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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.

Category

Academic article

Language

English

Author(s)

  • Aslak Wegner Eide
  • J Brian Pickering
  • Taha Yasseri
  • George Bravos
  • Asbjørn Følstad
  • Vegard Engen
  • Milena Tsvetkova
  • Eric T Meyer
  • Paul Walland
  • Marika Lüders

Affiliation

  • SINTEF Digital / Sustainable Communication Technologies
  • University of Southampton
  • University of Oxford
  • Greece

Year

2016

Published in

Lecture Notes in Computer Science (LNCS)

ISSN

0302-9743

Publisher

Springer

Volume

9731

Page(s)

11 - 22

View this publication at Cristin