{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:WWBC7OWLWYQYOMWSVHN46LU4BZ","short_pith_number":"pith:WWBC7OWL","canonical_record":{"source":{"id":"1901.10002","kind":"arxiv","version":5},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-01-28T21:00:20Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"a630c3cc7508e277653e672e7262da744eeaae79733413448fa35d82d8796098","abstract_canon_sha256":"6a9cbdaed275f37d1f696cf9ef8c0a52054a1553d41fd5dee5df457c779e0056"},"schema_version":"1.0"},"canonical_sha256":"b5822fbacbb6218732d2a9dbcf2e9c0e5f2b362885b9b9d0ec1e1a43ad026bde","source":{"kind":"arxiv","id":"1901.10002","version":5},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1901.10002","created_at":"2026-07-05T03:36:50Z"},{"alias_kind":"arxiv_version","alias_value":"1901.10002v5","created_at":"2026-07-05T03:36:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1901.10002","created_at":"2026-07-05T03:36:50Z"},{"alias_kind":"pith_short_12","alias_value":"WWBC7OWLWYQY","created_at":"2026-07-05T03:36:50Z"},{"alias_kind":"pith_short_16","alias_value":"WWBC7OWLWYQYOMWS","created_at":"2026-07-05T03:36:50Z"},{"alias_kind":"pith_short_8","alias_value":"WWBC7OWL","created_at":"2026-07-05T03:36:50Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:WWBC7OWLWYQYOMWSVHN46LU4BZ","target":"record","payload":{"canonical_record":{"source":{"id":"1901.10002","kind":"arxiv","version":5},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-01-28T21:00:20Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"a630c3cc7508e277653e672e7262da744eeaae79733413448fa35d82d8796098","abstract_canon_sha256":"6a9cbdaed275f37d1f696cf9ef8c0a52054a1553d41fd5dee5df457c779e0056"},"schema_version":"1.0"},"canonical_sha256":"b5822fbacbb6218732d2a9dbcf2e9c0e5f2b362885b9b9d0ec1e1a43ad026bde","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:36:50.578500Z","signature_b64":"UQWmZJOwkx20iYlQhx4qJsbpmB1kXbMLNuVa43JM65M95NiZdJn6OScyMq5yWR8UBp6rNIdLO5YbYkV0swlADg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b5822fbacbb6218732d2a9dbcf2e9c0e5f2b362885b9b9d0ec1e1a43ad026bde","last_reissued_at":"2026-07-05T03:36:50.577973Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:36:50.577973Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1901.10002","source_version":5,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T03:36:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ePbuZjog23ACTpUbk1dl5U6aXIY1ZweeVdnScDTizuib8jYhDksv8HMfs1bda3OCvCzlKupgOjC5umaKp+9UCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T04:22:05.418639Z"},"content_sha256":"febb8278570330e4946ec51298840669efb3ee5243e3105a0fba9c0971ec1cdf","schema_version":"1.0","event_id":"sha256:febb8278570330e4946ec51298840669efb3ee5243e3105a0fba9c0971ec1cdf"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:WWBC7OWLWYQYOMWSVHN46LU4BZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Framework for Understanding Sources of Harm throughout the Machine Learning Life Cycle","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Harini Suresh, John V. Guttag","submitted_at":"2019-01-28T21:00:20Z","abstract_excerpt":"As machine learning (ML) increasingly affects people and society, awareness of its potential unwanted consequences has also grown. To anticipate, prevent, and mitigate undesirable downstream consequences, it is critical that we understand when and how harm might be introduced throughout the ML life cycle. In this paper, we provide a framework that identifies seven distinct potential sources of downstream harm in machine learning, spanning data collection, development, and deployment. In doing so, we aim to facilitate more productive and precise communication around these issues, as well as mor"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1901.10002","kind":"arxiv","version":5},"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/1901.10002/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":"2026-07-05T03:36:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"As8rJfBvKeFgS2G49g6fl6bijur7xBfEM+bh09OAb1BFunRhJ1leLqIgkk74EAmsVQyUkXDG7EaG/w656BqiDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T04:22:05.419164Z"},"content_sha256":"0a28efd3a11b9ca1c3811c17099db869a99997053f0f9d0ab394278352c7a3e3","schema_version":"1.0","event_id":"sha256:0a28efd3a11b9ca1c3811c17099db869a99997053f0f9d0ab394278352c7a3e3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WWBC7OWLWYQYOMWSVHN46LU4BZ/bundle.json","state_url":"https://pith