51 research outputs found
Smart city as anti-planning in the UK
This is the author accepted manuscript. The final version is available from SAGE Publications via the DOI in this recordCritical commentaries have often treated the smart city as a potentially problematic ‘top down’ tendency within policy-making and urban planning, which appears to serve the interests of already powerful corporate and political actors. This article, however, positions the smart city as significant in its implicit rejection of the strong normativity of traditional technologies of planning, in favour of an ontology of efficiency and emergence. It explores a series of prominent UK smart city initiatives (in Bristol, Manchester and Milton Keynes) as bundles of experimental local practices, drawing on the literature pointing to a growing valorisation of the ‘experimental’ over strong policy commitments in urban governance. It departs from this literature, however, by reading contemporary ‘smart experiments’ through Shapin and Schafer’s work on the emergence of 17th-century science, to advance a transhistorical understanding of experimentation as oriented towards societal reordering. From this perspective, the UK smart city merits attention primarily as an indicator of a wider set of shifts in approaches to governance. Its pragmatic orientation sits uneasily alongside ambitions to ‘standardise’ smart and sustainable urban development; and raises questions about the conscious overlap between the stated practical ambitions of smart city initiatives and pre-existing environmental and social policies.This paper was supported by the Economic and Social Research Council (ESRC) [grant number
ES/L015978/1] “Smart eco-cities for a green economy: a comparative study of Europe and China”
The 15-minute city as paranoid urbanism: ten critical reflections
The 15-minute city has emerged as a key urban development theme in recent years, and especially since the Covid-19 pandemic. It has also become a focus point for tensions and debates over future urban trajectories, including over the role of automobility as the key technology that defines the experience of the urban. While the 15-minute city has become a widely-used concept by proponents and detractors alike, it remains vaguely defined and heavily contested. The paper makes two contributions: first, it reads plans for, and debates around, the 15-minute city as a form of post-political urbanism. Secondly, the paper introduces the concept of paranoid urbanism as a way of understanding urban tensions and conflicts linked to mistrust, fear and paranoia in the post-pandemic city. This novel concept goes to the heart of debates and tensions over the shape of the post-pandemic city, and over mechanisms of exclusion and inclusion that characterise it. The arguments presented in the paper aim to both chart areas for further research, and as provide critical pointers for policymakers and practitioners working in the area of urban development. To this end, the paper presents ten critical reflections aimed at both policy and practice, and at establishing new avenues of research on paranoid urbanism in the post-pandemic era
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Why does urban Artificial Intelligence (AI) matter for urban studies? Developing research directions in urban AI research
New digital technologies and systems are being extensively applied in urban contexts. These technologies and systems include algorithms, robotics, drones, Autonomous Vehicles (AVs) and autonomous systems that can collectively be labelled as Artificial Intelligence (AI). Critical debates have recognized that these various forms of AI do not merely layer onto existing urban infrastructures, forms of management and practices of everyday life. Instead, they have social and material power: they perform work, anticipate and assess risks and opportunities, are aberrant or glitchy, cause accidents, and make new demands on humans as well as the design of cities. And yet, urban scholars have only recently started to engage with research on urban AI and to begin articulating research directions for urban development beyond the current focus on smart cities. To enhance this engagement, this intervention explores three sets of questions: what is distinctive about this novel way of thinking about and doing cities; what are the emerging mutual interdependencies and interrelations between AI and their urban contexts; and what are the consequent challenges and opportunities for urban governance. In closing, we outline research directions shaped around new research questions raised by the emergence of urban AI
The New Urban Agenda: key opportunities and challenges for policy and practice
The UN-HABITAT III conference held in Quito in late 2016 enshrined the first Sustainable Development Goal (SDG) with an exclusively urban focus. SDG 11, as it became known, aims to make cities more inclusive, safe, resilient and sustainable through a range of metrics, indicators, and evaluation systems. It also became part of a post-Quito ‘New Urban Agenda’ that is still taking shape. This paper raises questions around the potential for reductionism in this new agenda, and argues for the reflexive need to be aware of the types of urban space that are potentially sidelined by the new trends in global urban policy
Interrogating Urban Experiments
The notion of the “urban experiment” has become increasingly prevalent and popular as a guiding concept and trope used by both scholars and policymakers, as well as by corporate actors with a stake in the future of the city. In this paper, we critically engage with this emerging focus on “urban experiments”, and with its articulation through the associated concepts of “living labs”, “future labs”, “urban labs” and the like. A critical engagement with the notion of urban experimentation is now not only useful, but a necessity: we introduce seven specific areas that need critical attention when considering urban experiments: these are focused on normativity, crisis discourses, the definition of “experimental subjects”, boundaries and boundedness, historical precedents, “dark” experiments and non-human experimental agency.This work was supported by the Economic and Social Research Council (ESRC) [Grant Number:
ES/L015978/1]
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