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Abstract. In this paper we outline an initial typology and framework for the purpose of profiling human-machine networks, that is, collective structures where humans and machines interact to produce synergistic effects. Profiling a human-machine network along the dimensions of the typology is intended to facilitate access to relevant design knowledge and experience. In this way the profiling of an envisioned or existing human-machine network will both facilitate relevant design discussions and, more importantly, serve to identify the network type. We present experiences and results from two case trials: a crisis management system and a peer-to-peer reselling network. Based on the lessons learnt from the case trials we suggest potential benefits and challenges, and point out needed future work.

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This paper reports on an experiment investigating how the number of simultaneous users affects the usability and user experience of a shareable user interface. Participants were instructed to complete individual drawing tasks on a shareable user interface running on a multi-touch surface table. The results show an increase in performance (shorter task completion times) correlated to an increase in the number of simultaneous users. No significant increase in user errors was observed when the number of simultaneous users was increased. However, despite these quantitative improvements in usability, participants reported that the tasks were more challenging when multiple users were working together.