Wenda Li

AI-enabled smart home technologies are increasingly embedded within urban socio-technical systems, contributing to energy efficiency, resource optimisation, and improved quality of life. However, their sustainable integration into cities depends not only on technical performance but also on societal acceptance, trust, and responsible governance. This study examines how responsibility signalling, through corporate social responsibility and responsible innovation, shapes consumer trust, risk perception, and acceptance of domestic AI ecosystems. Drawing on a large-scale survey of 1,549 users across Australia, the US, and the UK, the study employs a mixed-method approach combining partial least squares structural equation modelling and fuzzy-set qualitative comparative analysis. The findings reveal that responsibility signals operate as a multi-level socio-technical mechanism, where corporate-level social responsibility and product-level responsible design jointly enhance proxy trust and reduce perceived risks, thereby increasing acceptance. Configurational results show that no single factor is sufficient; instead, multiple pathways combining responsibility, trust, and reduced risk lead to high acceptance outcomes. Cross-national differences highlight the contextual nature of responsibility interpretation. The study contributes to sustainable urban research by positioning domestic AI ecosystems as critical components of smart and sustainable cities, where ethical design, governance transparency, and trust-building are essential for long-term societal adoption. Policy and industry implications emphasise aligning technological innovation with sustainability goals, including social equity, responsible data governance, and citizen-centric design, to support inclusive and resilient urban futures.

Cities are increasingly challenged by the scale, complexity, and uncertainty of spatio-temporal big data generated through urbanisation, climate change, and digitalisation. While classical high-performance computing has enabled significant advances in urban analytics, it is reaching practical limits in addressing combinatorial optimisation, high-dimensional data integration, and real-time decision-making. This paper introduces an urbanist perspective on quantum urbanism, examining how quantum computing and quantum AI can augment urban spatio-temporal big data analytics to support smart and sustainable city planning. Drawing on a bibliometric mapping, structured narrative review, and conceptual synthesis, the study identifies key domains where quantum approaches show emerging advantages over classical methods, including mobility optimisation, environmental monitoring, climate risk modelling, and infrastructure resilience. A conceptual framework is proposed to integrate hybrid quantum-classical workflows into urban planning pipelines, linking quantum machine learning, optimisation, and data compression techniques with sustainability-driven decision-making aligned with the sustainable development goals. Rather than advancing algorithmic novelty, the paper focuses on translating quantum capabilities into planning-relevant insights, highlighting institutional readiness, data architecture requirements, and governance considerations. By situating quantum computing within urban sustainability and governance debates, the study provides a practitioner-oriented roadmap for cities seeking to prepare for quantum-enabled futures, while outlining critical research gaps and pathways for empirical validation for urban scholars. The paper contributes to smart and sustainable cities scholarship by reframing quantum technologies not as technical upgrades, but as transformative enablers of anticipatory, adaptive, and equitable urban governance.

In an era marked by rapid technological progress, the pivotal role of Artificial Intelligence (AI) is increasingly evident across various sectors, including local governments. These governmental bodies are progressively leveraging AI technologies to enhance service delivery to their communities, ranging from simple task automation to more complex engineering endeavours. As more local governments adopt AI, it is imperative to understand the functions, implications, and consequences of these advanced technologies. Despite the growing importance of this domain, a significant gap persists within the scholarly discourse. This study aims to bridge this void by exploring the applications of AI technologies within the context of local government service provision. Through this inquiry, it seeks to generate best practice lessons for local government and smart city initiatives. By conducting a comprehensive review of grey literature, we analysed 262 real-world AI implementations across 170 local governments worldwide. The findings underscore several key points: (a) there has been a consistent upward trajectory in the adoption of AI by local governments over the last decade; (b) local governments from China, the US, and the UK are at the forefront of AI adoption; (c) among local government AI technologies, natural language processing and robotic process automation emerge as the most prevalent ones; (d) local governments primarily deploy AI across 28 distinct services; and (e) information management, back-office work, and transportation and traffic management are leading domains in terms of AI adoption. This study enriches the existing body of knowledge by providing an overview of current AI applications within the sphere of local governance. It offers valuable insights for local government and smart city policymakers and decision-makers considering the adoption, expansion, or refinement of AI technologies in urban service provision. Additionally, it highlights the importance of using these insights to guide the successful integration and optimisation of AI in future local government and smart city projects, ensuring they meet the evolving needs of communities.

