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Understanding Smart Cities as Social Machines
Dirk Ahlers, Patrick Driscoll, Erica Lofstrom, John Krogstie, Annemie Wyckmans
NTNU – Norwegian University of Science and Technology
SOCM2016 Workshop @ WWW2016
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
Our definition of Smart Cities
• Smart Sustainable Participatory Liveable Cities
• Energy-Efficient, Climate-Resilient, Health-Promoting, Inclusive & Attractive by default
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
Urban Machinery
• Urban Machinery [Hård & Misa2008]
• Cities as knowledge hubs
• Driving dissemination, research, innovation
Citizen involvement
• [Arnstein 69] Ladder of participation
[https://commons.wikimedia.org/wiki/File:Ladder_of_citizen_participation,_Sheey_Arnstein.tifUser:DuLithgow]
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]
(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
(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
(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
Related SM
• Lots of single-site social machines
• Towards higher complexity
– (e)Government [Tiropanis et al. 2014]
– Ecosystems
– The Web
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]
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
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
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/]
Contact
search://Dirk Ahlers
geo: 63°25‘10“N 10°24‘9“E
@dirkahlers
http://smartsustainablecities.org/
Let’s talk!
