{ "format": "agent-article-v0", "article_id": "EA-102", "canonical_url": "/tools/ea-102", "page_type": "reference", "claim_ids": [], "evidence_ids": [ "EVD-EA-102-URL-D6FFFB6F2FF8", "EVD-EA-102-URL-8A668914D489", "EVD-EA-102-URL-4EC0786EBA13", "EA-102-R11-RESEARCH", "EA-102-R11-WEB-READBACK" ], "unknown_ids": [ "EA-102-UNKNOWN-01", "EA-102-UNKNOWN-CURRENTNESS" ], "operational_object_ids": [], "provider": [], "models": [], "plans": [], "surfaces": [], "regions": [], "current_status": "UNKNOWN", "observation_status": "SPEC_ONLY", "freshness": "UNKNOWN", "last_verified": null, "supersedes": [], "superseded_by": [], "provenance": [ "COMM-039-EA0102", "SRC-EA-102-URL-D6FFFB6F2FF8", "SRC-EA-102-URL-8A668914D489", "SRC-EA-102-URL-4EC0786EBA13", "WEBBODY-EA0102-R8-544D9B05" ], "article_sources": [ { "id": "EVD-EA-102-URL-D6FFFB6F2FF8", "evidence_class": "RESEARCH", "title": "1) source class: government primary report; exact title: Copyright and Artificial Intelligence, Part 2: Copyrightability; author/org: U.S. Copyright Office; canonical URL:", "href": "https://www.copyright.gov/ai/Copyright-and-Artificial-Intelligence-Part-2-Copyrightability-Report.pdf", "supports": [], "limit": "元の監査済み資料に記載された参照先です。URLの復元は、資料の最新性や全主張の支持を新たに検証したことを意味しません。", "origin_class": "SOURCE_PACKET_REFERENCE", "source_or_experiment_ids": [ "SRC-EA-102-URL-D6FFFB6F2FF8" ], "supporting_locators": [ "EVIDENCE TABLE", "1) source class: government primary report; exact title: Copyright and Artificial Intelligence, Part 2: Copyrightability; author/org: U.S. Copyright Office; canonical URL: https://www.copyright.gov/ai/Copyright-and-Artificial-Intelligence-Part-2-Copyrightability-Report.pdf" ], "scope": "EVIDENCE TABLE", "provenance_status": "SOURCE_PACKET_REFERENCE_PROJECTED" }, { "id": "EVD-EA-102-URL-8A668914D489", "evidence_class": "RESEARCH", "title": "2) source class: government primary report; exact title: Copyright and Artificial Intelligence, Part 3: Generative AI Training, Pre-Publication Version; author/org: U.S. Copyright ", "href": "https://www.copyright.gov/ai/Copyright-and-Artificial-Intelligence-Part-3-Generative-AI-Training-Report-Pre-Publication-Version.pdf", "supports": [], "limit": "元の監査済み資料に記載された参照先です。URLの復元は、資料の最新性や全主張の支持を新たに検証したことを意味しません。", "origin_class": "SOURCE_PACKET_REFERENCE", "source_or_experiment_ids": [ "SRC-EA-102-URL-8A668914D489" ], "supporting_locators": [ "EVIDENCE TABLE", "2) source class: government primary report; exact title: Copyright and Artificial Intelligence, Part 3: Generative AI Training, Pre-Publication Version; author/org: U.S. Copyright Office; canonical URL: https://www.copyright.gov/ai/Copyright-and-Artificial-Intelligence-Part-3-Generative-AI-Training-Report-Pre-Publication-Version.pdf" ], "scope": "EVIDENCE TABLE", "provenance_status": "SOURCE_PACKET_REFERENCE_PROJECTED" }, { "id": "EVD-EA-102-URL-4EC0786EBA13", "evidence_class": "RESEARCH", "title": "3) source class: official government policy; exact title: Trade secret policy; author/org: USPTO, Office of Policy and International Affairs; canonical URL:", "href": "https://www.uspto.gov/ip-policy/trade-secret-policy", "supports": [], "limit": "元の監査済み資料に記載された参照先です。