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Cited by 337Smart Cities and TechnologiesImpact of AI and Big Data on Business and SocietyArtificial Intelligence Applications

The sustainability of artificial intelligence: an urbanistic viewpoint from the lens of smart and sustainable cities

Open access
Yigitcanlar, Tan, Cugurullo, Federico·2020·Sustainability
DOI 10.3390/su12208548
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Abstract

The popularity and application of artificial intelligence (AI) are increasing rapidly all around the world—where, in simple terms, AI is a technology which mimics the behaviors commonly associated with human intelligence. Today, various AI applications are being used in areas ranging from marketing to banking and finance, from agriculture to healthcare and security, from space exploration to robotics and transport, and from chatbots to artificial creativity and manufacturing. More recently, AI applications have also started to become an integral part of many urban services. Urban artificial intelligences manage the transport systems of cities, run restaurants and shops where every day urbanity is expressed, repair urban infrastructure, and govern multiple urban domains such as traffic, air quality monitoring, garbage collection, and energy. In the age of uncertainty and complexity that is upon us, the increasing adoption of AI is expected to continue, and so its impact on the sustainability of our cities. This viewpoint explores and questions the sustainability of AI from the lens of smart and sustainable cities, and generates insights into emerging urban artificial intelligences and the potential symbiosis between AI and a smart and sustainable urbanism. In terms of methodology, this viewpoint deploys a thorough review of the current status of AI and smart and sustainable cities literature, research, developments, trends, and applications. In so doing, it contributes to existing academic debates in the fields of smart and sustainable cities and AI. In addition, by shedding light on the uptake of AI in cities, the viewpoint seeks to help urban policymakers, planners, and citizens make informed decisions about a sustainable adoption of AI.

AI snapshot

Written from the paper’s full text.

TL;DR

This viewpoint argues that AI is increasingly embedded in urban systems, but its sustainability is not guaranteed: the artificially intelligent city is not automatically a sustainable city. It calls for balancing technology with policy and community, and for stakeholder engagement, ethics, regulation, and AI as a common good.

Key findings

  • AI’s urban benefits and risks are domain-specific across the economy, society, environment, and governance. For the environment, prospects include environmental monitoring, optimizing energy consumption and production, and optimizing transport systems; constraints include biased decisions, increased urban sprawl, more motor vehicle kilometers traveled, destabilized property values, heavy energy dependency, and increased carbon footprints.
  • The smart and sustainable city framework uses an Input-Process-Output-Impact approach, with technology, policy, and community as the three processes. Technology will only lead to sustainability if its adequateness is scrutinized via community engagement and its implementation is carried out via sound policy and government monitoring.
  • The paper describes AI levels as reactive machine (Level 1), independent AI (Level 2), mindful AI (Level 3), and super AI (Level 4), and states that current practice is artificial narrow intelligence and that AI evolution has reached only two levels out of four. It also outlines autonomy levels 0–5, where Level 5 is complete autonomy and decisions are taken by an AI in an unsupervised manner.
  • AI applications can potentially contribute to achieving 17 Sustainable Development Goals, with application areas including climate change/crisis mitigation, ocean health, clean air, biodiversity and conservation, clean water security, and weather and disaster resilience. However, the paper argues that AI’s drawbacks are equal to its potentials, requiring responsible and ethical AI, regulation, and AI commons.

Methods

  • This is a viewpoint that deploys a thorough review of the current status of AI and smart and sustainable cities literature, research, developments, trends, and applications.
  • It draws on a systematic literature review by Yigitcanlar et al. [124] of 99 peer-reviewed research articles concentrating on both smart cities and AI, organized under four smart city domains: economy, society, environment, and governance.
  • The paper presents conceptual frameworks and figures; no primary empirical data collection or statistical analysis is reported.

Limitations

  • The paper states that further theoretical and empirical investigations across disciplines are required; AI in smart and sustainable cities is an emerging area of research. It also states that there is neither an ideal AI system nor an ideal smart and sustainable city that can serve as a universal model, and that the very idea of a global paradigm is questionable given geographical differences.
  • Evident from the text: as a viewpoint, it relies on literature synthesis and illustrative examples rather than original empirical testing, and it does not detail a systematic review protocol for its own review.
  • Evident from the text: the provided manuscript contains duplicated passages and incomplete sentences (e.g., “This vast field of AI includes technologies with at least one of the following capabilities: .” and “before we get to .”), which may affect clarity.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.3390/su12208548

Cites

199 of 199 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

0 of 55 cited sources checked · 0 supported · 0 flagged

  • Premisereasoning

    In recent years, the focus of smart-city research has shifted towards the 'smart and sustainable city', in the attempt to rebalance the economic, social, and environmental dimensions of smart urbanism.

