Dream states: Smart cities, technology, and the pursuit of urban utopias. By JohnLorinc, Coach House Books, Toronto, 2022, 288 pp., paperback $22.95 (ISBN 978‐1552454282)
Bibliographic record
Abstract
The development of smart cities is becoming a trendy strategy to address the complex challenges confronting cities globally. John Lorinc's book presents thought-provoking arguments on how technology has shaped urban development processes in the past and how it will (re-)shape them in the future. The book is divided into three themed sections covering the technology of cities, the dream of the smart city, and, in the conclusion, a discussion of how technologies were deployed to deal with the pandemic and how these technologies are reshaping the post-pandemic city. The first section discusses different smart technologies that have been deployed in cities to deal with complex urban challenges. What is fascinating about this section is that it positions these discussions in a historical context, demonstrating that the deployment of urban technologies is not new. The second section focuses on the dream of the smart city, unpacking some of the most controversial utopian ideals associated with urban innovations. Lorinc begins this section by focusing more broadly on smart cities and the origin of urban utopianism, and highlights how global tech firms employ catchy marketing and advertising strategies to produce imaginings of cities as optimized machines. Most city governments, especially from the global south, end up embracing these ideas as a fast solution to existing urban problems. However, this kind of urban utopianism is detached from the realities several African and Asian cities are grappling with, such as massive expansion of informal settlements, notorious levels of air pollution, and disjointed transport systems. Under these conditions, to what extent will the deployment of urban technologies address city problems while optimizing social and economic prospects? The book tries to engage with this question, but does not adequately do so. Lorinc also addresses how the smart city movement is currently revolutionizing city planning, including generating real-time data to inform decision making about infrastructure needs. Most of the examples Lorinc uses are from western urban contexts. But how are smart city ideas transforming the planning of cities in the global south (e.g., in Africa, Latin America, and Asia)? There are some emerging practices in the utilization of urban technologies—in cities such as Kigali (Rwanda), Johannesburg (South Africa), Casablanca (Morocco), and other global south cities—that offer lessons about planning smart cities in different geographical contexts. In the second section, Lorinc also critically engages with the implications of big data and privacy. As smart city technologies such as smart sensors, CCTVs, and location-based tracking applications collect large amounts of data, significant questions arise. Who owns this data? What are the implications for privacy of human subjects whose information is collected, sometimes without consent? Indeed, smart city technologies have created new challenges relating to data governance and privacy. The book also explores the nexus between smart city technologies and the promise of green cities. Most cities, particularly those in advanced economies, have experimented with different smart city technologies to promote urban sustainability and green cities. The utopianism of smart city mega projects has been largely promoted using labels such as “eco,” “green,” and “smart.” These mega projects are usually marketed and promoted by global tech firms as an alternative model of urban development that can reverse the negative externalities in rapidly growing cities. However, if not carefully planned and implemented, these utopian smart city mega projects can lead to massive privatization and commodification of urban spaces, thereby aggravating existing inequalities in cities. Additionally, Lorinc addresses how politics influence the adoption of smart technologies in cities. One of the key take-aways is that deployment and appropriation of urban innovations—from the implementation of smart city mega projects to digital governance to pandemic preparedness tools—can effectively work if scrutinized together with the socio-economic and political complexities of city life. The concluding section raises critical issues about the future of a post-pandemic city. However, the deployment of urban technologies during the pandemic was not homogenous across different geographical contexts. In the global south, where millions of urban residents live in slums and overcrowded housing conditions, the application of technologies is limited or, in some cases, non-existent. What will the future of cities in these contexts look like? Overall, Lorinc's book is fascinating, creatively written, and raises important questions for city planners, geographers, activists, policymakers, and students who are interested in urban innovation and the application of technologies in the planning, governance, and management of cities in the 21st century.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".