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Welcome to today’s What is the future for cities podcast and its Research episode, my name is Fanni, and today, I will introduce a research by summarizing it. The episode really is just a short summary of the original article, and in case it is interesting enough, I would encourage everyone to check out the whole article.
So, the second research episode is working with a 2011 research about intelligent cities. This article is often referenced as a basic piece in the research about the future of cities and it is one of the early articles highlighting the importance of community intelligence. Plus, the researcher also talks about how this community intelligence spatially centred in cities can be utilised. Therefore, I thought it would be good to understand how this spatial intelligence can be included in our cities.
Our summary today works with the article titled as Intelligent cities: Variable geometries of spatial intelligence from 2011 by Nicos Komninos. The article was published in Intelligent Buildings International journal to discuss the spatial intelligence of cities through different case studies for the different cases.
Komninos started off with two concerns, one being the rapid increase in number of self-defined smart and intelligent cities as their diversity also had increased with their numbers. This increase had led to simplistic use of the terms smart and intelligent, maybe utilising the marketing value behind them. However, according to Komninos, there was no clear understanding behind the terms’ ideology. The second was connected to the sheer diversification of strategies and applications reflecting the highly fragmented space of urban systems such as governance and operation, and the sea of applications just exacerbating this fragmentation.
According to Komninos, the “widespread adoption of intelligent city strategies requires some standardization and simplification, clear solutions that the public administration can choose from, a portfolio of solutions that offer documented benefits”. He aimed to describe some fundamental mechanisms of spatial intelligence that could be implemented among and within districts. Therefore, he identified intelligence of cities based on series of knowledge functions created collectively and deployed, using network-based information intelligence and prediction, technology learning and acquisition, collaborative innovation, product and service promotion, and dissemination.
The spatial intelligence of cities referred to the ability of a community using its own intellectual, institutional and infrastructural capital to solve problems and challenges. The spatial intelligence emerged from three types of intelligence: 1. The inventiveness, creativity and intellectual capital of the populace, 2. The collective intelligence of the institutions and social capital, and 3. The artificial intelligence of smart infrastructure, virtual environments and intelligent agents. Based on this research, in case cities were able to use their three types of intelligence combined, creating spatial intelligence, they would be able to respond effectively to changing conditions, situations and environments while providing the citizens’ prosperity and wellbeing.
Komninos used smart and intelligent cities interchangeably, and he argued that they had been a major breakthrough for the urban research area. Both concepts, smart and intelligent cities were dated back to the early 1990s, and since then, they had been widespread offering more optimistic perspective for cities linking the development to knowledge and innovation economy and the information society.
He also argued that two different forces had been driving the paradigm shift towards intelligent cities: first, the rising knowledge and innovation economy sustaining the global current economic development, and second, the spread of the Internet and major technological innovations. These two forces met in intelligent cities and the urban development had became dependent on these forces. As well, he pointed out that the digital aspects had joined to the original spatialities of cities including agglomeration, population, demography, infrastructure, and even regulation enhancing the others along the way.
Komninos also talked about cyber cities, knowledge-based cities and digital cities as predecessors of the intelligent city. In his understanding, the intelligent city uses the digital spaces improving urban ecosystems due to their information processing capacity while sustains learning, innovation and problem-solving within the community. Interestingly, smart city, for him, is the intelligent city with sustainable pursuits. However, he also acknowledged that the landscape for intelligent and smart cities seemed extremely complex and open to creativity and innovation. He also questioned what made a city smart or intelligent and which type of spatial intelligence could be activated within the different sectors and districts.
His case studies presented the three form of spatial intelligence: orchestration intelligence with Bletchley Park and the first intelligent community; amplification intelligence with Cyberport Hong Kong experimental facilities and infrastructure; and instrumentation intelligence with Amsterdam Smart City real-time decision-making processes across the districts.
Orchestration intelligence, backed up with the example of Bletchley Park UK, was based on collaboration and diversified community problem-solving. The city could use cooperation and integration of individual, social and machine intelligence. Cities using orchestration intelligence end up with higher intelligence including quicker responses, higher problem-solving capability, quality solutions and lower operation costs. Such systems may have to have the four essential characteristics of intelligent cities: a. creative population working in information and knowledge-intensive activities, b. institutions and routines for collaborations in knowledge creation and sharing, c. technological infrastructure for communication, data processing and information analysis, and d. a proven ability to innovate and solve problems that appear for the first time.
Amplification intelligence, presented with Cyberport Hong Kong, is based on people’s ability to up-skill by infrastructure, open platforms and experimental facilities. Citizens are involved in learning and innovation, through, for example, innovation universities or intelligent campuses. Thereby improving creativity, intelligence and inventiveness of the population, citizens are encouraged to become producers of services and innovations. These areas should not be seen simple technological areas, but ecosystems which nurture talent and turn it into startups. This setting enhances human capabilities and intelligence by simultaneously using hard urban infrastructure and soft digital technologies and services.
Instrumentation intelligence, showed through Amsterdam Smart City Project is based on better decision making across districts based on real-time information, data analysis and predictive models. Instrumentation intelligence with interconnections producing data to help decision-making processes might be able to help cities to achieve their goals – such as lower energy use and cut city traffic.
Orchestration, amplification and instrumentation intelligence illustrated different paths of spatial intelligence leading to more efficient cities. These are based on different collaborations and integration, and spatial intelligence enabled by these creates more efficient cities by improving the innovation ecosystems of industry, commerce, services, transport and utilities that operate within cities. Further development could include, for instance, sustainability, and even Komninos stated that there were at least 20 different domains of cities as potential fields for smart or intelligent cities. However, he also acknowledged: “either smart cities are not well targeted on city challenges, solutions are more technology push than demand driven, or cities have not efficiently implemented spatial intelligence and with all the technology, cities actually are not yet sufficiently intelligent”.
He finished with the restatement that we still lack a deeper understanding of what makes a city smart or intelligent, meaning, that at that time, we were still rather in the digital city era than in the intelligent and smart city period. He suggested to focus on more collaborative, innovative and engaging solutions involving all available intelligence for urban areas.
As the most important things, I would like to highlight 3 aspects: 1. Cities have spatial intelligence which are the combination of human intelligence, community intelligence, and machine intelligence and their collaboration, 2. The different combinations of these can result in very different, but not wrong solutions, and 3. That we are not there yet –cities do not yet seem to be sufficiently intelligent – so there is way to go ahead.
Additionally, it would be great to talk about the following questions: 1. If we agree on that each city’s interpretation on these concepts will differ, why do we keep finding one definition to fit all cities? 2. What is the final destination for cities or is there one? He seemed to be torn apart between smart and intelligent cities, but at the end he also said that using the spatial intelligence should at some point result in effective cities.
What was the most interesting part for you? What questions did arise for you? Do you have any follow up questions? Let me know on Twitter @WTF4Cities or on the website where the transcripts and show notes are available! I hope this was an interesting research for you as well, and thanks for tuning in!
What is The Future for Cities? Podcast 
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