{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:5PKTCAB5NCCXYYY6DZLCOQDKZQ","short_pith_number":"pith:5PKTCAB5","schema_version":"1.0","canonical_sha256":"ebd531003d68857c631e1e5627406acc0e751499309b2eb420aa60991a178240","source":{"kind":"arxiv","id":"2505.11866","version":1},"attestation_state":"computed","paper":{"title":"Position Paper: Bounded Alignment: What (Not) To Expect From AGI Agents","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Ali A. Minai","submitted_at":"2025-05-17T06:17:57Z","abstract_excerpt":"The issues of AI risk and AI safety are becoming critical as the prospect of artificial general intelligence (AGI) looms larger. The emergence of extremely large and capable generative models has led to alarming predictions and created a stir from boardrooms to legislatures. As a result, AI alignment has emerged as one of the most important areas in AI research. The goal of this position paper is to argue that the currently dominant vision of AGI in the AI and machine learning (AI/ML) community needs to evolve, and that expectations and metrics for its safety must be informed much more by our "},"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":"2505.11866","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2025-05-17T06:17:57Z","cross_cats_sorted":[],"title_canon_sha256":"6e600e0a168a0b4c3cd155b2949d206f127f1eed11679345602acdf1293e4b68","abstract_canon_sha256":"a832a4bf514d3417288e86a66f1b037dc33c567db664e16859cccbd4a031d374"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:04:53.542227Z","signature_b64":"NWUZNC9D+eEp/PtIOcvTO1SlBe4bwZJuYZyK+PFBkNBO8LPhLsnOIIyJiCH20snu5Wqj10Zi/IdF3lok3J5YCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ebd531003d68857c631e1e5627406acc0e751499309b2eb420aa60991a178240","last_reissued_at":"2026-07-05T11:04:53.541741Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:04:53.541741Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Position Paper: Bounded Alignment: What (Not) To Expect From AGI Agents","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Ali A. Minai","submitted_at":"2025-05-17T06:17:57Z","abstract_excerpt":"The issues of AI risk and AI safety are becoming critical as the prospect of artificial general intelligence (AGI) looms larger. The emergence of extremely large and capable generative models has led to alarming predictions and created a stir from boardrooms to legislatures. As a result, AI alignment has emerged as one of the most important areas in AI research. The goal of this position paper is to argue that the currently dominant vision of AGI in the AI and machine learning (AI/ML) community needs to evolve, and that expectations and metrics for its safety must be informed much more by our "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.11866","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/2505.11866/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":"2505.11866","created_at":"2026-07-05T11:04:53.541801+00:00"},{"alias_kind":"arxiv_version","alias_value":"2505.11866v1","created_at":"2026-07-05T11:04:53.541801+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.11866","created_at":"2026-07-05T11:04:53.541801+00:00"},{"alias_kind":"pith_short_12","alias_value":"5PKTCAB5NCCX","created_at":"2026-07-05T11:04:53.541801+00:00"},{"alias_kind":"pith_short_16","alias_value":"5PKTCAB5NCCXYYY6","created_at":"2026-07-05T11:04:53.541801+00:00"},{"alias_kind":"pith_short_8","alias_value":"5PKTCAB5","created_at":"2026-07-05T11:04:53.541801+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/5PKTCAB5NCCXYYY6DZLCOQDKZQ","json":"https://pith.science/pith/5PKTCAB5NCCXYYY6DZLCOQDKZQ.json","graph_json":"https://pith.science/api/pith-number/5PKTCAB5NCCXYYY6DZLCOQDKZQ/graph.json","events_json":"https://pith.science/api/pith-number/5PKTCAB5NCCXYYY6DZLCOQDKZQ/events.json","paper":"https://pith.science/paper/5PKTCAB5"},"agent_actions":{"view_html":"https://pith.science/pith/5PKTCAB5NCCXYYY6DZLCOQDKZQ","download_json":"https://pith.science/pith/5PKTCAB5NCCXYYY6DZLCOQDKZQ.json","view_paper":"https://pith.science/paper/5PKTCAB5","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2505.11866&json=true","fetch_graph":"https://pith.science/api/pith-number/5PKTCAB5NCCXYYY6DZLCOQDKZQ/graph.json","fetch_events":"https://pith.science/api/pith-number/5PKTCAB5NCCXYYY6DZLCOQDKZQ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/5PKTCAB5NCCXYYY6DZLCOQDKZQ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/5PKTCAB5NCCXYYY6DZLCOQDKZQ/action/storage_attestation","attest_author":"https://pith.science/pith/5PKTCAB5NCCXYYY6DZLCOQDKZQ/action/author_attestation","sign_citation":"https://pith.science/pith/5PKTCAB5NCCXYYY6DZLCOQDKZQ/action/citation_signature","submit_replication":"https://pith.science/pith/5PKTCAB5NCCXYYY6DZLCOQDKZQ/action/replication_record"}},"created_at":"2026-07-05T11:04:53.541801+00:00","updated_at":"2026-07-05T11:04:53.541801+00:00"}