In an era marked by swift technological progress, the pivotal role of Artificial Intelligence (AI) is increasingly evident across various sectors, including local governments. These governmental bodies are progressively leveraging AI technologies to enhance service delivery to their communities, ranging from simple task automation to more complicated engineering endeavours. While more and more local governments are adopting AI, it is imperative to understand the functions, implications, and consequences of AI. Despite the growing importance of this domain, a significant gap persists within the scholarly discourse. This study strives to bridge this void by exploring the applications of AI technologies within the context of local government service provision and using this inquiry to generate lessons and best practices for similar smart city initiatives. Through a comprehensive grey literature review, we analysed 262 real-world AI implementations across 170 local governments worldwide. The findings underscore several key points: (a) There has been a consistent upward trajectory in the adoption of AI by local governments over the last decade; (b) Local governments from China, the US, and the UK are at the forefront of AI adoption; (c) Among local government AI technologies, Natural Language Processing and Robotic Process Automation emerge as the most prevalent ones; (d) Local governments primarily deploy AI across 28 distinct services; (e) Information management, back-office work, and transportation and traffic management are leading domains in terms of AI adoption. This study enriches the extant body of knowledge by providing an overview of existing AI applications within the sphere of local governance. It offers insights for smart city policymakers and decision-makers considering the adoption, expansion, or refinement of AI technologies in urban service provision. Additionally, it underscores the importance of using these insights to guide the successful integration and optimisation of AI in future smart city projects, ensuring they meet the evolving needs of communities.

As digital technology continues to evolve rapidly and get integrated into various aspects of our cities and societies, the alignment of technological advancements with societal values becomes paramount. The evolving socio-technical landscape has prompted an increased focus on responsible innovation and technology (RIT) among technology companies, driven by mounting public scrutiny, regulatory pressure, and concerns about reputation and long-term sustainability. This study contributes to the ongoing discourse on responsible practices by conducting a policy review that delves into insights from the most influential high-tech companies’—so-called tech giants’—RIT guidance. The findings disclose that (a) leading high-tech companies have started to focus on RIT; (b) the main RIT policy focus of the leading high-tech companies is artificial intelligence; (c) trustworthiness and acceptability of technology are the most common policy areas; (d) affordability related to technology outcomes and adoption is almost absent from the policy; and (e) sustainability considerations are rarely part of the RIT policy, but are included in annual corporate reporting. Additionally, this paper proposes a RIT assessment framework that integrates views from the policy community, academia, and the industry and can be used for evaluating how well high-tech companies adhere to RIT practices. The knowledge assembled in this study is instrumental in advancing RIT practices, ultimately contributing to technology-driven cities and societies that prioritise human and social well-being.

In an era in which technological advancements have a profound impact on our cities and societies, it is crucial to ensure that digital technology is not only driven by technological progress with economic goals but that it can also fulfill moral and social responsibilities. Hence, it is needed to advocate for ‘Responsible Innovation and Technology’ (RIT) to ensure cities and societies can harness the potential of technological progress and prosperity while safeguarding the well-being of individuals and communities. This study conducts a PRISMA review to explore and understand RIT concepts and its characteristics. In this study, we emphasize that RIT should deliver acceptable, accessible, trustworthy, and well governed technological outcomes, while ensuring these outcomes are aligned with societal desirability and human values, and should also be responsibly integrated into our cities and societies. The main contribution of this study is to identify and clarify the key characteristics of RIT, which has not been performed in such detail so far. The study, reported in this paper, also broadens the understanding of responsible research and innovation in the technosphere, particularly from a bottom-up perspective. Furthermore, the paper develops an RIT conceptual framework outlining its possible design procedures, which could be used by governments, companies, practitioners, researchers, and other stakeholders as a tool to address the grand challenges that accompany technological and scientific progress. The framework also informs science, technology, and innovation policy.