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Collective Intelligence and Algorithmic Governance of Socio-Technical Systems

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Social Collective Intelligence

Part of the book series: Computational Social Sciences ((CSS))

Abstract

In applying the methodology of sociologically-inspired computing to the idea of self-governing institutions for common-pool resource management, an algorithmic basis for self-organising resource allocation in open computer systems and networks has been established. This algorithmic base is not intended to be a testable model of how people manage decentralised resource allocation: on the other hand, it does raise the issue of: what happens when these computer models are made manifest in socio-technical systems for management of resources like energy, water, transport, and so on. This chapter investigates this issue from the perspective of decentralised Community Energy Systems, in which societies of people and societies of ‘agents’ are interleaved in a form of collective social intelligence. Two systems for demand-side self-organisation are presented, one based on collective awareness in a ‘serious game’, the other based on representation and reasoning with an electronic form of social capital. These systems suggest an implementation route for socio-technical systems, comprising both people and agents, in which ‘fair’ treatment of people is grounded in algorithms executed by the agents.

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Acknowledgements

This research has been partially supported by the UK EPSRC Grand Challenge project No. EP/I031650/1.

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Authors and Affiliations

  1. Department of Electrical & Electronic Engineering, Imperial College London, London, SW7 2BT, UK

    Jeremy Pitt, Dídac Busquets, Aikaterini Bourazeri & Patricio Petruzzi

Authors
  1. Jeremy Pitt
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  2. Dídac Busquets
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  3. Aikaterini Bourazeri
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  4. Patricio Petruzzi
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Corresponding author

Correspondence to Jeremy Pitt .

Editor information

Editors and Affiliations

  1. CREATE-NET, Trento, Italy

    Daniele Miorandi

  2. University of Trento, Trento, Italy

    Vincenzo Maltese

  3. School of Informatics Informatics, The University of Edinburgh, Edinburgh, United Kingdom

    Michael Rovatsos

  4. Faculty EEMCS, University of Twente, Enschede, The Netherlands

    Anton Nijholt

  5. The University of Edinburgh, Edinburgh, United Kingdom

    James Stewart

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Pitt, J., Busquets, D., Bourazeri, A., Petruzzi, P. (2014). Collective Intelligence and Algorithmic Governance of Socio-Technical Systems. In: Miorandi, D., Maltese, V., Rovatsos, M., Nijholt, A., Stewart, J. (eds) Social Collective Intelligence. Computational Social Sciences. Springer, Cham. https://doi.org/10.1007/978-3-319-08681-1_2

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  • DOI: https://doi.org/10.1007/978-3-319-08681-1_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-08680-4

  • Online ISBN: 978-3-319-08681-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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