Trustworthy Transparency by Design
Valentin Zieglmeier, Alexander Pretschner

TL;DR
This paper proposes a technical framework for embedding transparency into software design to enhance user trust and data sovereignty, supported by an empirical focus group study.
Contribution
It introduces a novel transparency framework for software, integrating user trust research, and empirically evaluates its effectiveness over three months.
Findings
Participants found the transparency beneficial and empowering.
The framework satisfies usability and trustworthiness requirements.
Empirical evaluation confirms improved user trust and understanding.
Abstract
Individuals lack oversight over systems that process their data. This can lead to discrimination and hidden biases that are hard to uncover. Recent data protection legislation tries to tackle these issues, but it is inadequate. It does not prevent data misusage while stifling sensible use cases for data. We think the conflict between data protection and increasingly data-based systems should be solved differently. When access to data is given, all usages should be made transparent to the data subjects. This enables their data sovereignty, allowing individuals to benefit from sensible data usage while addressing potentially harmful consequences of data misusage. We contribute to this with a technical concept and an empirical evaluation. First, we conceptualize a transparency framework for software design, incorporating research on user trust and experience. Second, we instantiate and…
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Taxonomy
TopicsPrivacy, Security, and Data Protection · Privacy-Preserving Technologies in Data · Ethics and Social Impacts of AI
