{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:YJZBIJGEK4BF64YJ5SSNRMFZRD","short_pith_number":"pith:YJZBIJGE","canonical_record":{"source":{"id":"2606.01929","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.AI","submitted_at":"2026-06-01T08:59:03Z","cross_cats_sorted":[],"title_canon_sha256":"024b0af1dd52b5b976dabf31012e1c98c9f3cee15b79844b76f727a1475e0783","abstract_canon_sha256":"bc786dfc46c2c77b4ee210449b1c9198094af094dbe1e8b19e4ab71470419229"},"schema_version":"1.0"},"canonical_sha256":"c2721424c457025f7309eca4d8b0b988c1ffe53b3ac930e678550de6db647950","source":{"kind":"arxiv","id":"2606.01929","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.01929","created_at":"2026-06-02T02:05:00Z"},{"alias_kind":"arxiv_version","alias_value":"2606.01929v1","created_at":"2026-06-02T02:05:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.01929","created_at":"2026-06-02T02:05:00Z"},{"alias_kind":"pith_short_12","alias_value":"YJZBIJGEK4BF","created_at":"2026-06-02T02:05:00Z"},{"alias_kind":"pith_short_16","alias_value":"YJZBIJGEK4BF64YJ","created_at":"2026-06-02T02:05:00Z"},{"alias_kind":"pith_short_8","alias_value":"YJZBIJGE","created_at":"2026-06-02T02:05:00Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:YJZBIJGEK4BF64YJ5SSNRMFZRD","target":"record","payload":{"canonical_record":{"source":{"id":"2606.01929","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.AI","submitted_at":"2026-06-01T08:59:03Z","cross_cats_sorted":[],"title_canon_sha256":"024b0af1dd52b5b976dabf31012e1c98c9f3cee15b79844b76f727a1475e0783","abstract_canon_sha256":"bc786dfc46c2c77b4ee210449b1c9198094af094dbe1e8b19e4ab71470419229"},"schema_version":"1.0"},"canonical_sha256":"c2721424c457025f7309eca4d8b0b988c1ffe53b3ac930e678550de6db647950","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-02T02:05:00.785527Z","signature_b64":"W9TKv8HVHQoh4CEkXN2H0pJU1/rWUaqU5eXfOLB5IRfLieJFLmIlpOX4asF/Mkv8jH7fWIUS6zRxkfgMkQ7+Dw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c2721424c457025f7309eca4d8b0b988c1ffe53b3ac930e678550de6db647950","last_reissued_at":"2026-06-02T02:05:00.785100Z","signature_status":"signed_v1","first_computed_at":"2026-06-02T02:05:00.785100Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2606.01929","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":"2026-06-02T02:05:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fg0cpiB7baCftqw/ONlSuJagpSu6p/igMX/OgVTchaSPpCvSuUuMoiNTYEfALR2f8MOEPgBp7UFjIISTwVnXCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-29T03:49:32.166304Z"},"content_sha256":"f328a567ccecdedde4c7e9300025c2777f55a620671bc4e41c5dc7ac1cea4d31","schema_version":"1.0","event_id":"sha256:f328a567ccecdedde4c7e9300025c2777f55a620671bc4e41c5dc7ac1cea4d31"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:YJZBIJGEK4BF64YJ5SSNRMFZRD","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"VET: A Framework for Analyzing AI Discourse","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Meredith Ringel Morris","submitted_at":"2026-06-01T08:59:03Z","abstract_excerpt":"Public discourse on AI has become polarized; exaggerated positions on AI in traditional and social media threaten the development of AI Literacy among the general public. In this article, I introduce the VET Framework, a method for categorizing AI discourse along the dimensions of valence, effectiveness, and trajectory. I show how this framework can be used to identify, compare, and critique prevalent narratives of AI Hype, AI Doom, AI Denial, and AI Normalcy. Using VET, I analyze how each of these four stances exaggerates some aspects of the current state and/or likely evolution of AI, and il"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.01929","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/2606.01929/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":"2026-06-02T02:05:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DscoZZyTs+ZJ5oPU1M4ZUTlbEB1sgXZvkUcoNkmitRwzcjNcMEZNy5PhiE9cQgbnU6h/Mq2n9l+Fv4Njtx++Cw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-29T03:49:32.166723Z"},"content_sha256":"5a72edab4f80b8fab074305f4c3330e6669e0c4d63857bf9aa12480ae068c563","schema_version":"1.0","event_id":"sha256:5a72edab4f80b8fab074305f4c3330e6669e0c4d63857bf9aa12480ae068c563"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/YJZBIJGEK4BF64YJ5SSNRMFZRD/bundle.json","state_url":"https://pith.science/pith