Call for Paper CONTESTI 2 | 2026 POSTGROWTH AND DEGROWTH IN PLANNING PRACTICE Edited by Barbara Pizzo and Jin Xue DEADLINE June 7, 2026. Modern planning is deeply rooted in pro-growth development model. Spatial planning is addressed to city growth, whatever definition of growth might be implied (i.e., expansion, densification, valorisation, both in physical and economic terms). There is a centuries-old history of urban planning irrefutably demonstrating that. Nonetheless, postgrowth and degrowth as key concept and as perspectives to look at the future of cities and regions is evidently spreading. In recent years, research groups and networks, conferences and seminars, books and journal publications have multiplied. Although postgrowth and degrowth scholars have succeeded in bringing the dominant growth model into question and seriously discussing alternatives, they have started worrying about that what should be a crucial and compelling paradigmatic turn in planning approaches may instead become just another (ab)used buzzword. The aim of this call is to identify, clarify, and discuss if, how and by whom postgrowth and degrowth thinking is being translated into actual urban and regional practices, with particular attention to the fundamental objects and fields of action within urban and regional planning. This inquiry will also challenge and critically examine some of the claimed more ‘advanced’ ideas in planning for long-term sustainability such as no net land take, circular economy and sharing, the green shift, digitalization, and related initiatives. More specifically, we invite contributions addressing the following topics: Land and soil, Water, Energy, Nature and Biodiversity, Mobility, Housing, Production and Labour. We welcome contributions that: place one or more of these issues at the core of their inquiry while considering the interconnections with the others, draw on real cases and examples from urban and regional development and planning, reflect on and propose actionable suggestions for planning practices that can inform and inspire degrowth and postgrowth-oriented approaches. Download the CALL FOR PAPERS (ITA | ENG) ISSN: 2035-5300 More information about Contesti. Città, Territori, Progetti Contesti has been evaluated as Class A-Journal in the latest 2023 official ranking of academic journals set up by the Italian Ministry of University and Research and its evaluation agency ANVUR. _____________________________________________________________________________________________________
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PlanAIr. Planning and Artificial Intelligence in Urban Research
Drawing on James Lovelock’s concept of the Novacene, this editorial for the PlanAIr thematic issue frames the contemporary city as the primary crucible in which the alliance among human intelligence, artificial intelligence (AI), and ecological systems is negotiated. It argues that the current dominant paradigm of “Urban AI”—largely confined to data-driven optimization and “weak AI”—is insufficient for addressing the socio-ecological and cognitive complexities of the Anthropocene. Building on this analysis, the editorial introduces the special issue PlanAIr to investigate the “epistemic turn” in urban planning and to explore how AI necessitates a rethinking grounded in urban ontology, concept-driven governance models, and hybrid design methodologies. This collection of interdisciplinary contributions takes a first step toward bridging the gap between data-driven approaches and cognitive reasoning, moving beyond the efficiency narratives of the smart city. The editorial contends that, with a generative, hybrid, and ontology-aware AI, we can shift from exploiting AI as a tool for management to engaging AI as a partner in co-creating inclusive, transparent, and resilient urban futures.
