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Privacy violations

Sociotechnical Harms of Algorithmic Systems: Scoping a Taxonomy for Harm Reduction

Shelby et al. (2023)

Sub-category

Risk Domain

2.1Compromise of privacy by leaking or correctly inferring sensitive information

AI systems that memorize and leak sensitive personal data or infer private information about individuals without their consent. Unexpected or unauthorized sharing of data and information can compromise user expectation of privacy, assist identity theft, or cause loss of confidential intellectual property.

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(p. 732)

Entity— Who or what caused the harm

Human

Due to a decision or action made by humans

AI system

Due to a decision or action made by an AI system

Other

Due to some other reason or is ambiguous

Intent— Whether the harm was intentional or accidental

Intentional

Due to an expected outcome from pursuing a goal

Unintentional

Due to an unexpected outcome from pursuing a goal