Startupfest 2014 - Cities are one of humankind's greatest inventions. More than four thousands years ago, we began the process of separating ourselves from the forces of natural Darwinism. By concentrating large numbers of people with wide ranges of interests, beliefs, and skills into high density living, we created the framework for driving forward our civilization. In the 21st century we will come close to completing our evolution into a species of city dwellers. Since 2008 more than 50% of us live in urban areas and by 2050 predictions suggest reaching 80%. To achieve this the world will build in the 21st century as much new urban infrastructure as existed at the end of the 20th century. We are entering the Age of Cities.
However, architects, urban planners, public administrators, agency leaders and many other stakeholders in urban living struggle to understand the impact that Information Technology will have on cities. Their thinking is naturally rooted in the permanence and immutability of concrete and steel and in 19th century organizational methods. But we live now in the Age of Intelligent Systems, which we expect to have characteristics such as awareness, responsiveness, adaptation, personalization, and so forth. In the smart cities movement the Internet of Things is instrumenting a myriad flows of information in cities. How can we leverage the new visibility of these flows to help cities evolve into intelligent systems? How can we re-invent how we live together in cities?
In this talk Distinguished Engineer Emeritus and inventor of IBM’s Smarter Cities architecture, Dr Colin Harrison, will share observations of these trends and offer suggestions for a wide range of start up opportunities based on viewing cities as intelligent systems that touch all of our lives.
2. A few successes and (mostly) failures
• Successes
– 1974 Distributed, real-time control system (CERN)
– 1978 First clinical MRI system (EMI)
– 1992 Mobile Wi-Fi MAC-Link protocol
– 2008 Smart Cities Architecture
– … and so forth
• Failures
– 1980 Magnetic Bubble Memory
– 1985 Medical Imaging business
– 1993 Mobile Web
– 1996 Intelligent Agents
– 2003 eLearning
– … and so forth
9. Fig. 1 Scaling of urban infrastructure and socioeconomic output.(A) Total lane miles (volume)
of roads in U.S. metropolitan areas (MSAs) in 2006 (blue dots).
L M A Bettencourt Science 2013;340:1438-1441
Published by AAAS
10. Invention scales faster than population
Metropolitan Patenting, Inventor Agglomeration and Social Networks: A Tale of Two Effects by Deborah Strumsky,
José Lobo, Lee Fleming
12. The Urbanisation-Innovation Challenge
1. Today 3-4 bn people live in cities
2. Some 200,000 people per week migrate into cities and
increase their resource consumption (become richer)
3. If nothing changes, by 2100 we expect to add another 3-4
bn urban residents
4. If nothing changes, there will not be sufficient water, food,
and raw materials for that urban population
5. Not to mention the environmental impact
6. Implicitly, we are assuming that we will innovate our way
out of this problem
7. The size of the “innovation gap” is hot research topic
Cities exist to enable humanity to live closely together, to share resources and infrastructures, to collaborate in producing value, to accumulate and generate information and knowledge, to encounter different cultures
Historically information was developed by people and maintained by written documents. Exchange of knowledge was facilitated by proximity but also protected by guilds and secrecy. Communication was by word of mouth. Later by books and newspapers. In the 20th century by mass media. Today by information systems.
It began with record keeping. The oldest written documents – such as the Linear A and Linear B tablets – concern bookkeeping. Cities and city governments – together with the established churches became the keepers of records, of history. Still a central role of government to record births and deaths, ownership of property, payment of taxes, issuance of licences. These records served additionally to understand the growth or decline of the city
But in the 21st Century, the Age of Information is not merely about record keeping or even incremental improvements in planning and operations…
New technologies are usually initially applied to extend some existing technology – cars as horse-drawn carriages, telephones as substitutes for telegrams, electricity as a substitute for water or steam power. Powerful technologies quickly go beyond extension to transformation and often destroy their technological antecedents.
ICT is such a transformational technology…Yes, it can incrementally improve the way we lived at the close of the 20th century. But that is only a beginning. ICT will change the way that we live together and the ways that cities work.
Cities are competitive environments and that competition extends to all the dimensions of human life <click>. We are here because we want more than we could get by staying on the farm. Successful life in the city depends on capturing, producing, storing, communicating, interpreting, combining information in order to make better decisions more quickly about all of these concerns.
Substituting processes of natural selection (Darwin) with artificial processes – the city is a collection of niches – high dimensional space whose dimensions are continually extended through innovation. As individuals we compete for the “best” niche we can gain and hold. Through innovation we may be able to create a new niche for ourselves – cf my career with IBM. If we continue to innovate we may move from that niche to yet another new one, leaving a vacant niche behind.
Likewise, cities also engage in the same kind of competition with one another – seeking to develop and hold valuable niches.
Scaling of urban infrastructure and socioeconomic output.(A) Total lane miles (volume) of roads in U.S. metropolitan areas (MSAs) in 2006 (blue dots). Data for 415 urban areas were obtained from the Office of Highway Policy Information from the Federal Highway Administration (14). Lines show the best fit to a scaling relation(red), with [95% confidence interval (CI), R2 = 0.65]; the theoretical prediction, β = 5/6 (yellow); and linear scaling β = 1 (black). (B) Gross metropolitan product of MSAs in 2006 (green dots). Data obtained for 363 MSAs from U.S. Bureau of Economic Analysis (14). Lines describe best fit (red) to data, β = 1.126 ± 0.023 (95% CI, R2 = 0.96); the theoretical prediction, β = 7/6 (yellow); and proportional scaling, β = 1 (black). The two best-fit parameters in each scaling relation were estimated by means of ordinary least-squares minimisation to the linear relation between logarithmically transformed variables (14). The inset shows the estimate of G for 313 U.S. MSAs and the conservation law(). G is measured as the product of gross domestic product and road volume, both per capita. As predicted by the theory, observed values of G for different cities cluster around its most likely value (mode, yellow line), which gives an estimate of the optimum and are bounded by the maximum (green line); see also Fig. 2B. Several metropolitan areas, such as Bridgeport, Connecticut (green circle); Riverside, California (yellow circle); or Brownsville, Texas (red circle), are outliers, suggesting that they are suboptimal in terms of their transportation efficiency or amount of social mixing.