This analysis describes what Segment'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
Personal data is used as training input for AI/ML systems, meaning it informs automated model development beyond direct service delivery.
Interpretive note: The excerpt covers two distinct activities: model training and real-time automated decision-making. The canonical claim states only the primary (model training) proposition; the automated decision-making activity is recorded in omitted_material.
The updated policy establishes a new opt-out mechanism allowing users to decline having their data disclosed to third parties (other than service providers) or used for purposes materially different from the original collection purpose. The policy also explicitly discloses that Twilio Inc. is subject to FTC investigatory and enforcement powers, providing users with notice of the regulatory authority overseeing the company's privacy practices. You can exercise this opt-out right by contacting Segment through the mechanism specified in their privacy policy.
View change record →The updated terms establish clearer disclosure of how Segment transfers personal data internationally. Segment now explicitly certifies its compliance with the EU-U.S. Data Privacy Framework, UK Extension, and Swiss-U.S. Data Privacy Framework, and states that these DPF Principles take precedence if they conflict with other policy terms. The updated policy also adds specific rights allowing you to opt out of: (i) disclosure of your personal data to third parties other than service providers acting under Segment's instructions, or (ii) use of your personal data for purposes materially different from the original purpose or your subsequent authorization. You can exercise these rights by contacting privacy@twilio.com.
View change record →The reader's data may be used to train AI/ML models aimed at recognizing security vulnerabilities and fraud signatures.
How other platforms handle this
Microsoft also emphasizes the importance of validating AI models responsibly to enhance fairness and alignment with reality.
it is unlikely that an objection or opt out right would apply to such processing. This is because... no such right applies because the process relates to an exempted purpose, such as performing our contract with you or the detection or prevention of fraud...
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"Training AI/ML models to recognize evolving security vulnerabilities and fraud signatures; and, utilizing signals to make real-time automated security decisions, such as approving account applications or suspending fraudulent accounts...Excerpt from Segment's Privacy Policy
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How 10 AI platforms describe the use of user data for model training, improvement, and development, based on archived governance provisions.
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Personal data is used as training input for AI/ML systems, meaning it informs automated model development beyond direct service delivery.
The reader's data may be used to train AI/ML models aimed at recognizing security vulnerabilities and fraud signatures.
ConductAtlas has identified this type of provision across 217 platforms. See the full comparison.
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