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
A typical RAG system. Illustration by Hrishi Olickel, taken from here.

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:

  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)”.

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)”.

‘Positive deviance’ and the power of outliers


Bloomberg Cities Network: “Groundbreaking solutions in cities are often the result of visionary mayoral leadership. But sometimes certain communities achieve significantly better outcomes than their similarly resourced neighbors—and the underlying reasons may not be immediately obvious to local leaders. Ravi Gurumurthy, CEO of the global innovation foundation Nesta, believes that this variation in quality of life at a hyper-local level is something worth paying a lot more attention to. 

“The fastest way for us to improve people’s lives will be to mine that variation and really understand what is going on,” he says.    

This concept, known as “positive deviance,” describes individuals or communities that achieve remarkable success or exhibit highly effective behaviors despite facing the same constraints as their peers. With a long history of use in international development, positive deviance is now gaining traction among city leaders as a source of solutions to stubborn urban challenges.  

Here’s a closer look at what it’s about, and how it’s already being used to uplift promising approaches in cities. 

What is positive deviance? 

Positive deviance first gained widespread attention because of a remarkable success story in 1990s Vietnam. Much of the country was suffering from a malnutrition crisis, and efforts to design and implement new solutions were coming up short. But aid workers landed on a breakthrough by paying closer attention to children who already appeared larger and healthier than their peers.  

It turned out these children were being fed different diets—leaning more heavily on shrimp and crab, for example, which were widely accessible but less often fed to young people. These children also were being fed more frequently, in smaller meals, throughout the day—an intervention that, again, did not require parents to have more resources so much as to differently use what was universally available.  

When these practices—feeding kids shellfish and making meals smaller and more frequent—were replicated, malnutrition plummeted…(More)”

A Literature Review on the Paradoxes of Public Interest in Spatial Planning within Urban Settings with Diverse Stakeholders


Paper by Danai Machakaire and Masilonyane Mokhele: “The concept of public interest legitimises the planning profession, provides a foundational principle, and serves as an ethical norm for planners. However, critical discourses highlight the problems of the assumptions underlying the notion of public interest in spatial planning. Using an explorative literature review approach, the article aims to analyse various interpretations and applications of public interest in spatial planning. The literature search process, conducted between August and November 2023, targeted journal articles and books published in English and focused on the online databases of Academic Search Premier, Scopus, and Google Scholar. The final selected literature comprised 71 sources. The literature showed that diverse conceptualisations of public interest complicate the ways spatial planners and authorities incorporate it in planning tools, processes, and products. This article concludes by arguing that the prospects of achieving a single definition of the public interest concept are slim and may not be necessary given the heterogeneous conceptualisation and the multiple operational contexts of public interest. The article recommends the development of context-based analytical frameworks to establish linkages that would lead towards the equitable inclusion of public interest in spatial planning…(More)”.

Cities Are at the Forefront of AI and Civic Engagement


Article by Hollie Russon Gilman and Sarah Jacob: “…cities worldwide are already adopting AI for everyday governance needs. Buenos Aires is integrating communication with residents through Boti, an AI chatbot accessible via WhatsApp. Over 5 million residents are using the chatbot everyday month, with some months upwards of 11 million users. Boti connects residents with city services such as bike sharing or social care programs or reports. Unlike other AI systems with a closed loop, Boti can connect externally to help residents with other government services. For more sensitive issues, such as domestic abuse, Boti can connect residents with a human operator. AI, in this context, offers residents a convenient means to efficiently engage with city resources and communicate with city employees.

Another example of AI improving people’s everyday lives is SomosUna, a partnership between the Inter American Development Bank and Next2MyLife, aims to address gender-based violence in Uruguay. In response to the rise in gender-based violence during and after Covid, this initiative aims to prevent violence through a network of support and “helpers” which includes 1) training 2) technology and 3) a community of volunteers. This initiative will leverage AI technology to enhance its support network, advancing preventative measures and providing immediate assistance.

While AI can foster engagement, local government officials recognize that they must pre-engage the public to determine the role that AI should play in civic life across diverse cities. This pre-engagement and education will inform the ethical standards and considerations against which AI will be assessed.

The EU’s ITHACA project, for example, explores the application of AI in civic participation and local governance…(More)”… See also: AI Localism.