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Geospatial Artificial Intelligence (GeoAI) systems are increasingly used by local governments to manage urban planning activities. However, there is a lack of clear guidelines for responsible artificial intelligence (AI) implementation. We address this gap by applying the task-data-user-technology fit theory. First, we create a conceptual framework that translates ethical AI principles into practical system requirements. Second, we apply this framework through a case study analysis. We examine the geospatial AI system that the city of eThekwini, South Africa, has deployed to monitor their informal settlements. Based on expert interviews, our analysis highlights the ethical trade-offs inherent in the interactions between fits, data, tasks, users, and AI interactions, especially in an inherently localized and multi-stakeholder field such as urban planning. Additionally, we show how these fits are interconnected and cross-dependent. For example, the technical skills and resources of users can influence all other fits. Our study also reveals how task reconfiguration, user adaptability, and data improvement can enhance or hinder alignment with technology. From these insights, we introduce practical and theoretical recommendations for responsible AI development, adoption, and use. [ABSTRACT FROM AUTHOR]

The Covid-19 pandemic has further evidenced the potential of grassroots actors as initiators of digital innovations, in the form of open-source applications, platform cooperatives, and other crowdsourced digital artifacts. These innovations played a crucial role in mitigating the impact of lockdown measures, specifically serving the needs of communities often neglected by commercial offerings from large tech companies. Grassroots digital innovations (GDIs) have long been recognized by scholars and policymakers as potential remedies to market distortions and social iniquities within digitalization processes. Nevertheless, these initiatives have historically struggled to become sustainable. Recent evidence confirms that many GDIs developed in response to the global health crisis are now facing financial issues that threaten their survival. In this commentary, we reflect on this challenge and assert that GDI literature exhibits several shortcomings that contribute to undermining the long-term stability of these initiatives and their capacity to foster more inclusive, just, and sustainable digitalization processes. We examine how these shortcomings can be addressed to enhance both GDI research and practice. Our discussion focuses on three major methodological and conceptual limitations: a tendency towards theory-devoid empiricism, a bias towards successful cases, and a dearth of longitudinal, multi-site analyses. We discuss the causes of each shortcoming and illustrate how they impact both the theoretical and practical development of GDIs. Drawing on this critical examination, we identify four priorities to advance future GDI research: leveraging methodological pluralism, applying theoretical sampling, enhancing qualitative longitudinal research, and strengthening methods for data collection and archival. These priorities aim to inform the agendas of academic communities, funding bodies, and policy institutions dedicated to harnessing the potential of GDIs for more sustainable and inclusive digitalization processes. [ABSTRACT FROM AUTHOR]

This Connexions article links collaboration in smart city projects, a contemporary and undertheorised social challenge, with theories on assemblage thinking, organisation, and public value creation. Using this multidisciplinary lens, we critically analyse smart city theory and expose the inability of prevailing collaborative models to properly account for the complexities of real-world practices. Building on our observations, we formulate a new and more robust theoretical perspective on smart city collaboration, which helps us trigger new research questions that focus on procedural, relational and diversity factors previously ignored. [ABSTRACT FROM AUTHOR]

Theories of smart urbanism have overlooked the influence of contextual factors on the conception, planning and implementation of digital transformation practices across regions. To articulate this critique, we focus on African cities and draw on a diverse range of urban and regional scholarship. We present the core assumptions advanced in the mainstream literature on smart urbanism and prove their inability to fit the organisation of African urban contexts. Three main research questions emerge from this critical examination and offer new perspectives for expanding knowledge on how smart urbanism challenges recombine with place-based governance approaches, not only in Africa, but globally. [ABSTRACT FROM AUTHOR]

Municipalities often collaborate with other stakeholders in smart city projects to develop and implement technological innovations to address complex urban issues. We propose the shared portfolio approach as an alternative way of collaborating, because we have identified possible limitations when the commonly used single-project approach is adopted in complex contexts, such as the smart city context. The portfolio approach enhances flexibility, an embedded focus and cross-project learning, because partners work on multiple projects – either in parallel or in succession – to develop multiple solutions to a specific problem. An in-depth case study is used to illustrate how the shared portfolio approach works. In practice, these insights can be used by public bodies who aim to collaborate in smart city development or by partners who work on smart city projects and wish to continue their collaboration in a portfolio setting. Conceptually, our paper develops a connection between cross-sector partnership literature and smart city literature by revealing how the shared portfolio approach could be an effective way to deal with the complexities of innovation in the smart city context. [ABSTRACT FROM AUTHOR]