/YJZBIJGEK4BF64YJ5SSNRMFZRD/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/YJZBIJGEK4BF64YJ5SSNRMFZRD/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":"2026-06-29T03:49:32Z","links":{"resolver":"https://pith.science/pith/YJZBIJGEK4BF64YJ5SSNRMFZRD","bundle":"https://pith.science/pith/YJZBIJGEK4BF64YJ5SSNRMFZRD/bundle.json","state":"https://pith.science/pith/YJZBIJGEK4BF64YJ5SSNRMFZRD/state.json","well_known_bundle":"https://pith.science/.well-known/pith/YJZBIJGEK4BF64YJ5SSNRMFZRD/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:YJZBIJGEK4BF64YJ5SSNRMFZRD","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":"bc786dfc46c2c77b4ee210449b1c9198094af094dbe1e8b19e4ab71470419229","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.AI","submitted_at":"2026-06-01T08:59:03Z","title_canon_sha256":"024b0af1dd52b5b976dabf31012e1c98c9f3cee15b79844b76f727a1475e0783"},"schema_version":"1.0","source":{"id":"2606.01929","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.01929","created_at":"2026-06-02T02:05:00Z"},{"alias_kind":"arxiv_version","alias_value":"2606.01929v1","created_at":"2026-06-02T02:05:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.01929","created_at":"2026-06-02T02:05:00Z"},{"alias_kind":"pith_short_12","alias_value":"YJZBIJGEK4BF","created_at":"2026-06-02T02:05:00Z"},{"alias_kind":"pith_short_16","alias_value":"YJZBIJGEK4BF64YJ","created_at":"2026-06-02T02:05:00Z"},{"alias_kind":"pith_short_8","alias_value":"YJZBIJGE","created_at":"2026-06-02T02:05:00Z"}],"graph_snapshots":[{"event_id":"sha256:5a72edab4f80b8fab074305f4c3330e6669e0c4d63857bf9aa12480ae068c563","target":"graph","created_at":"2026-06-02T02:05:00Z","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/2606.01929/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Public discourse on AI has become polarized; exaggerated positions on AI in traditional and social media threaten the development of AI Literacy among the general public. In this article, I introduce the VET Framework, a method for categorizing AI discourse along the dimensions of valence, effectiveness, and trajectory. I show how this framework can be used to identify, compare, and critique prevalent narratives of AI Hype, AI Doom, AI Denial, and AI Normalcy. Using VET, I analyze how each of these four stances exaggerates some aspects of the current state and/or likely evolution of AI, and il","authors_text":"Meredith Ringel Morris","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.AI","submitted_at":"2026-06-01T08:59:03Z","title":"VET: A Framework for Analyzing AI Discourse"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.01929","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:f328a567ccecdedde4c7e9300025c2777f55a620671bc4e41c5dc7ac1cea4d31","target":"record","created_at":"2026-06-02T02:05:00Z","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":"bc786dfc46c2c77b4ee210449b1c9198094af094dbe1e8b19e4ab71470419229","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.AI","submitted_at":"2026-06-01T08:59:03Z","title_canon_sha256":"024b0af1dd52b5b976dabf31012e1c98c9f3cee15b79844b76f727a1475e0783"},"schema_version":"1.0","source":{"id":"2606.01929","kind":"arxiv","version":1}},"canonical_sha256":"c2721424c457025f7309eca4d8b0b988c1ffe53b3ac930e678550de6db647950","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c2721424c457025f7309eca4d8b0b988c1ffe53b3ac930e678550de6db647950","first_computed_at":"2026-06-02T02:05:00.785100Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-02T02:05:00.785100Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"W9TKv8HVHQoh4CEkXN2H0pJU1/rWUaqU5eXfOLB5IRfLieJFLmIlpOX4asF/Mkv8jH7fWIUS6zRxkfgMkQ7+Dw==","signature_status":"signed_v1","signed_at":"2026-06-02T02:05:00.785527Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.01929","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f328a567ccecdedde4c7e9300025c2777f55a620671bc4e41c5dc7ac1cea4d31","sha256:5a72edab4f80b8fab074305f4c3330e6669e0c4d63857bf9aa12480ae068c563"],"state_sha256":"3d9a4af140f31230d1b65774c0e37fcb42bbb368dcad09d3bc7bd74bc0165bcc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"O8Ul0L34/07HPcL9wqWvIUSoG59E+fhYCeW1/aCRDgNQAsEwQyBrU6qsg130Jt8xo+Y+hZ56ypTNfuMtA+xrDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-29T03:49:32.168702Z","bundle_sha256":"1ffa7bff1c962283bff457ce9f8e4d93b5da35748ebec608f9ee7e5f15f6ef5c"}}