URLの復元は、資料の最新性や全主張の支持を新たに検証したことを意味しません。", "origin_class": "SOURCE_PACKET_REFERENCE", "source_or_experiment_ids": [ "SRC-EA-102-URL-4EC0786EBA13" ], "supporting_locators": [ "EVIDENCE TABLE", "3) source class: official government policy; exact title: Trade secret policy; author/org: USPTO, Office of Policy and International Affairs; canonical URL: https://www.uspto.gov/ip-policy/trade-secret-policy" ], "scope": "EVIDENCE TABLE", "provenance_status": "SOURCE_PACKET_REFERENCE_PROJECTED" }, { "id": "EA-102-R11-RESEARCH", "evidence_class": "RESEARCH", "title": "EA-102 監査済みresearch / canonical revision binding", "supports": [ "確立できるのは、米国著作権局がAI出力の著作権可能性を人間の寄与と事実関係に依存するものとして扱い、prompt単独を一般に十分なcontrolとしないこと、学習/RAG/出力を別論点として扱っていること、USPTOが営業秘密に3要素を要求していること。これを日本企業の個別法的結論へ外挿できない。" ], "limit": "canonical監査・revision bindingの存在を示す。外部ソースcurrentnessが本文またはcontrol-planeで確定していない場合は、currentnessをUNKNOWNのまま保持する。", "origin_class": "AUDITED_CANONICAL_RESEARCH_PACKET", "source_or_experiment_ids": [ "COMM-039-EA0102" ], "supporting_locators": [ "COMM-039-EA0102", "EA-102-R5-LEGACY-MIGRATION-20261008-R1", "content/staging/EA-102.md" ], "scope": "監査済みEA本文・canonical revision・既存Source Graph relationの範囲。欠損currentnessは推測で閉じない。", "provenance_status": "AUDIT_PASS_CANONICAL_BINDING" }, { "id": "EA-102-R11-WEB-READBACK", "evidence_class": "IMPL", "title": "EA-102 Web body identity / canonical readback", "supports": [ "canonical staging bodyのSHA-256一致とR9 canonical ledger readbackをProduction projectionの入力として検証する。" ], "limit": "body identity/readbackは本文claim自体の真偽や外部ソースの最新性を追加保証しない。", "checked_at": null, "origin_class": "IMPLEMENTATION_READBACK", "source_or_experiment_ids": [ "WEBBODY-EA0102-R8-544D9B05" ], "supporting_locators": [ "WEBBODY-EA0102-R8-544D9B05", "content/staging/EA-102.md", "EA-102-R5-LEGACY-MIGRATION-20261008-R1" ], "scope": "R9/R10 canonical readback後のProduction生成時body identity。", "provenance_status": "CANONICAL_READBACK_BODY_HASH_MATCH" } ], "research_sections": [ { "heading": "WHY_THIS_MATTERS_TO_UPDATE", "text": "入力・出力・学習・RAG・生成コードを一つの「AI利用可否」に圧縮すると、著作権、営業秘密、契約、ライセンスの別問題を取り違える。" }, { "heading": "SCOPE_ROUTING", "text": "Enterprise AI Core / IP / privacy / security / governance" }, { "heading": "CLAIM_OR_RESEARCH_QUESTION", "text": "AI入力・出力・学習・RAG・生成コードの各場面で、一次資料から固定できる境界は何か。" }, { "heading": "EVIDENCE TABLE", "text": "1) source class: government primary report; exact title: Copyright and Artificial Intelligence, Part 2: Copyrightability; author/org: U.S. Copyright Office; canonical URL: https://www.copyright.gov/ai/Copyright-and-Artificial-Intelligence-Part-2-Copyrightability-Report.pdf; publication/update/access: January 2025 / accessed 2026-09-13; version/release: Report Part 2; supporting locator: PDF pp. ii-iii / lines 66-121（AI出力の著作権可能性、human contribution、prompt aloneの限界、case-by-case）; evidence label: SOURCE_REPORT + PRODUCT_VOLATILE; relation: support / legal limit。