Unlock Your City’s Hidden Solutions


Article by Andreas Pawelke, Basma Albanna and Damiano Cerrone: “Cities around the world face urgent challenges — from climate change impacts to rapid urbanization and infrastructure strain. Municipal leaders struggle with limited budgets, competing priorities, and pressure to show quick results, making traditional approaches to urban transformation increasingly difficult to implement.

Every city, however, has hidden success stories — neighborhoods, initiatives, or communities that are achieving remarkable results despite facing similar challenges as their peers.

These “positive deviants” often remain unrecognized and underutilized, yet they contain the seeds of solutions that are already adapted to local contexts and constraints.

Data-Powered Positive Deviance (DPPD) combines urban data, advanced analytics, and community engagement to systematically uncover these bright spots and amplify their impact. This new approach offers a pathway to urban transformation that is not only evidence-based but also cost-effective and deeply rooted in local realities.

DPPD is particularly valuable in resource-constrained environments, where expensive external solutions often fail to take hold. By starting with what’s already working, cities can make strategic investments that build on existing strengths rather than starting from scratch. Leveraging AI tools that improve community engagement, the approach becomes even more powerful — enabling cities to envision potential futures, and engage citizens in meaningful co-creation…(More)”

Using Gamification to Engage Citizens in Micro-Mobility Data Sharing


Paper by Anu Masso, Anniki Puura, Jevgenia Gerassimenko and Olle Järv: “The European Strategy for Data aims to create a unified environment for accessing, sharing, and reusing data across sectors, institutions, and individuals, with a focus on areas like mobility and smart cities. While significant progress has been made in the technical interoperability and legislative frameworks for data spaces, critical gaps persist in the bottom-up processes, particularly in fostering social collaboration and citizen-driven initiatives. What is often overlooked is the need for effective citizen engagement and collaborative governance models to ensure the long-term viability and inclusivity of these data spaces. In addition, although principles for successful data sharing are well-established in sectors like healthcare, they remain underdeveloped and more challenging to implement in areas such as mobility. This article addresses these gaps by exploring how gamification can drive bottom-up data space formation, engaging citizens in data-sharing and fostering collaboration among private companies, local governments, and academic institutions. Using bicycle usage as an example, it illustrates how gamification can incentivise citizens to share mobility data for social good, promoting more active and sustainable transportation in cities. Drawing on a case study from Tallinn (Estonia), the paper demonstrates how gamification can improve data collection, highlighting the vital role of citizen participation in urban planning. The article emphasises that while technological solutions for data spaces are advancing, understanding collaborative governance models for data sharing remains crucial for ensuring the success of the European Union’s data space agenda and driving sustainable innovation in urban environments…(More)”.

Measuring the Shade Coverage of Trees and Buildings in Cambridge, Massachusetts


Paper by Amirhosein Shabrang, Mehdi Pourpeikari Heris, and Travis Flohr: “We investigated the spatial shade patterns of trees and buildings on sidewalks and bike lanes in Cambridge, Massachusetts. We used Lidar data and 3D modeling to analyze the spatial and temporal shade distribution across the City. Our analysis shows significant shade variations throughout the City. Western city areas receive more shade from trees, and the eastern regions receive more shade from buildings. The City’s northern areas lack shade, but natural and built sources of shade can improve shade coverage integration. This study’s findings help identify shade coverage gaps, which have implications for urban planning and design for more heat-resilient cities…(More)”

AI in Urban Life


Book by Patricia McKenna: “In exploring artificial intelligence (AI) in urban life, this book brings together and extends thinking on how human-AI interactions are continuously evolving. Through such interactions, people are aided on the one hand, while becoming more aware of their own capabilities and potentials on the other hand, pertaining, for example, to creativity, human sensing, and collaboration.

It is the particular focus of research questions developed in relation to awareness, smart cities, autonomy, privacy, transparency, theory, methods, practices, and collective intelligence, along with the wide range of perspectives and opportunities offered, that set this work apart from others. Conceptual frameworks are formulated for each of these areas to guide explorations and understandings in this work and going forward. A synthesis is provided in the final chapter for perspectives, challenges and opportunities, and conceptual frameworks for urban life in an era of AI, opening the way for evolving research and practice directions…(More)”.

