Personalized assistance systems (PAS) provide real-time assistance tailored to individual users to improve efficiency in the workplace. PAS communicate dynamically with users through wearable computing devices. To deliver such personalized assistance, PAS need personal data from the individuals who wear them. However, concerns over data protection and security can negatively influence the extent to which users accept personalized assistance systems. The key aspects in this regard that the literature currently lacks include data protection law and the employee perspective. Hence, we develop seven design principles for PAS that respect user privacy through employee-determined approaches to data collection and use. We developed the principles based on a systematic literature review, user personas, privacy control, and European Union legal requirements for privacy by design and privacy by default. Our design principles, which we evaluated in a focus group and an expert workshop, provide a framework to help practitioners and software developers mitigate adoption barriers due to privacy concerns. Our study also contributes to the theoretical discussion of current developments in personalized assistance in the workplace by providing a new perspective on ensuring employees accept the required data collection and use.
Design Principles for Personalized Assistance Systems that Respect Privacy.
AIS Transactions on Human-Computer Interaction, 14(4), 461-489.
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