    “This is why, in recent years, the focus of smart-city research has shifted towards the 'smart and sustainable city', in the attempt to rebalance the economic, social, and environmental dimensions of smart urbanism [76][77][78].”
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    • cites [76][77][78]

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  • Premisecitation

    In recent years, AI applications have started to become an integral part of the city.

    “In recent years, AI applications have been also started to become an integral part of the city.”
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    • cites [8][9][10]

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    • cites [11] Macrorie, R., Marvin, S., and While, A. (2020). Robotics and automation in the city: A research agenda. Urban. Geogr. source

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    • cites [12] Mende, 2019, Service robots rising: How humanoid robots influence service experiences and elicit compensatory consumer responses, J. Mark. Res. source

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    • cites [13] Caprotti, 2020, Emerging platform urbanism in China: Reconfigurations of data, citizenship and materialities, Technol. Forecast. Soc. Chang. source

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    • cites [14] Barns, S. (2019). Platform Urbanism: Negotiating Platform Ecosystems in Connected Cities, Palgrave Macmillan. source

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  • Interpretationreasoning

    Unsupervised AIs have to make important decisions and take actions that can actually kill.

    “Here unsupervised, AIs have to make important decisions and take actions that can actually kill.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: AI technology is progressing fast, thereby gaining more and more autonomy in cities.
  • Premisecitation

    When urban development is unregulated, key sustainability themes such as justice and environmental preservation get neglected and overshadowed by economic interests.

    “It is well documented in urban studies that, when urban development is unregulated, key sustainability themes (such as justice and environmental preservation) get neglected and overshadowed by economic interests [198,199].”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites [198] Datta, A., and Shaban, A. (2016). Speed kills: Fast urbanism and endangered sustainability in the Masdar City project. Mega-Urbanization in the Global South: Fast Cities and New Urban Utopias of the Postcolonial State, Routledge. source

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    • cites [199] Imrie, 2009, Regulating design: The practices of architecture, governance and control, Urban. Stud. source

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  • Premisecitation

    In the governance domain of smart cities, the AI focus is predominately on national and public security, urban governance and decision-making in government.

    “In terms of the 'governance' domain of smart cities, the AI focus is predominately on national and public security, urban governance and decision-making in government.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [124] Yigitcanlar, T., Desouza, K., Butler, L., and Roozkhosh, F. (2020). Contributions and risks of artificial intelligence (AI) in building smarter cities: Insights from a systematic review of the literature. Energies, 13. source

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  • Classified as probably not a substantial claim. 34
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    Premisecitation

    Digital technologies are increasingly offering new opportunities for cities in their journey to become smart and sustainable, especially in relation to issues of community engagement and participatory governance.

    “Digital technologies are increasingly offering new opportunities for cities in their journey to become smart and sustainable-especially in relation to issues of community engagement and participatory governance [84].”
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    • cites [84] Zhuravleva, 2019, Sustainable smart cities: Networked digital technologies, cognitive big data analytics, and information technology-driven economy, Geopolit. Hist. Int. Relat. source

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    Premisecitation

    Existing smart cities are often disproportionately driven by economic objectives and incapable of addressing social and environmental concerns.

    “Numerous studies have shown that, actually, existing smart cities are often disproportionately driven by economic objectives and incapable of addressing social and environmental concerns [70][71][72][73][74][75].”
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    • cites [70][71][72][73][74][75]

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    Premisecitation

    There is neither a universal definition of AI, nor an established blueprint to build one.

    “There is neither a universal definition of AI, nor an established blueprint to build one [4,90].”
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    • cites [4] Bostrom, N. (2017). Superintelligence, Oxford University Press.

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    • cites [90] Clifton, 2020, When machines think for us: The consequences for work and place, Camb. J. Reg. Econ. Soc. source

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    Premisecitation

    AI applications are being used in areas ranging from marketing to banking and finance, from agriculture to healthcare and security, from space exploration to robotics and transport, and from chatbots to artificial creativity and manufacturing.

    “AI applications are being used in areas ranging from marketing to banking and finance, from agriculture to healthcare and security, from space exploration to robotics and transport, and from chatbots to artificial creativity and manufacturing [6,7].”
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    • cites [6] Yun, J., Lee, D., Ahn, H., Park, K., Lee, S., and Yigitcanlar, T. (2016). Not deep learning but autonomous learning of open innovation for sustainable artificial intelligence. Sustainability, 8. source

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    • cites [7] Faisal, A., Yigitcanlar, T., Kamruzzaman, M., and Paz, A. (2020). Mapping two decades of autonomous vehicle research: A systematic scientometric analysis. J. Urban. Technol. source

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    Interpretationcitation

    Technology will only lead to sustainability if its adequateness is thoroughly scrutinized via community engagement, and its implementation is carried out via a sound policy and government monitoring.

