The New Metropolitan Discipline: Inception Lectures

2023

Cities of the Future Jacobs's critique of urban planning and her suggestions for improving cities flow from an analytical framework based on a set of coherent socioeconomic insights. These are, namely, that a city is an institution indispensable for peacefully coordinating the plans of myriad, self-interested strangers with imperfect knowledge; that a city is a natural unit of economic analysis, the principal locus of innovation, a system of organized complexity, and a spontaneous order; that locals tend to know better than outsiders about the problems and opportunities, large and small, in their own urban milieu; and that with limited outside guidance ordinary people can cooperatively and effectively address them with intelligence, resourcefulness, and creativity. In the last chapter we examined the limits of urban micro-interventions from this framework. Here I would like to address a different but related set of questions: To what extent is it feasible to consciously plan for "urban vitality," i.e., to promote or foster the experimentation and creativity essential for a real, living city? How much political authority do we need to accomplish this? How workable are some of the recent, imaginative proposals for city planning and rebuilding when we view it through a Jacobs-cum-market-process or Market Urbanist lens?

Smart Innovation, Systems and Technologies, 2019

The Smart Innovation, Systems and Technologies book series encompasses the topics of knowledge, intelligence, innovation and sustainability. The aim of the series is to make available a platform for the publication of books on all aspects of single and multi-disciplinary research on these themes in order to make the latest results available in a readily-accessible form. Volumes on interdisciplinary research combining two or more of these areas is particularly sought. The series covers systems and paradigms that employ knowledge and intelligence in a broad sense. Its scope is systems having embedded knowledge and intelligence, which may be applied to the solution of world problems in industry, the environment and the community. It also focusses on the knowledge-transfer methodologies and innovation strategies employed to make this happen effectively. The combination of intelligent systems tools and a broad range of applications introduces a need for a synergy of disciplines from science, technology, business and the humanities. The series will include conference proceedings, edited collections, monographs, handbooks, reference books, and other relevant types of book in areas of science and technology where smart systems and technologies can offer innovative solutions. High quality content is an essential feature for all book proposals accepted for the series. It is expected that editors of all accepted volumes will ensure that contributions are subjected to an appropriate level of reviewing process and adhere to KES quality principles.

Foresight, 2016

Cambridge University Press eBooks, 2018

DYNA

Emerging serious games mark the beginning of a new era in video games. Emerging serious games introduce advances in distributed artificial intelligence into their design in order to guide the player’s manipulation of a specific subject in an adaptive way. In this article, we present a city simulator game, called Metropolis, which generates emergent properties. Metropolis can be used by a smart city for city planning, to make collective decisions, and for other purposes. This paper describes why Metropolis can be classified as a serious game. It also analyzes how its emergent properties can be used for managing a smart city, and especially how it promotes e-participation as an e-decision-making tool within the context of urban planning. In addition, this paper explores how Metropolis can be used to analyze a smart city’s emergent citizen and urban patterns (urban spatial distribution) based on strong e-participation.

Artificial Intelligence and the City: Urbanistic Perspectives on AI, 2023

Innovation in artificial intelligence (AI) is transforming cities in unprecedented ways. Robots are increasingly managing key urban services, performing jobs that were once the exclusive domain of humans and maintaining the infrastructure of cities (Lynch et al., 2022; Macrorie et al., 2021). Self-driving cars are reshaping urban transport systems, thereby triggering new mobilities that impact the design of the built environment (Cugurullo et al. 2021; Dowling and McGuirk, 2022). City brains and digital platforms are gradually reengineering the practice of urban governance by operating entire urban systems that range from health to transport and from security to ecosystems (Caprotti and Liu, 2020; Curran and Smart, 2021; Marvin et al., 2022). Meanwhile, through mobile apps and personal computers, invisible software agents are sifting and sorting urban lives, for instance, deciding which residents to quarantine and which residents qualify for a mortgage (Kitchin, 2020; Lee and Floridi, 2021). In essence, the advent of AI introduces multiple non-biological intelligences that act upon and within cities. For the first time in history, the control of the city is not determined exclusively by humans. It is also influenced by AIs whose logics and actions sometimes might diverge significantly from ours (Cugurullo, 2021; Russell, 2019). We are witnessing the beginning of a new and uncertain urban era, replete with risks and opportunities. In di erent spaces and through diverse modalities, AIs and urban systems are converging at a rapid pace (Amoore, 2023; Son et al., 2023; While et al., 2021; Yigitcanlar et al., 2022). The urban changes associated with AI are challenging to describe and analyse in theoretical and empirical terms. There

ISPRS International Journal of Geo-Information

In urban planning, a common unit of measure for housing density is the number of households per hectare. However, the actual size of the physical space occupied by a household, i.e., a dwelling, is seldom considered, neither in 2D nor in 3D. This article proposes a methodology to estimate the average size of a dwelling in existing urban areas from available open data, and to use it as one of the design parameters for new urban-development projects. The proposed unit of measure, called “living space”, includes outdoor and indoor spaces. The idea is to quantitatively analyze the city of today to help design the city of tomorrow. First, the “typical”-dwelling size and a series of Key Performance Indicators are computed for all neighborhoods from a semantic 3D city model and other spatial and non-spatial datasets. A limited number of neighborhoods is selected based on their similarities with the envisioned development plan. The size of the living space of the selected neighborhoods is s...

Cities

Clearly with the rapid urbanization of nations throughout the world, a new framework for dealing with this growth is needed. Ortiz offers a compelling case for consideration and implementation of the Metro-Matrix method and places this in the context of urban planning history, the recent experience of developing cities and a theoretical base for decision-making and governance.

Artificial Intelligence and the City: Urbanistic Perspectives on AI, 2023

The era of urban artificial intelligences has begun. It is already di cult to imagine urban futures without artificial intelligence (AI). As the previous chapters have empirically shown, AI is being strongly integrated into the nature, character and functioning of urban spaces. Cities, in particular, are increasingly absorbing large volumes of AI technology into their transport, government and economic portfolios, triggering urban transformations of rare impetus. The technology in question is new, but the type of techno-urban symbiosis that we are now witnessing runs deep in the history of the city. For example, the reverberations of the introduction of combustion engines into the urban environment at the end of the nineteenth century are still echoing (Hall, 2014). Likewise, when the digital revolution of the 1970s transformed society's fundamental dynamics, the changes wrought on urban systems continued this momentum of sociotechnical change (Castells, 2011; Graham and Marvin, 2002). In essence, urban history tells us that significant technological innovations carry substantial and long-standing urban changes with them. Today, in the belief that 'AI is the new electricity,' entrepreneurs and politicians from all over the world position AI as a great technological innovation (see Lee, 2018: 25). As urbanists, we expect such positioning to drive ongoing changes in the fabric of cities for many years to come. This volume has clarified the urbanity of AI, revealing the urban as a space where multiple AIs become prominently visible, materially situated in the physical landscape and imbricated in everyday life. The contributors have identified several key reasons for the growth of AI in urban spaces, thereby shedding light on the drivers of the urban AI phenomenon which in recent CONCLUSIONS