Copyright (c) 2026 Giulia Guadagnoli, Camilla Perrone, Stefano Borgo https://creativecommons.org/licenses/by-nc/4.0
This excerpt from the first chapter of The Sciences of the Artificial (1969; 1996) by Herbert A. Simon establishes the epistemological foundations for distinguishing natural sciences from the “sciences of the artificial.” While natural sciences seek hidden patterns to explain how things are, the sciences of the artificial deal with objects synthesised by human beings, characterised by functions, goals, and normative imperatives—addressing how things “ought” to be. Simon introduces the crucial concept of the artefact as an “interface” between an “inner” environment (the substance and organisation of the object itself) and an “outer” environment (the context in which it operates); the artefact’s effectiveness depends on the successful adaptation of these two environments to one another. The text further explores the role of simulation as a source of new knowledge that can reveal the hidden implications of known premises. It defines both computers and the human mind as “physical symbol systems.” According to Simon, intelligence is fundamentally the work of these systems, which can encode information, manipulate structures, and adapt to their environment. The re-proposal of this classic text within the contemporary context of urban studies and Artificial Intelligence (PlanAIr) is driven by three fundamental reasons. First, Simon provides a critical ontological definition, reminding us that the world we inhabit is predominantly man-made. In this view, the city is the artefact par excellence: not a natural phenomenon to be passively observed, but a complex, designed system that must answer to human purposes, thus legitimising urban planning as a rigorous science of the artificial. Second, the vision of the artefact as a “meeting point” between inner and outer environments offers a powerful metaphor for Urban AI. Intelligent technologies in the city act as an interface between physical infrastructure and citizens’ social or environmental dynamics, requiring mutual adaptation to function effectively. Finally, as Simon’s work is foundational to symbolic Artificial Intelligence, revisiting it today allows us to grasp the theoretical roots of rule-based and logical AI. This historical perspective is crucial for distinguishing and potentially integrating symbolic approaches with the currently dominant data-driven paradigms, thereby recovering the capacity to reason about goals, meanings, and design imperatives rather than relying solely on raw data processing. In this article, we examine these ontological issues, discuss existing frameworks that aim to unify fragmented information, and explore the practical implications for urban AI applications. The thesis is that ontologies—structured and formal representations of knowledge—offer a powerful tool to address the challenges outlined above, while serving as a blueprint for defining, categorizing, and interrelating the entities present in urban environments and putting them to work in urban planning.
Copyright (c) 2026 Simon Herbert A. https://creativecommons.org/licenses/by-nc/4.0
AI, Data and Ontology: The Epistemic Turn in Urban Planning
In recent years, cities have undergone a dramatic evolution as they have become increasingly connected, data-rich environments. Urban artificial intelligence (AI) has emerged as a transformative force, empowering city planners, policymakers, and researchers to address complex challenges ranging from resource management to public safety. However, the sheer abundance of data in contemporary urban settings also presents significant ontological challenges, which become even more crucial when undertaking urban planning. These challenges revolve around the conceptualization, classification, and integration of heterogeneous data sources into coherent models capable of supporting intelligent decision-making. In this article, we examine these ontological issues, discuss existing frameworks that aim to unify fragmented information, and explore the practical implications for urban AI applications. The thesis is that ontologies—structured and formal representations of knowledge—offer a powerful tool to address the challenges outlined above, while serving as a blueprint for defining, categorizing, and interrelating the entities present in urban environments and putting them to work in urban planning.
Copyright (c) 2026 Stefano Borgo, Camilla Perrone https://creativecommons.org/licenses/by-nc/4.0
Marshall McLuhan e l’intelligenza artificiale urbana
This article offers an interpretation of urban artificial intelligence based on the concept of media and more specifically on Marshall McLuhan’s media theory. The Canadian scholar’s legacy, imbued with humanistic values, can inform an understanding of contemporary intelligent media that transcends the efficiency-focused discourses on the smart city. The article also argues that it is unnecessary to make a conclusive choice between artificial and collective intelligence as the term ‘collective’ can be given a wider meaning so as to encompass, beyond humans, sociotechnical communication systems.
Copyright (c) 2026 Luca Gaeta https://creativecommons.org/licenses/by-nc/4.0
Jumping Off AI Anxiety and Enthusiasm Bandwagons: The Legacy of Positivism and Its Pluralist Antidotes in Planning Thought and Information Science
In the last three decades, post-positivist approaches to planning theory sprung in parallel to digital applications intended as decision support systems in planning practice. Today, artificial intelligence (AI) raises expectations about the solutions to planning problems these systems may deliver. These expectations stir either anxiety or enthusiasm depending on whether one acknowledges the limitations of expert knowledge, or assumes that they rest on inadequate computing abilities. This article traces the lineage of contemporary enthusiasm about AI in planning practice back to the legacy of positivism in planning thought. Moreover, the article addresses the anxiety by showcasing pluralist challenges to positivist legacies across planning theory and information science. In this light, the paper lays the conceptual ground for planners' engagement with scholarship akin to post-positivist perspectives in information science, to foster pluralist due diligence in the use of AI applications.
