6ce4deeb2162a935d1754b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:27:54.581372Z","signature_b64":"S9UgpJMwPB4y7tghh8CuGIxJpJgHqlYsJz6e7hY1jnbM3dGKVNHvcaBUojYErTBzMdLOuE2zaH63RzUa85FRBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e22b1e14ed86d3ae03504691d29050bb8f6ec9aebd6ce4deeb2162a935d1754b","last_reissued_at":"2026-07-05T08:27:54.580852Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:27:54.580852Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2406.03292","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:27:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"J1tq1MBKu73LzojaTXmxHjnE6nsDm/Xxy3bhU1t6Ri7pfdu79NAtz1jBk+Ri6mUFCsvsmTeMIQRKZLymur8QDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T07:53:56.983142Z"},"content_sha256":"a87123b2ef5ae04d18b7b5bf010425484e6e76d1e8cecccc510692ddbac7530e","schema_version":"1.0","event_id":"sha256:a87123b2ef5ae04d18b7b5bf010425484e6e76d1e8cecccc510692ddbac7530e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:4IVR4FHNQ3J24A2QI2I5FECQXO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Evaluating AI fairness in credit scoring with the BRIO tool","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Davide Posillipo, Enrico Bagli, Francesco A. Genco, Giuseppe Primiero, Greta Coraglia, Pellegrino Piantadosi, Pietro Giuffrida","submitted_at":"2024-06-05T14:00:46Z","abstract_excerpt":"We present a method for quantitative, in-depth analyses of fairness issues in AI systems with an application to credit scoring. To this aim we use BRIO, a tool for the evaluation of AI systems with respect to social unfairness and, more in general, ethically undesirable behaviours. It features a model-agnostic bias detection module, presented in \\cite{DBLP:conf/beware/CoragliaDGGPPQ23}, to which a full-fledged unfairness risk evaluation module is added. As a case study, we focus on the context of credit scoring, analysing the UCI German Credit Dataset \\cite{misc_statlog_(german_credit_data)_14"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.03292","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/2406.03292/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:27:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"d89rqouks8cVc1+d8PaU1oX125kQW29f1uX9IDrXT6kUCtegNhMgONTXOPlkbv5LgggeY2CcFeL/b/xDb3v3Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T07:53:56.983654Z"},"content_sha256":"271d20db5c85bbeccdc6519c57077ef0146dbabea318c1c0fbbf168a998be119","schema_version":"1.0","event_id":"sha256:271d20db5c85bbeccdc6519c57077ef0146dbabea318c1c0fbbf168a998be119"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4IVR4FHNQ3J24A2QI2I5FECQXO/bundle.json","state_url":"https://pith.science/pith/4IVR4FHNQ3J24A2QI2I5FECQXO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4IVR4FHNQ3J24A2QI2I5FECQXO/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-09T07:53:56Z","links":{"resolver":"https://pith.science/pith/4IVR4FHNQ3J24A2QI2I5FECQXO","bundle":"https://pith.science/pith/4IVR4FHNQ3J24A2QI2I5FECQXO/bundle.json","state":"https://pith.science/pith/4IVR4FHNQ3J24A2QI2I5FECQXO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4IVR4FHNQ3J24A2QI2I5FECQXO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:4IVR4FHNQ3J24A2QI2I5FECQXO","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":"0e6d5e348ae2e583f000e5deb45f498c6092340eec8859fc7d381d5d5c7e102e","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-06-05T14:00:46Z","title_canon_sha256":"3e33c75278da6e1e7b47bc88e5f1febd931f354ce5d6bdd8d5d753f8f2edee98"},"schema_version":"1.0","source":{"id":"2406.03292","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.03292","created_at":"2026-07-05T08:27:54Z"},{"alias_kind":"arxiv_version","alias_value":"2406.03292v1","created_at":"2026-07-05T08:27:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.03292","created_at":"2026-07-05T08:27:54Z"},{"alias_kind":"pith_short_12","alias_value":"4IVR4FHNQ3J2","created_at":"2026-07-05T08:27:54Z"},{"alias_kind":"pith_short_16","alias_value":"4IVR4FHNQ3J24A2Q","created_at":"2026-07-05T08:27:54Z"},{"alias_kind":"pith_short_8","alias_value":"4IVR4FHN","created_at":"2026-07-05T08:27:54Z"}],"graph_snapshots":[{"event_id":"sha256:271d20db5c85bbeccdc6519c57077ef0146dbabea318c1c0fbbf168a998be119","target":"graph","created_at":"2026-07-05T08:27:54Z","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/2406.03292/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We present a method for quantitative, in-depth analyses of fairness issues in AI systems with an application to credit scoring. To this aim we use BRIO, a tool for the evaluation of AI systems with respect to social unfairness and, more in general, ethically undesirable behaviours. It features a model-agnostic bias detection module, presented in \\cite{DBLP:conf/beware/CoragliaDGGPPQ23}, to which a full-fledged unfairness risk evaluation module is added. As a case study, we focus on the context of credit scoring, analysing the UCI German Credit Dataset \\cite{misc_statlog_(german_credit_data)_14","authors_text":"Davide Posillipo, Enrico Bagli, Francesco A. Genco, Giuseppe Primiero, Greta Coraglia, Pellegrino Piantadosi, Pietro Giuffrida","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-06-05T14:00:46Z","title":"Evaluating AI fairness in credit scoring with the BRIO tool"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.03292","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:a87123b2ef5ae04d18b7b5bf010425484e6e76d1e8cecccc510692ddbac7530e","target":"record","created_at":"2026-07-05T08:27:54Z","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":"0e6d5e348ae2e583f000e5deb45f498c6092340eec8859fc7d381d5d5c7e102e","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-06-05T14:00:46Z","title_canon_sha256":"3e33c75278da6e1e7b47bc88e5f1febd931f354ce5d6bdd8d5d753f8f2edee98"},"schema_version":"1.0","source":{"id":"2406.03292","kind":"arxiv","version":1}},"canonical_sha256":"e22b1e14ed86d3ae03504691d29050bb8f6ec9aebd6ce4deeb2162a935d1754b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e22b1e14ed86d3ae03504691d29050bb8f6ec9aebd6ce4deeb2162a935d1754b","first_computed_at":"2026-07-05T08:27:54.580852Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:27:54.580852Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"S9UgpJMwPB4y7tghh8CuGIxJpJgHqlYsJz6e7hY1jnbM3dGKVNHvcaBUojYErTBzMdLOuE2zaH63RzUa85FRBA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:27:54.581372Z","signed_message":"canonical_sha256_bytes"},"source_id":"2406.03292","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a87123b2ef5ae04d18b7b5bf010425484e6e76d1e8cecccc510692ddbac7530e","sha256:271d20db5c85bbeccdc6519c57077ef0146dbabea318c1c0fbbf168a998be119"],"state_sha256":"2fd71177bf5c0539e9b2566e670ddd3fe2e554d8244e373cf310a54246e3225b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ewlquzOKs4l12HQfc0BONcFb9D3jIdVWMEECPjG10MhFrQss4ID8puqsk2XUXQadidCIkOnStkIdAkj3CdKnBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T07:53:56.987880Z","bundle_sha256":"fb1ff619b955bd53e9ba06bd94966b23795bd411ec087cf4647c1529bef3897b"}}