Smart Cities to Smart Societies: Moving Beyond Technology


Book edited by Esmat Zaidan, Imad Antoine Ibrahim, and Elie Azar: “…explores the governance of smart cities from a holistic approach, arguing that the creation of smart cities must consider the specific circumstances of each country to improve the preservation, revitalisation, liveability, and sustainability of urban areas. The recent push for smart cities is part of an effort to reshape urban development through megaprojects, centralised master planning, and approaches that convey modernism and global affluence. However, moving towards a citywide smart transition is a major undertaking, and complexities are expected to grow exponentially. This book argues that a comprehensive approach is necessary to consider all relevant aspects. The chapters seek to identify the potential and pitfalls of the smart transformation of urban communities and its role in sustainability goals; share state-of-the-art practices concerning technology, policy, and social science dimensions in smart cities and communities; and develop opportunities for cooperation and partnership in wider and larger research and development programmes. Divided into three parts, the first part of the book highlights the significance of various societal elements and factors in facilitating a successful smart transition, with a particular emphasis on the role of human capital. The second part delves into the challenges associated with technology and its integration into smart city initiatives. The final part of the book examines the current state of regulations and policies governing smart cities. The book will be an important asset for students and researchers studying law, engineering, political science, international relations, geopolitics, economics, and engineering…(More)”.

The Next Wave of Innovation Districts


Article by Bruce Katz and Julie Wagner: “A next wave of innovation districts is gaining momentum given the structural changes underway in the global economy. The examples cited above telegraph where existing innovation districts are headed and explain why new districts are forming. The districts highlighted and many others are responding to fast-changing and highly volatile macro forces and the need to de-riskdecarbonize, and diversify talent.

The next wave of innovation districts is distinctive for multiple reasons.

  • The sectors leveraging this innovation geography expand way beyond the traditional focus on life sciences to include advanced manufacturing for military and civilian purposes.
  • The deeper emphasis on decarbonization is driving the use of basic and applied R&D to invent new clean technology products and solutions as well as organizing energy generation and distribution within the districts themselves to meet crucial carbon targets.
  • The stronger emphasis on the diversification of talent includes the upskilling of workers for new production activities and a broader set of systems to drive inclusive innovation to address long-standing inequities.
  • The districts are attracting a broader group of stakeholders, including manufacturing companies, utilities, university industrial design and engineering departments and hard tech startups.
  • The districts ultimately are looking to engage a wider base of investors given the disparate resources and traditions of capitalization that support defense tech, clean tech, med tech and other favored forms of innovation.

Some regions or states are also seeking ways to connect a constellation of districts and other economic hubs to harness the imperative to innovate accentuated by these and other macro forces. The state of South Australia is one such example. It has prioritized several innovation hubs across this region to foster South Australia’s knowledge and innovation ecosystem, as well as identify emerging economic clusters in industry sectors of global competitiveness to advance the broader economy…(More)”.

Urban Development Needs Systems Thinking


Article by Yaera Chung: “More than three decades after the collapse of the Soviet Union, cities in Eastern Europe and Central Asia (EECA) continue to grapple with economic stagnation, aging infrastructure, and environmental degradation while also facing new pressures from climate change and regional conflicts. In this context, traditional city planning, which tackles problems in isolation, is struggling to keep up. Urban strategies often rely on siloed, one-off interventions that fail to reflect the complexity of social challenges or adapt to shifting conditions. As a result, efforts are frequently fragmented, overlook root causes, and miss opportunities for long-term, cross-sector collaboration.

Instead of addressing one issue at a time, cities need to develop a set of coordinated, interlinked solutions that tackle multiple urban challenges simultaneously and align efforts across sectors. As part of a broader strategy to address environmental, economic, and social goals at once, for example, cities might advance a range of initiatives, such as transforming biowaste into resources, redesigning streets to reduce air pollution, and creating local green jobs. These kinds of “portfolio” approaches are leading to lasting and systems-level change.

Since 2021, the United Nations Development Programme (UNDP) has been collaborating with 15 cities across EECA to solve problems in ways that embrace complexity and interconnectedness. Selected through open calls under two UNDP initiatives, Mayors for Economic Growth and the City Experiment Fund, these cities demonstrated a strong interest in tackling systemic issues. Their proposals highlighted the problems they face, their capacity for innovation, and local initiatives and partnerships.

