TikTok · TikTok Privacy Policy · View original document ↗

Machine Learning Model Training Using User Data

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Document Record

What it is

The policy states that TikTok uses collected data including user content, messages, AI interactions, and metadata to train and improve machine learning models and algorithms, and that this includes scanning and analyzing user content and messages.

This analysis describes what TikTok's agreement states, permits, or reserves. It does not constitute a legal determination about enforceability. Regulatory applicability and practical outcomes may vary by jurisdiction, enforcement context, and individual circumstances. Read our methodology

ConductAtlas Analysis

Why it matters (compliance & governance perspective)

This provision authorizes use of user-generated content, direct messages, and AI interaction data for machine learning training purposes, which extends the use of this data beyond service delivery into technology development. The inclusion of messages in the scope of ML training data is operationally notable.

What you can do

⚠️ These actions may provide transparency or partial mitigation but may not fully address the underlying issue. Effectiveness varies by jurisdiction and individual circumstances.
  • Delete Your Data
    Submit a data deletion request via TikTok's privacy webform. TikTok states it will respond consistent with applicable law and subject to verification.

If You Do Nothing

User content, messages, and AI interaction data will be used for ML model training under the terms as written

Cross-platform context

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Monitoring

TikTok has changed this document before.

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▸ View Original Clause Language DOCUMENT RECORD
"
To review, support, improve, and develop the Services, and train, test, and improve technology, such as machine learning models and algorithms, including by analyzing how people are using the Services; conducting research; soliciting feedback; monitoring your activity and usage across the devices you use to access the Services; and scanning, analyzing, and reviewing user content, messages, AI interactions, and associated metadata.

Excerpt from TikTok's Privacy Policy

ConductAtlas Analysis

Institutional analysis (regulatory & governance intelligence)

(1) REGULATORY LANDSCAPE: Use of user-generated content and messages for ML training engages CCPA purpose limitation principles and may implicate the California Privacy Rights Act's provisions on automated decision-making. State privacy laws in Colorado, Connecticut, and Virginia include provisions relevant to profiling and automated processing. The EU AI Act, while not directly applicable to US-only operations, may inform practices for users with cross-jurisdictional access. (2) GOVERNANCE EXPOSURE: Medium. The authorization to use messages for ML training raises data minimization considerations. The policy does not provide a separate consent mechanism or opt-out specifically for ML training use, relying on the general data rights request process. (3) JURISDICTION FLAGS: California, Colorado, Connecticut, and Virginia users have data access and deletion rights that extend to data used for ML training. Where ML training constitutes profiling under applicable state definitions, opt-out rights may apply. (4) CONTRACT AND VENDOR IMPLICATIONS: Businesses using TikTok for customer communication through in-app messaging or shopping chat features should assess whether their customer communications may be included in ML training data flows and whether their privacy disclosures to customers reflect this. (5) COMPLIANCE CONSIDERATIONS: Data mapping documentation should reflect ML training as a distinct processing purpose for user content, messages, and AI interactions. Legal teams should evaluate whether the current disclosure is sufficient under applicable state purpose limitation requirements or whether a separate disclosure or consent mechanism is warranted.

Full institutional analysis

Regulatory citations, enforcement risk, and due diligence action items.

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Applicable agencies

  • FTC
    The FTC has jurisdiction over data use practices for AI and machine learning training that may constitute unfair or deceptive practices under consumer protection authority.
    File a complaint →

Provision details

Document information
Document
TikTok Privacy Policy
Entity
TikTok
Document last updated
May 5, 2026
Tracking information
First tracked
July 16, 2026
Last verified
July 16, 2026
Record ID
CA-P-00033005
Document ID
CA-D-00033
Evidence Provenance
Source URL
Wayback Machine
Content hash (SHA-256)
8d9807c92ed6aba7e076558b9c07abcf61408c1aa289dfd4b342947576e13121
Analysis generated
July 16, 2026 01:57 UTC
Methodology
Evidence
✓ Snapshot stored   ✓ Hash verified
Citation Record
Entity: TikTok
Document: TikTok Privacy Policy
Record ID: CA-P-00033005
Captured: 2026-07-16 01:57:57 UTC
SHA-256: 8d9807c92ed6aba7…
URL: https://conductatlas.com/platform/tiktok/tiktok-privacy-policy/machine-learning-model-training-using-user-data/
Accessed: July 23, 2026
Permanent archival reference. Stable identifier suitable for legal filings, compliance documentation, and research citation.
Classification
Severity
Medium
Categories

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Frequently Asked Questions

What does TikTok's Machine Learning Model Training Using User Data clause do?

This provision authorizes use of user-generated content, direct messages, and AI interaction data for machine learning training purposes, which extends the use of this data beyond service delivery into technology development. The inclusion of messages in the scope of ML training data is operationally notable.

Is ConductAtlas affiliated with TikTok?

No. ConductAtlas is an independent monitoring service. We are not affiliated with, endorsed by, or sponsored by TikTok.