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Privacy Violations

AI Risk

Privacy violation occurs when algorithmic systems diminish privacy, such as enabling the undesirable flow of private information [180], instilling the feeling of being watched or surveilled [181], and the collection of data without explicit and informed consent... privacy violations may arise from algorithmic systems making predictive inference beyond what users openly disclose [222] or when data collected and alg...

Overview

A source-backed snapshot of this AI risk.

Privacy violation occurs when algorithmic systems diminish privacy, such as enabling the undesirable flow of private information [180], instilling the feeling of being watched or surveilled [181], and the collection of data without explicit and informed consent... privacy violations may arise from algorithmic systems making predictive inference beyond what users openly disclose [222] or when data collected and algorithmic inferences made about people in one context is applied to another without the person’s knowledge or consent through big data flows

Techniques3Attack methods connected to this risk.
Mitigations7Defenses 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
Intent3 - Other; 2 - Unintentional
Timing2 - Post-deployment
CategoryInterpersonal Harms; Informational Risks
SubcategoryPrivacy Violations

Merged risk records

Source records unified into this canonical risk concept.

2 recordsView all →

MITRISK-Shelby2023-11.04.04 - Privacy violations

Privacy violation occurs when algorithmic systems diminish privacy, such as enabling the undesirable flow of private information [180], instilling the feeling of being watched or surveilled [181], and the collection of data without explicit and informed consent... privacy violations may arise from algorithmic systems making predictive inference beyond what users openly disclose [222] or when data collected and algorithmic inferences made about people in one context is applied to another without the person’s knowledge or consent through big data flows

Domain2. Privacy & SecuritySubdomain2.1 > Compromise of privacy by leaking or correctly inferring sensitive informationSourceSociotechnical Harms of Algorithmic Systems: Scoping a Taxonomy for Harm ReductionYear2023

MITRISK-Perlo2025-70.02.01 - Privacy Violations

"EAI systems interact with huge amounts of data, creating significant privacy concerns. These systems are often trained on vast corpora and process a variety of data modalities— spanning visual, auditory, and tactile information—during deployment [12]. Like text-based virtual AI models, which are known to memorize and expose personally identifiable information [75, 76], commercial robots have been shown to disclose proprietary information through simple prompts [61]."

Domain2. Privacy & SecuritySubdomain2.1 > Compromise of privacy by leaking or correctly inferring sensitive informationSourceEmbodied AI: Emerging Risks and Opportunities for Policy ActionYear2025

Mitigations

Defenses that may help with related attacks.

Showing 4 of 7

Source evidence

Research source for this risk, when available.