Place identity: a generative AI’s perspective


Paper by Kee Moon Jang et al: “Do cities have a collective identity? The latest advancements in generative artificial intelligence (AI) models have enabled the creation of realistic representations learned from vast amounts of data. In this study, we test the potential of generative AI as the source of textual and visual information in capturing the place identity of cities assessed by filtered descriptions and images. We asked questions on the place identity of 64 global cities to two generative AI models, ChatGPT and DALL·E2. Furthermore, given the ethical concerns surrounding the trustworthiness of generative AI, we examined whether the results were consistent with real urban settings. In particular, we measured similarity between text and image outputs with Wikipedia data and images searched from Google, respectively, and compared across cases to identify how unique the generated outputs were for each city. Our results indicate that generative models have the potential to capture the salient characteristics of cities that make them distinguishable. This study is among the first attempts to explore the capabilities of generative AI in simulating the built environment in regard to place-specific meanings. It contributes to urban design and geography literature by fostering research opportunities with generative AI and discussing potential limitations for future studies…(More)”.

Atlas of Intangibles


About: “Atlas of Intangibles is a data experience designed to highlight the rich, interconnected web of sensory information that lies beneath our everyday encounters. Showcasing sensory data collected by me around the city of London through score-based data walks, the digital experience allows viewers to choose specific themes and explore related data as views — journeys, connections, and typologies. Each data point is rich in context, encompassing images and audio recordings…(More)”.

Data sovereignty for local governments. Considerations and enablers


Report by JRC Data sovereignty for local governments refers to a capacity to control and/or access data, and to foster a digital transformation aligned with societal values and EU Commission political priorities. Data sovereignty clauses are an instrument that local governments may use to compel companies to share data of public interest. Albeit promising, little is known about the peculiarities of this instrument and how it has been implemented so far. This policy brief aims at filling the gap by systematising existing knowledge and providing policy-relevant recommendations for its wider implementation…(More)”.

Modeling Cities and Regions as Complex Systems


Book by Roger White, Guy Engelen and Inge Uljee: “Cities and regions grow (or occasionally decline), and continuously transform themselves as they do so. This book describes the theory and practice of modeling the spatial dynamics of urban growth and transformation. As cities are complex, adaptive, self-organizing systems, the most appropriate modeling framework is one based on the theory of self-organizing systems—an approach already used in such fields as physics and ecology. The book presents a series of models, most of them developed using cellular automata (CA), which are inherently spatial and computationally efficient. It also provides discussions of the theoretical, methodological, and philosophical issues that arise from the models. A case study illustrates the use of these models in urban and regional planning. Finally, the book presents a new, dynamic theory of urban spatial structure that emerges from the models and their applications.

The models are primarily land use models, but the more advanced ones also show the dynamics of population and economic activities, and are integrated with models in other domains such as economics, demography, and transportation. The result is a rich and realistic representation of the spatial dynamics of a variety of urban phenomena. The book is unique in its coverage of both the general issues associated with complex self-organizing systems and the specifics of designing and implementing models of such systems…(More)”.

Using AI to Map Urban Change


Brief by Tianyuan Huang, Zejia Wu, Jiajun Wu, Jackelyn Hwang, Ram Rajagopal: “Cities are constantly evolving, and better understanding those changes facilitates better urban planning and infrastructure assessments and leads to more sustainable social and environmental interventions. Researchers currently use data such as satellite imagery to study changing urban environments and what those changes mean for public policy and urban design. But flaws in the current approaches, such as inadequately granular data, limit their scalability and their potential to inform public policy across social, political, economic, and environmental issues.

Street-level images offer an alternative source of insights. These images are frequently updated and high-resolution. They also directly capture what’s happening on a street level in a neighborhood or across a city. Analyzing street-level images has already proven useful to researchers studying socioeconomic attributes and neighborhood gentrification, both of which are essential pieces of information in urban design, sustainability efforts, and public policy decision-making for cities. Yet, much like other data sources, street-level images present challenges: accessibility limits, shadow and lighting issues, and difficulties scaling up analysis.

To address these challenges, our paper “CityPulse: Fine-Grained Assessment of Urban Change with Street View Time Series” introduces a multicity dataset of labeled street-view images and proposes a novel artificial intelligence (AI) model to detect urban changes such as gentrification. We demonstrate the change-detection model’s effectiveness by testing it on images from Seattle, Washington, and show that it can provide important insights into urban changes over time and at scale. Our data-driven approach has the potential to allow researchers and public policy analysts to automate and scale up their analysis of neighborhood and citywide socioeconomic change…(More)”.

Governments Empower Citizens by Promoting Digital Rights


Article by Julia Edinger: “The rapid rise of digital services and smart city technology has elevated concerns about privacy in the digital age and government’s role, even as cities from California to Texas take steps to make constituents aware of their digital rights.

Earlier this month, Long Beach, Calif., launched an improved version of its Digital Rights Platform, which shows constituents their data privacy and digital rights and information about how the city uses technologies while protecting digital rights.

“People’s digital rights are no different from their human or civil rights, except that they’re applied to how they interact with digital technologies — when you’re online, you’re still entitled to every right you enjoy offline,” said Will Greenberg, staff technologist at the Electronic Frontier Foundation (EFF), in a written statement. The nonprofit organization defends civil liberties in the digital world.


