The Privacy-Utility Trade-Off in Artificial Intelligence Contexts

A Systematic Literature Review

Brîncoveanu, Witzki & Carl · Open Identity Summit 2026. Gesellschaft für Informatik e.V., Dresden, Germany ·
TL;DR: A systematic literature review investigating the conceptualization of the privacy-utility trade-off in the context of Artificial Intelligence.

While AI-driven technologies offer significant benefits like personalization and convenience, they simultaneously amplify privacy risks through extensive data collection. This creates a fundamental tension between the utility of a service and the privacy of its users.

To understand this challenge, we are conducting a systematic literature review to investigate how research conceptualizes this privacy-utility trade-off in AI contexts. Our analysis synthesizes findings on user attitudes, AI-specific risks, and the effectiveness of privacy-preserving technologies, aiming to identify critical gaps and provide recommendations for future theory, technology design, and policy.

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