{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:4XBANYJJIPJ6FVLUBPTJ5BKFKD","short_pith_number":"pith:4XBANYJJ","schema_version":"1.0","canonical_sha256":"e5c206e12943d3e2d5740be69e854550eebc9aba5da8622dfad5678406754d23","source":{"kind":"arxiv","id":"2507.08244","version":1},"attestation_state":"computed","paper":{"title":"Advancing AI Capabilities and Evolving Labor Outcomes","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["q-fin.EC"],"primary_cat":"econ.GN","authors_text":"Jacob Dominski, Yong Suk Lee","submitted_at":"2025-07-11T01:15:20Z","abstract_excerpt":"This study investigates the labor market consequences of AI by analyzing near real-time changes in employment status and work hours across occupations in relation to advances in AI capabilities. We construct a dynamic Occupational AI Exposure Score based on a task-level assessment using state-of-the-art AI models, including ChatGPT 4o and Anthropic Claude 3.5 Sonnet. We introduce a five-stage framework that evaluates how AI's capability to perform tasks in occupations changes as technology advances from traditional machine learning to agentic AI. The Occupational AI Exposure Scores are then li"},"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":"2507.08244","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"econ.GN","submitted_at":"2025-07-11T01:15:20Z","cross_cats_sorted":["q-fin.EC"],"title_canon_sha256":"ef0d4579eb40e7df50083e198331d4ac90966bc25ff8b767fc2682fdfbb7f4be","abstract_canon_sha256":"c8b08884e6302ba671f55fa0cb139dc542028ed7c47e5e15cb7eb7fc28684726"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:35:19.956132Z","signature_b64":"24cxMiDNkH4rpm4D1jpjN8rMjY6937JDc0u2a1ov87Dv6wjs+JUMw7QdwKTLRgKNkl/QSvVcUsQJqo8GSobfDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e5c206e12943d3e2d5740be69e854550eebc9aba5da8622dfad5678406754d23","last_reissued_at":"2026-07-05T11:35:19.955693Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:35:19.955693Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Advancing AI Capabilities and Evolving Labor Outcomes","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["q-fin.EC"],"primary_cat":"econ.GN","authors_text":"Jacob Dominski, Yong Suk Lee","submitted_at":"2025-07-11T01:15:20Z","abstract_excerpt":"This study investigates the labor market consequences of AI by analyzing near real-time changes in employment status and work hours across occupations in relation to advances in AI capabilities. We construct a dynamic Occupational AI Exposure Score based on a task-level assessment using state-of-the-art AI models, including ChatGPT 4o and Anthropic Claude 3.5 Sonnet. We introduce a five-stage framework that evaluates how AI's capability to perform tasks in occupations changes as technology advances from traditional machine learning to agentic AI. The Occupational AI Exposure Scores are then li"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.08244","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/2507.08244/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":"2507.08244","created_at":"2026-07-05T11:35:19.955761+00:00"},{"alias_kind":"arxiv_version","alias_value":"2507.08244v1","created_at":"2026-07-05T11:35:19.955761+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.08244","created_at":"2026-07-05T11:35:19.955761+00:00"},{"alias_kind":"pith_short_12","alias_value":"4XBANYJJIPJ6","created_at":"2026-07-05T11:35:19.955761+00:00"},{"alias_kind":"pith_short_16","alias_value":"4XBANYJJIPJ6FVLU","created_at":"2026-07-05T11:35:19.955761+00:00"},{"alias_kind":"pith_short_8","alias_value":"4XBANYJJ","created_at":"2026-07-05T11:35:19.955761+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/4XBANYJJIPJ6FVLUBPTJ5BKFKD","json":"https://pith.science/pith/4XBANYJJIPJ6FVLUBPTJ5BKFKD.json","graph_json":"https://pith.science/api/pith-number/4XBANYJJIPJ6FVLUBPTJ5BKFKD/graph.json","events_json":"https://pith.science/api/pith-number/4XBANYJJIPJ6FVLUBPTJ5BKFKD/events.json","paper":"https://pith.science/paper/4XBANYJJ"},"agent_actions":{"view_html":"https://pith.science/pith/4XBANYJJIPJ6FVLUBPTJ5BKFKD","download_json":"https://pith.science/pith/4XBANYJJIPJ6FVLUBPTJ5BKFKD.json","view_paper":"https://pith.science/paper/4XBANYJJ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2507.08244&json=true","fetch_graph":"https://pith.science/api/pith-number/4XBANYJJIPJ6FVLUBPTJ5BKFKD/graph.json","fetch_events":"https://pith.science/api/pith-number/4XBANYJJIPJ6FVLUBPTJ5BKFKD/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/4XBANYJJIPJ6FVLUBPTJ5BKFKD/action/timestamp_anchor","attest_storage":"https://pith.science/pith/4XBANYJJIPJ6FVLUBPTJ5BKFKD/action/storage_attestation","attest_author":"https://pith.science/pith/4XBANYJJIPJ6FVLUBPTJ5BKFKD/action/author_attestation","sign_citation":"https://pith.science/pith/4XBANYJJIPJ6FVLUBPTJ5BKFKD/action/citation_signature","submit_replication":"https://pith.science/pith/4XBANYJJIPJ6FVLUBPTJ5BKFKD/action/replication_record"}},"created_at":"2026-07-05T11:35:19.955761+00:00","updated_at":"2026-07-05T11:35:19.955761+00:00"}