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概述
The initial posting deadline was January 1, 2026; developers must also post before each later public release or substantial modification in scope. The law creates transparency duties but does not decide whether particular training uses are lawful.
深入探讨
AB 2013, the Generative Artificial Intelligence Training Data Transparency Act, was enacted in 2024. It requires a developer of a covered generative AI system or service made publicly available to Californians for use to post training-data documentation on its website. The initial posting deadline was January 1, 2026. For a covered system released on or after January 1, 2022, documentation must also be posted before each later public release or substantial modification. The documentation includes a high-level summary of training datasets and information about their sources or owners, purpose, approximate number and types of data points, and collection period. It must address whether datasets include copyrighted, trademarked, patented, personal, or aggregate consumer information; whether they were purchased or licensed; how the developer cleaned or processed them; when they were first used; and whether synthetic data generation was used. The definition of developer includes parties that substantially modify a system for public use. AB 2013 requires dataset-level information, not publication of the raw training corpus or source code. A disclosure does not grant copyright permission, decide fair use, or replace privacy obligations. The act includes exceptions, including systems used solely for security and integrity, systems whose sole purpose is aircraft operation in the national airspace, and systems developed for national-security, military, or defense purposes that are made available only to a federal entity. Read each exception against its exact statutory conditions. Maintain a training-data inventory linked to model versions, fine-tuning runs, synthetic-data generation, and release dates. Assign an owner to prepare and update the public documentation, review sensitive claims, and preserve evidence of what was posted for each covered release. Describe uncertainty rather than inventing dataset provenance. Check the enacted text and current California code for definitions, exceptions, and amendments.
战略影响
风险与安全
灾难性和日常的人工智能危害都取决于谁了解风险以及谁能够采取行动。
更清晰的判决
公众和专业素养决定强有力的安全政策在政治上是否可行。
打破炒作
清晰的解释可以减少炒作、实验室公关和模糊道德剧场的影响。
The Future of California AB 2013 Training Data Transparency Law
AB 2013 is operative on a fixed timeline, and implementation choices may be clarified through amendments, enforcement, or litigation. Data pipelines and model versions continue to change, making stale disclosures a practical risk. Developers should monitor official California sources, preserve the dated disclosure in release records, and reassess coverage after substantial model changes. Training-data transparency should be coordinated with privacy, copyright, and contractual review. Retain dated copies of posted documentation and link them to model release records. Recheck the official code after amendments.
现实世界的实施
A developer lists the sources or owners of training datasets and explains how the data were collected, processed, and used.
A model maker describes whether training included copyrighted, trademarked, or patented material, without claiming that disclosure settles permission questions.
A developer identifies whether personal information was included and whether synthetic data generation was used.
A system developed for national-security, military, or defense purposes is checked against the statutory condition that it be made available only to a federal entity.
风险与防护栏
将存在风险视为科幻小说，同时能力复合。
混淆了表面产品安全与高度自治下的对准。
只给非英语和非专业观众留下低质量的资源。
实施路线图
单独的产品危害、误用和失控/失调风险。
询问哪些证据会改变您对时间表和严重性的看法。
比起营销主张，更喜欢主要来源和具体评估。
确定一条行动路径：职业、政策、资金或技能——而不仅仅是意识。
不断探索
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常见问题
What is California AB 2013 Training Data Transparency Law?
California AB 2013 requires developers of covered generative AI systems and services to publish training-data documentation. The initial posting deadline was January 1, 2026; developers must also post before each later public release or substantial modification in scope. The law creates transparency duties but does not decide whether particular training uses are lawful.
Which developer activity can bring a system within AB 2013?
The statute defines developer broadly to include designing, coding, producing, or substantially modifying a system or service for public use.
Which public documentation deadline does AB 2013 set?
The statute sets January 1, 2026 as the deadline for the required posting.
Which information belongs in the required documentation?
AB 2013 calls for documentation about datasets used in development, including source, collection, processing, and use information.
Does AB 2013 disclosure itself authorize use of copyrighted training material?
The transparency requirement does not resolve copyright permission or fair-use questions.
Which system date can be relevant to coverage?
The statute’s scope includes systems released or substantially modified on or after January 1, 2022.
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