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Understanding Smart Cities as Social Machines

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Presentation at the 4th International Workshop on the Theory and Practice of Social Machines SOCM2016 at WWW2016.
Paper is here:
http://www2016.net/proceedings/companion/p759.pdf
More details: http://www.informatik.uni-oldenburg.de/~there/

Published in: Science
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Understanding Smart Cities as Social Machines

  1. 1. Understanding Smart Cities as Social Machines Dirk Ahlers, Patrick Driscoll, Erica Löfström, John Krogstie, Annemie Wyckmans NTNU – Norwegian University of Science and Technology SOCM2016 Workshop @ WWW2016
  2. 2. Cities and Smart Cities • Cities are interesting and complex • Mixing place for people and technology • Increased adaptation pressure • Reinvention, sustainability • Data-driven operation • Smart City concepts as a driver • Integration of ICT into services, operation, and planning
  3. 3. Our definition of Smart Cities • Smart Sustainable Participatory Liveable Cities • Energy-Efficient, Climate-Resilient, Health- Promoting, Inclusive & Attractive by default
  4. 4. Megamachines • [Mumford 67] City as a singular convergence of technics, politics, civilization • Complex social process • City-as-megamachine • [May 2000] Information Society as mega-machine
  5. 5. Urban Machinery • Urban Machinery [Hård & Misa 2008] • Cities as knowledge hubs • Driving dissemination, research, innovation
  6. 6. Citizen involvement • [Arnstein 69] Ladder of participation [https://commons.wikimedia.org/wiki/File:Ladder_of_citizen_participation,_Sheey_Arnstein.tif User:DuLithgow]
  7. 7. Criteria for Social Machines • Social processes, merged with computation, happening on the Web • “social participation with machine-based computation” [Smart et al. 2014] • “Web-based socio-technical systems in which the human and technological elements play the role of participant machinery” [Smart, Shadbolt 2014]
  8. 8. (1) Social Processes • Cities as socio-technical organisms • Society arises from social processes • Cities are crystallisation points of societal issues and transformation processes. • Modern city planning approaches value such influences • Cities run complementary to human social processes and within human social and societal environments • Citizen involvement
  9. 9. (2) Machine-based computation • City operation as a background process • IoT as enabler • Integration of separate systems that make up the city • Official, inofficial, and global systems – Cf. e-services, neighbor meetups, OSM
  10. 10. (3) Web-based • Smart Cities are partially Web-based • Features and aspects arise on the Web • Smart Cities can be managed through IoT • Not all of the Social Machine that is a Smart City is very obvious on the Web • Even factors that operate rather invisible under the surface are used to make an impact • Enables participatory and collaborative aspects
  11. 11. Related SM • Lots of single-site social machines • Towards higher complexity – (e)Government [Tiropanis et al. 2014] – Ecosystems – The Web
  12. 12. Complexity • Smart City as a system of systems • Smart City as the Social Machine of an ecosystem of Social Machines • System surfaces are manifestations of the city • Multiple abstraction levels • Combination of official/ inofficial and local/global social machines [https://commons.wikimedia.org/wiki/File:Social_Network_Analysis_Visualization.png User:SlvrKy]
  13. 13. Synthesis • Smart Cities as a complex ecosystem at different levels of components, systems, and system- of- systems • Social Machines evolved in interaction between system providers, users and machines • Smart City as a loosely integrated set of Social Machines in a digital ecosystem • A semi-controlled infrastructure with a number of data sources, application services, digital infrastructures needed to bring data and services to the users, and the users and citizens
  14. 14. Applications • Transformation to Smart Cities adds complexity • Bridge computer science and urban planning/architecture approaches • Interdisciplinary understanding • Drive observatory and Web Science/City science approaches • Urban computation and city analytics
  15. 15. Conclusion • Smart City as Social Machine – Thinking about complex urban issues – Inclusion of citizens – Improved social and societal view of the city – Bridging gaps within interdisciplinary teams [http://trondheim2030.no/2015/11/09/ny-tredimensjonal-modell-av-trondheim-gjor-det- enklere-a-planlegge-framtidas-by/]
  16. 16. Contact search://Dirk Ahlers geo: 63°25‘10“N 10°24‘9“E @dirkahlers dirk.ahlers@idi.ntnu.no http://smartsustainablecities.org/ Let’s talk!

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