Long Beach’s platform initially launched several years ago, to mitigate privacy concerns that came out of the 2020 launch of a smart city initiative, according to Long Beach CIO Lea Eriksen. When that initiative debuted, the Department of Innovation and Technology requested the City Council approve a set of data privacy guidelines to ensure digital rights would be protected, setting the stage for the initial platform launch. Its 2021 beta version has now been enhanced to offer information on 22 city technology uses, up from two, and an enhanced feedback module enabling continued engagement and platform improvements…(More)”.

Artificial intelligence and the local government: A five-decade scientometric analysis on the evolution, state-of-the-art, and emerging trends


Paper by Tan Yigitcanlar et al: “In recent years, the rapid advancement of artificial intelligence (AI) technologies has significantly impacted various sectors, including public governance at the local level. However, there exists a limited understanding of the overarching narrative surrounding the adoption of AI in local governments and its future. Therefore, this study aims to provide a comprehensive overview of the evolution, current state-of-the-art, and emerging trends in the adoption of AI in local government. A comprehensive scientometric analysis was conducted on a dataset comprising 7112 relevant literature records retrieved from the Scopus database in October 2023, spanning over the last five decades. The study findings revealed the following key insights: (a) exponential technological advancements over the last decades ushered in an era of AI adoption by local governments; (b) the primary purposes of AI adoption in local governments include decision support, automation, prediction, and service delivery; (c) the main areas of AI adoption in local governments encompass planning, analytics, security, surveillance, energy, and modelling; and (d) under-researched but critical research areas include ethics of and public participation in AI adoption in local governments. This study informs research, policy, and practice by offering a comprehensive understanding of the literature on AI applications in local governments, providing valuable insights for stakeholders and decision-makers…(More)”.

close.city


About: “Proximity governs how we live, work, and socialize. Close is an interactive travel time map for people who want to be near the amenities that matter most to them. Close builds on two core principles:

  1. Different people will prioritize being near different amenities
  2. A neighborhood is only as accessible as its most distant important amenity

When you select multiple amenities in Close, the map shows the travel time to the furthest of those amenities. You can set your preferred travel mode to get to each amenity. Walking + Public Transit, Biking or Combined. Close is currently in public beta, with more features and destination types coming over the next few months. The reliability of destinations will continually improve as new data sources and user feedback are incorporated. Close is built and maintained by Henry Spatial Analysis. You can stay up-to-date on the latest improvements to Close by subscribing to the newsletter. How to use Close – Close includes travel time information for cities across the United States. To view a different location, select the search icon on the top left of the screen and enter a city or county name. To access map details, including a link to this About page, click the menu icon in the top left corner of the map…(More)”

Building SimCity: How to Put the World in a Machine


Book by Chaim Gingold: “…explores the history of computer simulation by chronicling one of the most influential simulation games ever made: SimCity. As author Chaim Gingold explains, Will Wright, the visionary designer behind the urban planning game, created SimCity in part to learn about cities, thinking about the world as a complex system and appropriating ideas from traditions in which computers are used for modeling. As such, SimCity is a microcosm of the histories and cultures of computer simulation that engages with questions, themes, and representational techniques that reach back to the earliest computer simulations.

Gingold uses SimCity to explore a web of interrelated topics in the history of technology, software, and simulation, taking us far and wide—from the dawn of programmable computers to miniature cities made of construction paper and role-play. An unprecedented history of Maxis, the company founded to bring SimCity to market, the book reveals Maxis’s complex relations with venture capitalists, Nintendo, and the Santa Fe Institute, which shaped the evolution of Will Wright’s career; Maxis’s failure to back The Sims to completion; and the company’s sale to Electronic Arts.

A lavishly visual book, Building SimCity boasts a treasure trove of visual matter to help bring its wide-ranging subjects to life, including painstakingly crafted diagrams that explain SimCity‘s operation, the Kodachrome photographs taken by Charles Eames of schoolchildren making model cities, and Nintendo’s manga-style “Dr. Wright” character design, just to name a few…(More)”.

Groups want N.Y. to disaggregate data of Middle Eastern, North African individuals


Article by Luke Parsnow: “A group of organizations are pushing for New York lawmakers to pass a bill that would disaggregate data of Middle Eastern and North African (MENA) individuals, according to a letter sent Monday.

The bill (S6584-B/A6219-A) would direct every state agency, board, department and commission that collects demographic data to use separate categories to collect data for the “White” and “Middle Eastern or North African” groups.

“Our organizations have seen firsthand the impact of the systemic exclusion of Middle Eastern and North African communities from data collection,” the letter reads. “Our communities do not perceive themselves to be white and are not perceived to be white. We also experience various disparities compared to non-Hispanic whites that go unseen because of the lack of data.”

The group says those communities categorized as “White” hinders those communities in education, employment, housing, health care and political representation.

“Miscategorizing a New Yorker’s race is not only offensive, but has real-world impacts on services and resources my particular communities receive,” Senate Deputy Leader Michael Gianaris said in a statement. “It should be obvious that people from the Middle East or North Africa are not white, yet that is how our laws define them.”

Gianaris said the legislation would give many New Yorkers better representation and a more powerful voice.

“The lack of a MENA category has hindered our understanding of the needs of MENA communities and our ability to consider those needs in decision-making and resource allocation,” according to the letter…(More)”.