Trustworthy Transparency by Design

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 empirically evaluate the framework in a focus group study over three months, centering on the user perspective. Our transparency framework enables developing software that incorporates transparency in its design. The evaluation shows that it satisfies usability and trustworthiness requirements. The provided transparency is experienced as beneficial and participants feel empowered by it. This shows that our framework enables Trustworthy Transparency by Design

Decentralized Inverse Transparency With Blockchain

Employee data can be used to facilitate work, but their misusage may pose risks for individuals. Inverse transparency therefore aims to track all usages of personal data, allowing individuals to monitor them to ensure accountability for potential misusage. This necessitates a trusted log to establish an agreed-upon and non-repudiable timeline of events. The unique properties of blockchain facilitate this by providing immutability and availability. For power asymmetric environments such as the workplace, permissionless blockchain is especially beneficial as no trusted third party is required. Yet, two issues remain: (1) In a decentralized environment, no arbiter can facilitate and attest to data exchanges. Simple peer-to-peer sharing of data, conversely, lacks the required non-repudiation. (2) With data governed by privacy legislation such as the GDPR, the core advantage of immutability becomes a liability. After a rightful request, an individual's personal data need to be rectified or deleted, which is impossible in an immutable blockchain. To solve these issues, we present Kovacs, a decentralized data exchange and usage logging system for inverse transparency built on blockchain. Its new-usage protocol ensures non-repudiation, and therefore accountability, for inverse transparency. Its one-time pseudonym generation algorithm guarantees unlinkability and enables proof of ownership, which allows data subjects to exercise their legal rights regarding their personal data. With our implementation, we show the viability of our solution. The decentralized communication impacts performance and scalability, but exchange duration and storage size are still reasonable. More importantly, the provided information security meets high requirements. We conclude that Kovacs realizes decentralized inverse transparency through secure and GDPR-compliant use of permissionless blockchain.Comment: Peer-reviewed version accepted for publication in ACM Distributed Ledger Technologies: Research and Practice (DLT). arXiv admin note: substantial text overlap with arXiv:2104.0997

Increasing Employees' Willingness to Share: Introducing Appeal Strategies for People Analytics

Increasingly digital workplaces enable advanced people analytics (PA) that can improve work, but also implicate privacy risks for employees. These systems often depend on employees sharing their data voluntarily. Thus, to leverage the potential benefits of PA, companies have to manage employees' disclosure decision. In literature, we identify two main strategies: increase awareness or apply appeal strategies. While increased awareness may lead to more conservative data handling, appeal strategies can promote data sharing. Yet, to our knowledge, no systematic overview of appeal strategies for PA exists. Thus, we develop an initial taxonomy of strategies based on a systematic literature review and interviews with 18 experts. We describe strategies in the dimensions of values, benefits, and incentives. Thereby, we present concrete options to increase the appeal of PA for employees.Comment: Peer-reviewed version accepted for publication in the proceedings of the 13th International Conference on Software Business (ICSOB 2022

Rethinking People Analytics With Inverse Transparency by Design

Employees work in increasingly digital environments that enable advanced analytics. Yet, they lack oversight over the systems that process their data. That means that potential analysis errors or hidden biases are hard to uncover. Recent data protection legislation tries to tackle these issues, but it is inadequate. It does not prevent data misusage while at the same time stifling sensible use cases for data. We think the conflict between data protection and increasingly data-driven systems should be solved differently. When access to an employees' data is given, all usages should be made transparent to them, according to the concept of inverse transparency. This allows individuals to benefit from sensible data usage while addressing the potentially harmful consequences of data misusage. To accomplish this, we propose a new design approach for workforce analytics we refer to as inverse transparency by design. To understand the developer and user perspectives on the proposal, we conduct two exploratory studies with students. First, we let small teams of developers implement analytics tools with inverse transparency by design to uncover how they judge the approach and how it materializes in their developed tools. We find that architectural changes are made without inhibiting core functionality. The developers consider our approach valuable and technically feasible. Second, we conduct a user study over three months to let participants experience the provided inverse transparency and reflect on their experience. The study models a software development workplace where most work processes are already digital. Participants perceive the transparency as beneficial and feel empowered by it. They unanimously agree that it would be an improvement for the workplace. We conclude that inverse transparency by design is a promising approach to realize accepted and responsible people analytics.Comment: Peer-reviewed version accepted for publication in Proceedings of the ACM on Human-Computer Interaction (PACMHCI), CSCW issue. Note: The introduction and motivation of this paper have evolved from arXiv:2103.10769, but the remainder is new. We keep the old paper online as they differ substantiall

Leading Agents or Stewards? Exploring Design Principles for Empowerment through Workplace Technologies

Workplace technologies lead to increasing levels of transparency for managers and employees. On the one hand, transparency facilitates novel styles of work, but on the other hand, it drives employee privacy concerns. Despite the technical possibilities to monitor employees, workforce demands empowerment leadership and challenges the assumptions from agency theory. Thus, following a design science research process and collaborating closely with the software provider SoftCo over three years, we aim to develop a suitable technical solution to the changing needs. We build on the knowledge base of stewardship theory, the concept of transparency, and existing market solutions. The design cycles are driven by literature search and empirical investigations, such as qualitative interviews at SoftCo. In this research-in-progress paper, we derive design requirements, design principles, and design features for digital leadership innovations that facilitate stewardship behavior and outline our further research agenda