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Company Privacy Dashboards: Employee Needs and Requirements

: Polst, Svenja; Kelbert, Patricia; Feth, Denis


Moallem, A.:
HCI for cybersecurity, privacy and trust: First international conference, HCI-CPT 2019. Proceedings : Orlando, FL, USA, July 26-31, 2019
Cham: Springer, 2019 (Lecture Notes in Computer Science 11594)
ISBN: 978-3-030-22350-2
ISBN: 3-030-22350-7
ISBN: 978-3-030-22351-9
International Conference on HCI for Cybersecurity, Privacy and Trust (HCI-CPT) <1, 2019, Orlando/Fla.>
International Conference on Human-Computer Interaction <21, 2019, Orlando/Fla.>
Bundesministerium für Bildung und Forschung BMBF (Deutschland)
16KIS0898; TrUSD
Transparente und selbstbestimmte Ausgestaltung der Datennutzung im Unternehmen
Conference Paper
Fraunhofer IESE ()
Privacy; Privacy needs; Privacy requirements; Transparency; Self-determination; Privacy dashboard; Employee privacy

As work becomes increasingly digital, companies store and process more personally identifiable information of their employees. This is typically beneficial for both employees and employers, who take advantage of simplified digital work processes and tools. The problem is that there is typically no opt-out option for employees, and employers can misuse collected data for productiveness tracking and other analyses that might be problematic with regard to privacy. Furthermore, employees oftentimes do not know (lack of transparency) and cannot influence (lack of self-determination) which personally identifiable information the employer collects and uses. As a result, many employees have a variety of privacy concerns. While various online services have recently successfully implemented so-called “privacy dashboards” for their users, comparable services are virtually unknown in the workplace. In this paper, we present employees’ needs and requirements with regard to transparency and self-determination in the company context. The elicitation was based on a requirements model we introduce. We conducted two workshops with participants from four research institutes and one company. The results were compared to the state of the practice and used to build models that serve as a baseline for company privacy dashboards.