Human-Machine Networks: Towards a Typology and Profiling Framework
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.
Cite
@article{arxiv.1602.07199,
title = {Human-Machine Networks: Towards a Typology and Profiling Framework},
author = {Aslak Wegner Eide and J. Brian Pickering and Taha Yasseri and George Bravos and Asbjørn Følstad and Vegard Engen and Milena Tsvetkova and Eric T. Meyer and Paul Walland and Marika Lüders},
journal= {arXiv preprint arXiv:1602.07199},
year = {2023}
}
Comments
Pre-print; To be presented at the 18th International Conference on Human-Computer Interaction International, Toronto, Canada, 17 - 22 July 2016