Their ongoing journeys have surfaced four lessons that can help other cities move beyond conventional planning pitfalls, and adopt a more responsive, inclusive, and sustainable approach to urban development…(More)”.

Governing in the Age of AI: Reimagining Local Government


Report by the Tony Blair Institute for Global Change: “…The limits of the existing operating model have been reached. Starved of resources by cuts inflicted by previous governments over the past 15 years, many councils are on the verge of bankruptcy even though local taxes are at their highest level. Residents wait too long for care, too long for planning applications and too long for benefits; many people never receive what they are entitled to. Public satisfaction with local services is sliding.

Today, however, there are new tools – enabled by artificial intelligence – that would allow councils to tackle these challenges. The day-to-day tasks of local government, whether related to the delivery of public services or planning for the local area, can all be performed faster, better and cheaper with the use of AI – a true transformation not unlike the one seen a century ago.

These tools would allow councils to overturn an operating model that is bureaucratic, labour-intensive and unresponsive to need. AI could release staff from repetitive tasks and relieve an overburdened and demotivated workforce. It could help citizens navigate the labyrinth of institutions, webpages and forms with greater ease and convenience. It could support councils to make better long-term decisions to drive economic growth, without which the resource pressure will only continue to build…(More)”.

Smart Cities:Technologies and Policy Options to Enhance Services and Transparency


GAO Report: “Cities across the nation are using “smart city” technologies like traffic cameras and gunshot detectors to improve public services. In this technology assessment, we looked at their use in transportation and law enforcement.

Experts and city officials reported multiple benefits. For example, Houston uses cameras and Bluetooth sensors to measure traffic flow and adjust signal timing. Other cities use license plate readers to find stolen vehicles.

But the technologies can be costly and the benefits unclear. The data they collect may be sold, raising privacy and civil liberties concerns. We offer three policy options to address such challenges…(More)”.

Data Commons: The Missing Infrastructure for Public Interest Artificial Intelligence


Article by Stefaan Verhulst, Burton Davis and Andrew Schroeder: “Artificial intelligence is celebrated as the defining technology of our time. From ChatGPT to Copilot and beyond, generative AI systems are reshaping how we work, learn, and govern. But behind the headline-grabbing breakthroughs lies a fundamental problem: The data these systems depend on to produce useful results that serve the public interest is increasingly out of reach.

Without access to diverse, high-quality datasets, AI models risk reinforcing bias, deepening inequality, and returning less accurate, more imprecise results. Yet, access to data remains fragmented, siloed, and increasingly enclosed. What was once open—government records, scientific research, public media—is now locked away by proprietary terms, outdated policies, or simple neglect. We are entering a data winter just as AI’s influence over public life is heating up.

This isn’t just a technical glitch. It’s a structural failure. What we urgently need is new infrastructure: data commons.

A data commons is a shared pool of data resources—responsibly governed, managed using participatory approaches, and made available for reuse in the public interest. Done correctly, commons can ensure that communities and other networks have a say in how their data is used, that public interest organizations can access the data they need, and that the benefits of AI can be applied to meet societal challenges.

Commons offer a practical response to the paradox of data scarcity amid abundance. By pooling datasets across organizations—governments, universities, libraries, and more—they match data supply with real-world demand, making it easier to build AI that responds to public needs.

We’re already seeing early signs of what this future might look like. Projects like Common Corpus, MLCommons, and Harvard’s Institutional Data Initiative show how diverse institutions can collaborate to make data both accessible and accountable. These initiatives emphasize open standards, participatory governance, and responsible reuse. They challenge the idea that data must be either locked up or left unprotected, offering a third way rooted in shared value and public purpose.

But the pace of progress isn’t matching the urgency of the moment. While policymakers debate AI regulation, they often ignore the infrastructure that makes public interest applications possible in the first place. Without better access to high-quality, responsibly governed data, AI for the common good will remain more aspiration than reality.

That’s why we’re launching The New Commons Challenge—a call to action for universities, libraries, civil society, and technologists to build data ecosystems that fuel public-interest AI…(More)”.