Illbook is a big data system that predicts when employees are about to get sick. Illbook is the outcome of a speculative design project exploring the opportunities as well as the tensions brought about by the big data paradigm, specifically as they pertain to human resource management and medical prediction tools.

Illbook exists as a design specification. It brings together existing data sources about employees—such as, their email and phone communication, location data, restaurant check-ins, health history, etc.—and data outside the workplace, such as weather conditions, spread of contagious diseases like the flu, etc. The system’s functionality is driven by its predictions of employees’ likelihood of getting sick. This information is available to management as well as employees and is used for a diverse range of automated actions from human resource management to the organization of day-to-day operations. Such automated actions include canceling and rescheduling meetings, changing the office layout and the desk assignment to minimize illness and thus increase productivity, compute who is most likely to spread illness into the office, etc.

Through speculative scenarios depicting Illbook’s use cases, this work exposes policy issues that need to be addressed around data and employment regulations as it makes visible tensions between efficiency and usefulness on the one hand and privacy and data ownership on the other. Furthermore, the designs reveal tensions around the stories that can be told about our bodies based on our digital traces.

Illbook was featured recently in an SVT program on big data.

Contact and project leader: Lucian Leahu, assistant professor at the IT University of Copenhagen; llea@itu.dk