\n2) source class: government primary report; exact title: Copyright and Artificial Intelligence, Part 3: Generative AI Training, Pre-Publication Version; author/org: U.S. Copyright Office; canonical URL: https://www.copyright.gov/ai/Copyright-and-Artificial-Intelligence-Part-3-Generative-AI-Training-Report-Pre-Publication-Version.pdf; publication/update/access: pre-publication released 2025-05-09 / accessed 2026-09-13; version/release: pre-publication; supporting locator: PDF contents pp. 2, 9, 17, 26-31（training data、training、RAG、outputsを別章で扱う）; evidence label: SOURCE_REPORT + UNKNOWN + PRODUCT_VOLATILE; relation: scope / limit。\n3) source class: official government policy; exact title: Trade secret policy; author/org: USPTO, Office of Policy and International Affairs; canonical URL: https://www.uspto.gov/ip-policy/trade-secret-policy; publication/update/access: published 2025-10-28, updated 2026-07-29 / accessed 2026-09-13; version/release: current policy page; supporting locator: lines 454-463（economic value/not generally known、value from secrecy、reasonable effortsの3要素）; evidence label: VERIFIED_SPEC + PRODUCT_VOLATILE; relation: support / limit。" }, { "heading": "FINDINGS", "text": "確立できるのは、米国著作権局がAI出力の著作権可能性を人間の寄与と事実関係に依存するものとして扱い、prompt単独を一般に十分なcontrolとしないこと、学習/RAG/出力を別論点として扱っていること、USPTOが営業秘密に3要素を要求していること。これを日本企業の個別法的結論へ外挿できない。" }, { "heading": "LIMITS / COUNTEREVIDENCE / FAILURE ENVELOPE", "text": "Part 3はpre-publicationであり、最終版ではない。著作権局の分析は米国著作権法の報告で、契約・秘密保持・各国法を確定しない。RAGで参照しただけで権利処理が完了する証拠ではない。" }, { "heading": "AVAILABILITY_GATES", "text": "法域・権利者/ライセンス・入力機密性・provider契約・出力の人間寄与・学習/保存設定・生成コード依存関係・OSS licenseを別gate化。" }, { "heading": "IMPLEMENTATION_STATE", "text": "実装状態: data classification、prompt/input provenance、human contribution log、生成コードのdependency/license scanを設計候補として抽出。実組織の法務承認は未実施。" }, { "heading": "BENCHMARK_OR_EVAL", "text": "Benchmark: なし。Evaluation: 公開/社内秘/個人情報/第三者著作物/OSSコードを含むfixtureで、入力・出力・保存・再利用・削除の記録を監査する非破壊試験。" }, { "heading": "SECURITY / PRIVACY / AUDIT / COST / OPERABILITY", "text": "SECURITY/PRIVACY/AUDIT: secretを評価用promptへ投入しない、アクセス・保持・利用目的を記録。COST: 法務レビューとライセンス調査工数は未計測。OPERABILITY: report版と法域as-ofを保存。" }, { "heading": "SAFE_WORDING_FOR_FUTURE_BOOK", "text": "「米国著作権局はAI出力の保護を人間の寄与に基づき事実ごとに判断する分析を示している。営業秘密は秘密性を維持する合理的努力を含む要件がある。日本での結論やprovider契約は別確認が必要。」" }, { "heading": "UPDATE_WORK_HANDOFF", "text": "将来本文は、入力/出力/学習/RAG/コードの5行×法域/契約/秘密性/ライセンスの列で改訂する。法的助言として閉じない。" }, { "heading": "OPEN_UNKNOWN", "text": "日本・EU等の最新判例/行政指針、providerごとの学習・保持契約、RAG再利用時の権利処理、生成コードのlicense provenance。" }, { "heading": "STOP_CONDITION", "text": "一次資料が対象法域と用途をカバーしないとき、UNKNOWNを「利用可/不可」へ変換しない。\nUNIT_CLOSE_STATUS: INDIVIDUAL_BOUNDED_CLOSE / EVIDENCE_RECORDED / UNKNOWN_PRESERVED\n\n---" }, { "heading": "AUDITED_CURRENTNESS_BOUNDARY", "text": "U.S. Copyright Office Part 3 remains May 2025 PRE-PUBLICATION VERSION; U.S. copyright/trade-secret analysis is not generalized to Japan/EU or provider contracts." } ], "human_url": "/tools/ea-102", "markdown_url": "/agent/article.md?path=%2Ftools%2Fea-102", "json_url": "/agent/article.json?path=%2Ftools%2Fea-102" }