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Risks to privacy

AI Risk

"General- purpose AI systems can cause or contribute to violations of user privacy. Violations can occur inadvertently during the training or usage of AI systems, for example through unauthorised processing of personal data or leaking health records used in training. But violations can also happen deliberately through the use of general- purpose AI by malicious actors; for example, if they use AI to infer private...

Overview

A source-backed snapshot of this AI risk.

"General- purpose AI systems can cause or contribute to violations of user privacy. Violations can occur inadvertently during the training or usage of AI systems, for example through unauthorised processing of personal data or leaking health records used in training. But violations can also happen deliberately through the use of general- purpose AI by malicious actors; for example, if they use AI to infer private facts or violate security."

Techniques8Attack methods connected to this risk.
Mitigations18Defenses that may help with related attacks.
Records2Source records unified into this concept.

Risk profile

How the MIT AI Risk Repository categorizes this risk.

Domain2. Privacy & Security
Subdomain2.1 > Compromise of privacy by leaking or correctly inferring sensitive information
Entity2 - AI
Intent2 - Unintentional
Timing3 - Other; 2 - Post-deployment
CategorySystemic risks
SubcategoryRisks to privacy

Merged risk records

Source records unified into this canonical risk concept.

2 recordsView all →

MITRISK-Bengio2025-60.03.05 - Risks to privacy

"General- purpose AI systems can cause or contribute to violations of user privacy. Violations can occur inadvertently during the training or usage of AI systems, for example through unauthorised processing of personal data or leaking health records used in training. But violations can also happen deliberately through the use of general- purpose AI by malicious actors; for example, if they use AI to infer private facts or violate security."

Domain2. Privacy & SecuritySubdomain2.1 > Compromise of privacy by leaking or correctly inferring sensitive informationSourceInternational AI Safety Report 2025Year2025

MITRISK-Bengio2024-49.03.05 - Risks to privacy

"General- purpose AI models or systems can ‘leak’ information about individuals whose data was used in training. For future models trained on sensitive personal data like health or financial data, this may lead to particularly serious privacy leaks. General- purpose AI models could enhance privacy abuse. For instance, Large Language Models might facilitate more efficient and effective search for sensitive data (for example, on internet text or in breached data leaks), and also enable users to infer sensitive information about individuals."

Domain2. Privacy & SecuritySubdomain2.1 > Compromise of privacy by leaking or correctly inferring sensitive informationSourceInternational Scientific Report on the Safety of Advanced AIYear2024

Mitigations

Defenses that may help with related attacks.

Showing 4 of 10

Source evidence

Research source for this risk, when available.