Human-Machine Networks: Towards a Typology and Profiling Framework
This work addresses the need for structured approaches to analyze and design collective systems where humans and machines interact, though it appears incremental as it builds on existing concepts without major breakthroughs.
The paper tackled the problem of understanding and designing human-machine networks by proposing an initial typology and profiling framework, and demonstrated its application through two case trials in crisis management and peer-to-peer reselling.
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.