.science/pith/WWBC7OWLWYQYOMWSVHN46LU4BZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WWBC7OWLWYQYOMWSVHN46LU4BZ/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":"2026-08-13T04:22:05Z","links":{"resolver":"https://pith.science/pith/WWBC7OWLWYQYOMWSVHN46LU4BZ","bundle":"https://pith.science/pith/WWBC7OWLWYQYOMWSVHN46LU4BZ/bundle.json","state":"https://pith.science/pith/WWBC7OWLWYQYOMWSVHN46LU4BZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WWBC7OWLWYQYOMWSVHN46LU4BZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:WWBC7OWLWYQYOMWSVHN46LU4BZ","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":"6a9cbdaed275f37d1f696cf9ef8c0a52054a1553d41fd5dee5df457c779e0056","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-01-28T21:00:20Z","title_canon_sha256":"a630c3cc7508e277653e672e7262da744eeaae79733413448fa35d82d8796098"},"schema_version":"1.0","source":{"id":"1901.10002","kind":"arxiv","version":5}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1901.10002","created_at":"2026-07-05T03:36:50Z"},{"alias_kind":"arxiv_version","alias_value":"1901.10002v5","created_at":"2026-07-05T03:36:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1901.10002","created_at":"2026-07-05T03:36:50Z"},{"alias_kind":"pith_short_12","alias_value":"WWBC7OWLWYQY","created_at":"2026-07-05T03:36:50Z"},{"alias_kind":"pith_short_16","alias_value":"WWBC7OWLWYQYOMWS","created_at":"2026-07-05T03:36:50Z"},{"alias_kind":"pith_short_8","alias_value":"WWBC7OWL","created_at":"2026-07-05T03:36:50Z"}],"graph_snapshots":[{"event_id":"sha256:0a28efd3a11b9ca1c3811c17099db869a99997053f0f9d0ab394278352c7a3e3","target":"graph","created_at":"2026-07-05T03:36:50Z","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/1901.10002/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"As machine learning (ML) increasingly affects people and society, awareness of its potential unwanted consequences has also grown. To anticipate, prevent, and mitigate undesirable downstream consequences, it is critical that we understand when and how harm might be introduced throughout the ML life cycle. In this paper, we provide a framework that identifies seven distinct potential sources of downstream harm in machine learning, spanning data collection, development, and deployment. In doing so, we aim to facilitate more productive and precise communication around these issues, as well as mor","authors_text":"Harini Suresh, John V. Guttag","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-01-28T21:00:20Z","title":"A Framework for Understanding Sources of Harm throughout the Machine Learning Life Cycle"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1901.10002","kind":"arxiv","version":5},"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:febb8278570330e4946ec51298840669efb3ee5243e3105a0fba9c0971ec1cdf","target":"record","created_at":"2026-07-05T03:36:50Z","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":"6a9cbdaed275f37d1f696cf9ef8c0a52054a1553d41fd5dee5df457c779e0056","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-01-28T21:00:20Z","title_canon_sha256":"a630c3cc7508e277653e672e7262da744eeaae79733413448fa35d82d8796098"},"schema_version":"1.0","source":{"id":"1901.10002","kind":"arxiv","version":5}},"canonical_sha256":"b5822fbacbb6218732d2a9dbcf2e9c0e5f2b362885b9b9d0ec1e1a43ad026bde","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b5822fbacbb6218732d2a9dbcf2e9c0e5f2b362885b9b9d0ec1e1a43ad026bde","first_computed_at":"2026-07-05T03:36:50.577973Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:36:50.577973Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"UQWmZJOwkx20iYlQhx4qJsbpmB1kXbMLNuVa43JM65M95NiZdJn6OScyMq5yWR8UBp6rNIdLO5YbYkV0swlADg==","signature_status":"signed_v1","signed_at":"2026-07-05T03:36:50.578500Z","signed_message":"canonical_sha256_bytes"},"source_id":"1901.10002","source_kind":"arxiv","source_version":5}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:febb8278570330e4946ec51298840669efb3ee5243e3105a0fba9c0971ec1cdf","sha256:0a28efd3a11b9ca1c3811c17099db869a99997053f0f9d0ab394278352c7a3e3"],"state_sha256":"2f5ffed32718c7ab1cd9b031002e73895b929ea4be478fc32ac73db3b02f683e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"d5Z4k4XB6FVpcFgqA/p5AyCDps23cMWQ3AwGzT4M3LLUwLl2YBQzdQs1uWHV+SEfroKTXMbWBwUAQzY/8k77Dw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-13T04:22:05.425131Z","bundle_sha256":"9743a98eee9f1c523db2a2192e545fd5a2a89314c85423c10eb6af2f485534f1"}}