Artificial Intelligence and the City

Curated on Posted on by Stefaan Verhulst

Book edited by Federico Cugurullo, Federico Caprotti, Matthew Cook, Andrew Karvonen, Pauline McGuirk, and Simon Marvin: “This book explores in theory and practice how artificial intelligence (AI) intersects with and alters the city. Drawing upon a range of urban disciplines and case studies, the chapters reveal the multitude of repercussions that AI is having on urban society, urban infrastructure, urban governance, urban planning and urban sustainability.

Contributors also examine how the city, far from being a passive recipient of new technologies, is influencing and reframing AI through subtle processes of co-constitution. The book advances three main contributions and arguments:

  • First, it provides empirical evidence of the emergence of a post-smart trajectory for cities in which new material and decision-making capabilities are being assembled through multiple AIs.
  • Second, it stresses the importance of understanding the mutually constitutive relations between the new experiences enabled by AI technology and the urban context.
  • Third, it engages with the concepts required to clarify the opaque relations that exist between AI and the city, as well as how to make sense of these relations from a theoretical perspective…(More)”.

Open data ecosystems: what models to co-create service innovations in smart cities?

Curated on Posted on by Stefaan Verhulst

Paper by Arthur Sarazin: “While smart cities are recently providing open data, how to organise the collective creation of data, knowledge and related products and services produced from this collective resource, still remains to be thought. This paper aims at gathering the literature review on open data ecosystems to tackle the following research question: what models can be imagined to stimulate the collective co-creation of services between smart cities’ stakeholders acting as providers and users of open data? Such issue is currently at stake in many municipalities such as Lisbon which decided to position itself as a platform (O’Reilly, 2010) in the local digital ecosystem. With the implementation of its City Operation Center (COI), Lisbon’s municipality provides an Information Infrastructure (Bowker et al., 2009) to many different types of actors such as telecom companies, municipalities, energy utilities or transport companies. Through this infrastructure, Lisbon encourages such actors to gather, integrate and release heterogeneous datasets and tries to orchestrate synergies among them so data-driven solution to urban problems can emerge (Carvalho and Vale, 2018). The remaining question being: what models for the municipalities such as Lisbon to lean on so as to drive this cutting-edge type of service innovation?…(More)”.

Urban Artificial Intelligence: From Real-world Observations to a Paradigm-Shifting Concept

Curated on Posted on by Stefaan Verhulst

Blog by Hubert Beroche: “Cities are facing unprecedented challenges. The figures are well known: while occupying only 2% of the earth’s surface, urban settlements host more than 50% of the global population and are responsible for 70% of greenhouse emissions. While concentrating most capital and human wealth, they are also places of systemic inequalities (Nelson, 2023), exacerbating and materializing social imbalances. In the meantime, cities have fewer and fewer resources to face those tensions. Increasing environmental constraints, combined with shrinking public budgets, are putting pressure on cities’ capacities. More than ever, urban stakeholders have to do more with less.

In this context, Artificial Intelligence has usually been seen as a much-welcomed technology. This technology can be defined as machines’ ability to perform cognitive functions, mainly through learning algorithms since 2012. First embedded in heavy top-down Smart City projects, AI applications in cities have gradually proliferated under the impetus of various stakeholders. Today’s cities are home to numerous AIs, owned and used by multiple stakeholders to serve different, sometimes divergent, interests.

The diversity of urban AIs in cities is well illustrated in our project co-produced with Cornell Tech: “The Future of Urban AI”. This graph represents different urban AI trends based on The Future of UrbanTech Horizon Scan. Each colored dot represents a major urban tech/urban AI trend, with its ramifications. Some of these trends are opposed but still cohabiting (eg “Dark Plans” and “New Screen Deal”)…(More)”.

Public Value of Data: B2G data-sharing Within the Data Ecosystem of Helsinki

Curated on Posted on by Stefaan Verhulst

Paper by Vera Djakonoff: “Datafication penetrates all levels of society. In order to harness public value from an expanding pool of private-produced data, there has been growing interest in facilitating business-to-government (B2G) data-sharing. This research examines the development of B2G data-sharing within the data ecosystem of the City of Helsinki. The research has identified expectations ecosystem actors have for B2G data-sharing and factors that influence the city’s ability to unlock public value from private-produced data.

