Data Protection in Personalized AI Services: A Decentralized Approach

Christian Meurisch
2021
Advances in Artificial Intelligence (AI) have shaped today's user services, enabling enhanced personalization and new kinds of support. As such AI-based services -- referred to as AI services in this thesis -- necessarily involve (potentially sensitive) user data, the resulting privacy implications are de facto the unacceptable face of this technology: data once provided, e.g., to AI services typically running in the provider's cloud or on (third-party) edge devices, may be used for other
more » ... commercial) purposes than originally intended, even without the user's consent or awareness. While approaches to data protection are manifold, each of them makes a certain tradeoff between personalization, privacy, and applicability -- there is no practical one-size-fits-all solution. This thesis explores a data decentralization approach in the context of personalized (single-user) AI services to achieve a more favorable tradeoff for users while considering the providers' interests. As a result, this work comprises seven (7) major contributions, two for the systematic understanding of data protection and privacy requirements in AI services, and five technical contributions -- of the latter, three contribute protection mechanisms based on data decentralization and two pave the way for a decentralized (urban) operation. Specifically, the first contribution presents a user study that explores user expectations of such data-demanding AI services and the extent to which privacy concerns arise. Based on these findings, the second contribution classifies the related work of data protection in AI services in a novel way, highlighting the identified research gaps -- some of which are addressed in this thesis, as outlined below. While data decentralization promises users more control over their own data, it entails issues related to both efficiency and the protection of the provider's intellectual property due to the need for locally running AI services; this part of the thesis contributes three building blocks to address these iss [...]
doi:10.26083/tuprints-00019355 fatcat:5yhxebta4jeo7bhfxrgbhfn324