Copyright (c) 2026 Giulia Guadagnoli https://creativecommons.org/licenses/by-nc/4.0
Intelligenza artificiale, da un mondo distopico al riconoscimento del patrimonio territoriale
The contribution examines the radical transformations in the relationship between power, technology, and urban space in the contemporary era, exploring the evolution from the dystopian narratives of the 20th century to the current digital scenario. Through theories such as Michel Foucault's biopolitics and Byung-Chul Han's psychopolitics, the text emphasizes how modern cognitive infrastructures have transformed surveillance into a mechanism of control based on voluntary connection and perceived freedom, risking reducing living to a comfortable digital prison. Criticizing the dematerialization of experience, the article argues that cognitive processes are embodied and relational, asserting the importance of physical interaction with the environment. The author critiques the technocratic vision of the smart city and proposes a reinterpretation of urban planning through the concepts of ‘hybrid space’ and ‘living city.’ The central goal is to define a new "right to the city" in the era of AI urbanism, proposing the use of artificial intelligence not as a tool of control but as a means of analyzing territorial heritage. The suggested approach includes the use of data-mining techniques to identify the identity qualities of places, with the goal of bridging the gap between humans and their environment, integrating both physical and digital dimensions in support of collective well-being.
Copyright (c) 2026 Claudio Saragosa, Maddalena Rossi https://creativecommons.org/licenses/by-nc/4.0
Pianificazione intelligente nell'era dell'incertezza: decisioni, conoscenza, complessità e tecnologie emergenti
Traditional spatial planning shows increasing limitations in addressing the complexity and dynamism of real contexts, often resulting in plans that are abstract and difficult to implement. The advent of emerging technologies, in particular Artificial Intelligence (AI), offers new perspectives to manage complex data and support informed decisions, but also shows risks of amplification of inequalities and persistence of existing biases. The text explores these issues in a framework of historical and theoretical evolution of planning, highlighting the dialectic between traditional top-down models and the need for multi-agent and knowledge-based approaches, more collaborative and adaptive. Through the analysis of experiments with generative AI and applied ontologies, some potential and limits of current technologies in the construction of future scenarios and in the management of diffused knowledge are outlined. A central epistemological challenge emerges, consisting in integrating advanced tools with inclusive participatory processes, shifting the emphasis towards collaborative knowledge structures capable of responding to the changing needs of communities and promoting more equitable and sustainable decisions.
Copyright (c) 2026 Domenico Camarda https://creativecommons.org/licenses/by-nc/4.0
On small area composite indicators and classifications for urban planning: theory-driven and data-driven approaches
The collection of data by public and private organisations has increased rapidly and continuously in the last decades. While some have called for “the end of theory” in a society dominated by data, this paper argues that theory and data driven approaches are both fundamental to make informed evidence-based decisions. Taking the case of geographic data products aimed at supporting urban planning, this paper critically examines the approaches that underpin their development. Through illustrative examples, it describes two types of research data products — small-area multidimensional theory-driven indicators and data-driven classifications — and outlines their respective advantages, limitations, and applications. While it is recognised that geographic data products can be a valuable asset to support urban planning, challenges remain in translating research outputs into practice. To avoid technocratic and decontextualised applications of such data, it is suggested to prioritise reflexivity, situate knowledge, acknowledge uncertainty, and embrace openness throughout the data production and use process.
Copyright (c) 2026 Alessia Calafiore https://creativecommons.org/licenses/by-nc/4.0
Ottimizzazione delle città intelligenti: l’utilizzo dei gemelli digitali e dell’intelligenza artificiale nei processi decisionali urbani
The article explores the use of artificial intelligence (AI) in “Digital Twin” models to facilitate urban decision-making processes. The authors examine the potential of digital twins, which are virtual replicas of physical systems, to optimise the planning and management of smart cities. AI, when integrated into digital twins, allows managing complex functions such as traffic, energy consumption and social behaviours to be simulated and monitored in real-time, so establishing a basis for more informed and timely decisions. The digital twin concept was originally applied to industrial manufacturing and has expanded to urban design. An effective digital twin must accurately represent physical reality and related processes, incorporating up-to-date data and using advanced AI models for predictions and simulations. This approach allows for more efficient and resilient urban management, improving responsiveness to unexpected events and facilitating long-term strategic planning. The Snap4City platform is presented as an example of implementing digital twins for smart cities. It integrates data from different sources, supports real-time analysis and visualisation, and enables AI-based operational and strategic management. Snap4City demonstrates significant benefits for public administrations, improving the efficiency of urban services and promoting sustainability and the well-being of citizens.