The research context is smart cities, with a specific focus on the City of Helsinki. Smart cities are in an advantageous position to develop novel public-private collaborations. Helsinki, on the international stage, stands out as a pioneer in the realm of data-driven smart city development. For this research, nine data ecosystem actors representing the city and companies participated in semi-structured thematic interviews through which their perceptions and experiences were mapped.

The theoretical framework of this research draws from the public value management (PVM) approach in examining the smart city data ecosystem and alignment of diverse interests for a shared purpose. Additionally, the research transcends the examination of the interests in isolation and looks at how technological artefacts shape the social context and interests surrounding them. Here, the focus is on the properties of data as an artefact with anti-rival value-generation potential.

The findings of this research reveal that while ecosystem actors recognise that more value can be drawn from data through collaboration, this is not apparent at the level of individual initiatives and transactions. This research shows that the city’s commitment to and facilitation of a long-term shared sense of direction and purpose among ecosystem actors is central to developing B2G data-sharing for public value outcomes. Here, participatory experimentation is key, promoting an understanding of the value of data and rendering visible the diverse motivations and concerns of ecosystem actors, enabling learning for wise, data-driven development…(More)”.

New York City Takes Aim at AI

Curated on Posted on by Stefaan Verhulst

Article by Samuel Greengard: “As concerns over artificial intelligence (AI) grow and angst about its potential impact increase, political leaders and government agencies are taking notice. In November, U.S. president Joe Biden issued an executive order designed to build guardrails around the technology. Meanwhile, the European Union (EU) is currently developing a legal framework around responsible AI.

Yet, what is often overlooked about artificial intelligence is that it’s more likely to impact people on a local level. AI touches housing, transportation, healthcare, policing and numerous other areas relating to business and daily life. It increasingly affects citizens, government employees, and businesses in both obvious and unintended ways.

One city attempting to position itself at the vanguard of AI is New York. In October 2023, New York City announced a blueprint for developing, managing, and using the technology responsibly. The New York City Artificial Intelligence Action Plan—the first of its kind in the U.S.—is designed to help officials and the public navigate the AI space.

“It’s a fairly comprehensive plan that addresses both the use of AI within city government and the responsible use of the technology,” says Clifford S. Stein, Wai T. Chang Professor of Industrial Engineering and Operations Research and Interim Director of the Data Science Institute at Columbia University.

Adds Stefaan Verhulst, co-founder and chief research and development officer at The GovLab and Senior Fellow at the Center for Democracy and Technology (CDT), “AI localism focuses on the idea that cities are where most of the action is in regard to AI.”…(More)”.

Boston experimented with using generative AI for governing. It went surprisingly well

Curated on Posted on by Stefaan Verhulst

Article by Santiago Garces and Stephen Goldsmith: “…we see the possible advances of generative AI as having the most potential. For example, Boston asked OpenAI to “suggest interesting analyses” after we uploaded 311 data. In response, it suggested two things: time series analysis by case time, and a comparative analysis by neighborhood. This meant that city officials spent less time navigating the mechanics of computing an analysis, and had more time to dive into the patterns of discrepancy in service. The tools make graphs, maps, and other visualizations with a simple prompt. With lower barriers to analyze data, our city officials can formulate more hypotheses and challenge assumptions, resulting in better decisions.

Not all city officials have the engineering and web development experience needed to run these tests and code. But this experiment shows that other city employees, without any STEM background, could, with just a bit of training, utilize these generative AI tools to supplement their work.

To make this possible, more authority would need to be granted to frontline workers who too often have their hands tied with red tape. Therefore, we encourage government leaders to allow workers more discretion to solve problems, identify risks, and check data. This is not inconsistent with accountability; rather, supervisors can utilize these same generative AI tools, to identify patterns or outliers—say, where race is inappropriately playing a part in decision-making, or where program effectiveness drops off (and why). These new tools will more quickly provide an indication as to which interventions are making a difference, or precisely where a historic barrier is continuing to harm an already marginalized community.  

