Human-machine networks: Towards a typology and profiling framework

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Authors: Eide, A.W., Pickering, J.B., Yasseri, T., Bravos, G., Følstad, A., Engen, V., Tsvetkova, M., Meyer, E.T., Walland, P. and Lüders, M.

http://eprints.bournemouth.ac.uk/33673/

Journal: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volume: 9731

Pages: 11-22

eISSN: 1611-3349

ISBN: 9783319395098

ISSN: 0302-9743

DOI: 10.1007/978-3-319-39510-4_2

© Springer International Publishing Switzerland 2016. 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 humanmachine 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 peerto- 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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