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)”.
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)”.
Training LLMs to Draft Replies to Parliamentary Questions
Blog by Watson Chua: “In Singapore, the government is answerable to Parliament and Members of Parliament (MPs) may raise queries to any Minister on any matter in his portfolio. These questions can be answered orally during the Parliament sitting or through a written reply. Regardless of the medium, public servants in the ministries must gather materials to answer the question and prepare a response.
Generative AI and Large Language Models (LLMs) have already been applied to help public servants do this more effectively and efficiently. For example, Pair Search (publicly accessible) and the Hansard Analysis Tool (only accessible to public servants) help public servants search for relevant information in past Parliamentary Sittings relevant to the question and synthesise a response to it.
The existing systems draft the responses using prompt engineering and Retrieval Augmented Generation (RAG). To recap, RAG consists of two main parts:
- Retriever: A search engine that finds documents relevant to the question
- Generator: A text generation model (LLM) that takes in the instruction, the question, and the search results from the retriever to respond to the question
Using a pre-trained instruction-tuned LLM like GPT-4o, the generator can usually generate a good response. However, it might not be exactly what is desired in terms of verbosity, style and writing prose, and additional human post-processing might be needed. Extensive prompt engineering or few-shot learning can be done to mold the response at the expense of incurring higher costs from using additional tokens in the prompt…(More)”
Artificial Intelligence Is Making The Housing Crisis Worse
Article by Rebecca Burns: “When Chris Robinson applied to move into a California senior living community five years ago, the property manager ran his name through an automated screening program that reportedly used artificial intelligence to detect “higher-risk renters.” Robinson, then 75, was denied after the program assigned him a low score — one that he later learned was based on a past conviction for littering.
Not only did the crime have little bearing on whether Robinson would be a good tenant, it wasn’t even one that he’d committed. The program had turned up the case of a 33-year-old man with the same name in Texas — where Robinson had never lived. He eventually corrected the error but lost the apartment and his application fee nonetheless, according to a federal class-action lawsuit that moved towards settlement this month. The credit bureau TransUnion, one of the largest actors in the multi-billion-dollar tenant screening industry, agreed to pay $11.5 million to resolve claims that its programs violated fair credit reporting laws.
Landlords are increasingly turning to private equity-backed artificial intelligence (AI) screening programs to help them select tenants, and resulting cases like Robinson’s are just the tip of the iceberg. The prevalence of incorrect, outdated, or misleading information in such reports is increasing costs and barriers to housing, according to a recent report from federal consumer regulators.
Even when screening programs turn up real data, housing and privacy advocates warn that opaque algorithms are enshrining high-tech discrimination in an already unequal housing market — the latest example of how AI can end up amplifying existing biases…(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:
- Different people will prioritize being near different amenities
- 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)”.
Predicting hotspots of unsheltered homelessness using geospatial administrative data and volunteered geographic information
Paper by Jessie Chien, Benjamin F. Henwood, Patricia St. Clair, Stephanie Kwack, and Randall Kuhn: “Unsheltered homelessness is an increasingly prevalent phenomenon in major cities that is associated with adverse health and mortality outcomes. This creates a need for spatial estimates of population denominators for resource allocation and epidemiological studies. Gaps in the timeliness, coverage, and spatial specificity of official Point-in-Time Counts of unsheltered homelessness suggest a role for geospatial data from alternative sources to provide interim, neighborhood-level estimates of counts and trends. We use citizen-generated data from homeless-related 311 requests, provider-based administrative data from homeless street outreach cases, and expert reports of unsheltered count to predict count and emerging hotspots of unsheltered homelessness in census tracts across the City of Los Angeles for 2019 and 2020. Our study shows that alternative data sources can contribute timely insights into the state of unsheltered homelessness throughout the year and inform the delivery of interventions to this vulnerable population…(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)”.