Civic groups will be able to hold government accountable in new ways, too. This is where the linguistic power of large language models really shines: Public employees and community leaders alike can request that tools create visual process maps, build checklists based on a description of a project, or monitor progress compliance. Imagine if people who have a deep understanding of a city—its operations, neighborhoods, history, and hopes for the future—can work toward shared goals, equipped with the most powerful tools of the digital age. Gatekeepers of formerly mysterious processes will lose their stranglehold, and expediters versed in state and local ordinances, codes, and standards, will no longer be necessary to maneuver around things like zoning or permitting processes. 

Numerous challenges would remain. Public workforces would still need better data analysis skills in order to verify whether a tool is following the right steps and producing correct information. City and state officials would need technology partners in the private sector to develop and refine the necessary tools, and these relationships raise challenging questions about privacy, security, and algorithmic bias…(More)”

Managing smart city governance – A playbook for local and regional governments

Curated on Posted on by Stefaan Verhulst

Report by UN Habitat” “This playbook and its recommendations are primarily aimed at municipal governments and their political leaders, local administrators, and public officials who are involved in smart city initiatives. The recommendations, which are delineated in the subsequent sections of this playbook, are intended to help develop more effective, inclusive, and sustainable governance practices for urban digital transformations. The guidance offered on these pages could also be useful for national agencies, private companies, non-governmental organizations, and all stakeholders committed to promoting the sustainable development of urban communities through the implementation of smart city initiatives…(More)”.

Cities are ramping up to make the most of generative AI

Curated on Posted on by Stefaan Verhulst

Blog by Citylab: “Generative artificial intelligence promises to transform the way we work, and city leaders are taking note. According to a recent survey by Bloomberg Philanthropies in partnership with the Centre for Public Impact, the vast majority of mayors (96 percent) are interested in how they can use generative AI tools like ChatGPT—which rely on machine learning to identify patterns in data and create, or generate, new content after being fed prompts—to improve local government. Of those cities surveyed, 69 percent report that they are already exploring or testing the technology. Specifically, they’re interested in how it can help them more quickly and successfully address emerging challenges with traffic and transportation, infrastructure, public safety, climate, education, and more.  

Yet even as a majority of city leaders surveyed are exploring generative AI’s potential, only a small fraction of them (2 percent) are actively deploying the technology. They indicated there are a number of issues getting in the way of broader implementation, including a lack of technical expertise, budgetary constraints, and ethical considerations like security, privacy, and transparency…(More)”.

City Science

Curated on Posted on by Stefaan Verhulst

Book by Ramon Gras, and Jeremy Burke: “The Aretian team, a spin off company from the Harvard Innovation Lab, has developed a city science methodology to evaluate the relationship between city form and urban performance. This book illuminates the relationship between a city’s spatial design and quality of life it affords for the general population. By measuring innovation economies to design Innovation Districts, social networks and patterns to help form organization patterns, and city topology, morphology, entropy and scale to create 15 Minute Cities are some of the frameworks presented in this volume.
Therefore, urban designers, architects and engineers will be able to successfully tackle complex urban design challenges by using the authors’ frameworks and findings in their own work. Case studies help to present key insights from advanced, data-driven geospatial analyses of cities around the world in an illustrative manner. This inaugural book by Aretian Urban Analytics and Design will give readers a new set of tools to learn from, expand, and develop for the healthy growth of cities and regions around the world…(More)”.

Smart City Data Governance

Curated on Posted on by Stefaan Verhulst

OECD Report: “Smart cities leverage technologies, in particular digital, to generate a vast amount of real-time data to inform policy- and decision-making for an efficient and effective public service delivery. Their success largely depends on the availability and effective use of data. However, the amount of data generated is growing more rapidly than governments’ capacity to store and process them, and the growing number of stakeholders involved in data production, analysis and storage pushes cities data management capacity to the limit. Despite the wide range of local and national initiatives to enhance smart city data governance, urban data is still a challenge for national and city governments due to: insufficient financial resources; lack of business models for financing and refinancing of data collection; limited access to skilled experts; the lack of full compliance with the national legislation on data sharing and protection; and data and security risks. Facing these challenges is essential to managing and sharing data sensibly if cities are to boost citizens’ well-being and promote sustainable environments…(More)”