Copyright (c) 2025 Paolo Nesi, Chiara Garau, Paola Zamperlin https://creativecommons.org/licenses/by-nc/4.0
L'intelligenza artificiale per la città a 15 minuti: una proposta per innovare la pianificazione dei servizi a Milano
The ‘15-minute city’ represents a reinterpretation of a consolidated disciplinary paradigm, rediscovered during the pandemic as a response to the need for proximity in urban systems. In Europe, many experiments have focused on sustainable mobility and public spaces, while the integration of services has proven more complex, hindered by the lack of empirical tools and interoperable data. The future challenge lies in moving beyond traditional urban planning standards by adopting data-driven approaches to ensure accessible services and maximize social impact. This contribution explores the potential of artificial intelligence as a lever to innovate service planning, starting from the case of Milan. The city provides a relevant field of investigation, where the local authority is experimenting with new service planning tools in a context marked by heated public debate and inquiries centered on the relationship between private transformations and collective interests.
Copyright (c) 2026 Francesco Berni, Andrea Bartolini https://creativecommons.org/licenses/by-nc/4.0
Urban Artificial Intelligence in Mobility Infrastructure: Lessons for Just and Inclusive Cities
Artificial Intelligence is increasingly embedded in urban mobility and emergency response systems, where real-time decision-making, infrastructure coordination, and public safety converge. This article examines Urban Artificial Intelligence (Urban AI) through the domain of traffic management and emergency mobility, using these systems as a strategic entry point for analyzing broader questions of governance, equity, and resilience in AI-enabled cities. The paper develops a theoretical framework that distinguishes among cognitive, data-driven, and hybrid Urban AI models, highlighting how each approach shapes urban knowledge production, operational performance, and accountability. This framework is grounded through three U.S.-based case studies: AI-enabled emergency vehicle preemption in Fremont, California; AI-assisted subway infrastructure monitoring in New York City; and AI-driven signal coordination for emergency routing in Seattle. Together, these cases illustrate how Urban AI systems are deployed in real-world contexts to enhance efficiency, safety, and resilience. The analysis demonstrates that while Urban AI can significantly improve urban operations, its long-term legitimacy depends on integrating principles of equity, transparency, environmental responsibility, and participatory governance. The article concludes by arguing for integrated Urban AI models that balance technical effectiveness with democratic oversight, positioning Urban AI as a critical component of just, resilient, and inclusive urban futures.
Copyright (c) 2026 Asma Mehan https://creativecommons.org/licenses/by-nc/4.0
Data centers and the city. The territorial impacts of the growing data economy, with a focus on Italy
The present paper focuses on the study of the multiple impacts that the digital economy, which is expanding rapidly today, has and may have in the future on territories, with a particular focus on the Italian context and on the implementation of Data Centers (DCs), a facilities used for the remote storage, processing, or distribution of large amounts of data. In this context, there is a pressing need for in-depth research and multifaceted discourse on the urban and regional challenges of DCs location to enhance public knowledge and informed decision-making processes. This encompasses both the physical impact on territories and the implications for urban governance and socioeconomic aspects. This issue is of particular urgency in Italy. As the country emerges as a significant player in the European DC landscape, the absence of clear regulations gives rise to questions concerning the territorial and strategic planning of these infrastructures.
Copyright (c) 2026 Cristiana Mattioli, Alice Franchina https://creativecommons.org/licenses/by-nc/4.0
Fra mente e algoritmo: l’intelligenza artificiale nel progetto urbano
The paper analyses the application of artificial intelligence in urban planning through a concrete case study. Using computational tools, the proposed test compares AI-generated solutions with a traditional design process. The analysis highlights the ability of the algorithms to generate layouts but reveals limitations in the integration with the urban context and in the management of qualitative aspects. The tools used prove to be effective in supporting design schemes and in allowing rapid environmental simulations, but require human guidance to interpret the spatial fabric and urban standards. The experiment confirms the role of the designer in mediating between calculation and creativity, integrating ethics, spatial narrative and contextual adaptation. AI emerges as a regulatory device but does not replace human vision in interpreting urban complexity and translating social values into design solutions.
Copyright (c) 2025 Iacopo Zetti, Biagio Martino https://creativecommons.org/licenses/by-nc/4.0