California AB 2013 AI Training Data Transparency

state_law — US-CA
Effective: January 1, 2026 56 platforms tracked 912 provisions indexed Enforced by: California Attorney General

Overview

California AB 2013 requires developers of generative AI systems to publicly disclose detailed information about the data used to train their models. Disclosures must include high-level summaries of training datasets, whether datasets include copyrighted material or personal information, the sources and methods of data collection, the number or volume of data points in training sets, and the time period covered by training data. The law aims to increase transparency around AI training practices, particularly regarding the use of copyrighted works and personal data in model development. Narrow exceptions exist for national security applications and certain trade secret protections.

Key Articles & Sections

Platforms We Track Subject to

Recent Changes Related to

ConductAtlas maps governance language to potentially relevant regulatory frameworks. Regulatory applicability and enforceability may vary by jurisdiction, enforcement context, and individual circumstances. This page is informational and does not constitute legal advice. Methodology

Provisions Governed by (912 across 56 platforms)

Collection of Account Registration Identifiers AI21 Labs
Medium
Cookies Used for Analytics and Advertising Partners AI21 Labs
Medium
Automatic Collection of IP and Device Data AI21 Labs
Medium
Collection of Geolocation from IP Address AI21 Labs
Medium
Use of Cookies and Tracking Technologies AI21 Labs
Medium
Amplitude Data Anonymized Unless Consent Given AI21 Labs
Medium
Collection of User Usage and Interaction Data AI21 Labs
Medium
Anthropic Not Obligated to Host Third-Party Content Anthropic
Medium
Brazil right to review automated processing decisions Anthropic
Medium
Training data sourced from third parties Anthropic
Medium
Academic testing and admissions AI requirements Anthropic
Medium
Feedback storage of full conversation Anthropic
Medium
No automated legal decision-making Anthropic
Medium
Feedback Ratings Stored as Conversation Data Anthropic
Medium
Asynchronous Monitoring Classifier Deep Scrutiny Obligation Anthropic
Medium
Canada consent basis for data processing Anthropic
Medium
Feedback Stored as Part of User Conversation Anthropic
Medium
Feedback storage of full conversation Anthropic
Medium
Right to Remove Infringing or Harmful Third-Party Content Anthropic
Medium
Usage information collection including browsing history Anthropic
Medium
AI R&D Doubling Rate Definition Binding Interpretation Anthropic
Medium
Classifier Regular Update Requirement Anthropic
Medium
Collection of payment information Anthropic
Medium
Brazil right to review automated decisions Anthropic
Medium
Collection of identity and contact data at signup Anthropic
Medium
Collection of payment information for purchases Anthropic
Medium
Study participation data collection and combination Anthropic
Medium
Canada consent required for collection and disclosure Anthropic
Medium
Journalistic content publishing AI requirements Anthropic
Medium
Cookies and similar tracking technologies Anthropic
Medium

Showing 30 of 912 provisions. View all →

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Frequently Asked Questions

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Which platforms does apply to?

ConductAtlas tracks -relevant provisions across 56 platforms. Each platform's specific provisions are classified by severity and mapped to requirements.

How does ConductAtlas monitor compliance?

ConductAtlas captures policy documents daily, classifies provisions by regulatory framework, and flags changes that affect obligations. Every change is archived with cryptographic verification.