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/

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. 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

4. Our definition of Smart Cities
• Smart Sustainable Participatory Liveable Cities
• Energy-Efficient, Climate-Resilient, Health-
Promoting, Inclusive & Attractive by default

5. 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

6. Urban Machinery
• Urban Machinery [Hård & Misa
2008]
• Cities as knowledge hubs
• Driving dissemination, research,
innovation

7. Citizen involvement
• [Arnstein 69] Ladder of
participation
[https://commons.wikimedia.org/wiki/File:Ladder_of_citizen_participation,_Sheey_Arnstein.tif
User:DuLithgow]

8. 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]

9. (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

10. (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

11. (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

12. Related SM
• Lots of single-site social machines
• Towards higher complexity
– (e)Government [Tiropanis et al. 2014]
– Ecosystems
– The Web

13. 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]

14. 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

15. 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

16. 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/]

17. 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!