    “In other words, technology will only lead to sustainability if its adequateness is thoroughly scrutinized via community engagement, and its implementation is carried out via a sound policy and government monitoring [79].”
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    • cites [79] Yigitcanlar, 2019, The making of smart cities: Are Songdo, Masdar, Amsterdam, San Francisco and Brisbane the best we could build?, Land Use Policy source

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    Premisecitation

    Cities are the main hubs and drivers of most socioeconomic activities, political actions, and environmental transformations.

    “Given that cities are the main hubs and drivers of most socioeconomic activities, political actions, and environmental transformations, it is important to understand how the development of AI and the development of the city are intertwining [123].”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [123] 2017, AI and robotics for the city: Imagining and transforming social infrastructure in San Francisco, Yokohama, and Lviv, Field Actions Sci. Rep.

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    Premisecitation

    The concepts of innovation and sustainability, and Internet-of-things (IoT) and artificial intelligence (AI) technologies, are the dominant ones in Australia.

    “The results have shown that the concepts of innovation and sustainability, and Internet-of-things (IoT) and artificial intelligence (AI) technologies, are the dominant ones.”
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    • cites [87] Yigitcanlar, T., Kankanamge, N., and Vella, K. (2020). How are the smart city concepts and technologies perceived and utilized? A systematic geo-twitter analysis of smart cities in Australia. J. Urban. Technol. source

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    Premisecitation

    These top technologies are merging today to form artificial-intelligence-of-things (AIoT) to achieve more efficient IoT operations, improve decision-making and human-machine interactions, and enhance data management and analytics.

    “Unsurprisingly, these top technologies are merging today to form artificial-intelligence-of-things (AIoT) [88] to achieve more efficient IoT operations, improve decision-making and human-machine interactions, and enhance data management and analytics [89].”
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    • cites [88] Adly, 2020, Approaches based on artificial intelligence and the internet of intelligent things to prevent the spread of COVID-19: Scoping review, J. Med. Internet Res. source

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    • cites [89] Mohamed, 2020, The relation of artificial intelligence with internet of things: A survey, J. Cybersecur. Inf. Manag.

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    Premisecitation

    AI has already entered our cities, and it is therefore essential to critically examine and question its urban sustainability potential.

    “After all, AI has already entered our cities, and it is therefore essential to critically examine and question its urban sustainability potential [15].”
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    • cites [15] Cugurullo, 2020, Urban artificial intelligence: From automation to autonomy in the smart city, Front. Sustain. Cities source

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    Premisecitation

    Smart and sustainable cities utilize digital technologies to make infrastructure services more efficient and reactive to reduce resource consumption, increase environmental quality, and cut down on carbon emissions.

    “where such cities utilize digital technologies to make infrastructure services more efficient and reactive to reduce resource consumption, increase environmental quality, and cut down on carbon emissions [20].”
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    • cites [20] Evans, 2019, Smart and sustainable cities? Pipedreams, practicalities and possibilities, Local Environ. source

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    Interpretationcitation

    Cities should not be understood and treated as mere technological artefacts, but rather as social processes.

    “cities should not be understood and treated as mere technological artefacts, but rather as social processes”
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    • cites [81][82][83]

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    Interpretationcitation

    In order to create cities that are smart and sustainable, we actually need a balanced view on the community, technology, and policy trio as the driver of transformation.

    “The framework underlines that, despite the prevalent technocentric perspective in the making of smart cities, in order to create cities that are smart and sustainable, we actually need a balanced view on the community, technology, and policy trio as the driver of transformation.”
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    • cites [79] Yigitcanlar, 2019, The making of smart cities: Are Songdo, Masdar, Amsterdam, San Francisco and Brisbane the best we could build?, Land Use Policy source

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  • Classified as probably not a substantial claim.

    Study design and conductnone given

    This viewpoint deploys a thorough review of the current status of AI and smart and sustainable cities literature, research, developments, trends, and applications.

    “In terms of methodology, this viewpoint deploys a thorough review of the current status of AI and smart and sustainable cities literature, research, developments, trends, and applications.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing). May combine two claims.

    Premisecitation

    There is a large variety of smart and sustainable city technologies available today and their list is exhaustingly long.

    “There is a large variety of smart and sustainable city technologies available today and their list is exhaustingly long [85,86].”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [85] Chaurasia, V.K., Yunus, A., and Singh, M. (2020). An overview of smart city: Observation, technologies, challenges and blockchain applications. Blockchain Technology for Smart Cities, Springer. source

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    • cites [86] Ullah, 2020, Applications of artificial intelligence and machine learning in smart cities, Comput. Commun. source

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  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationcitation

    Urban artificial intelligences are embodied in urban spaces, urban infrastructures, and urban technologies, which together are turning cities into autonomous entities operating in an unsupervised manner.

    “We refer to this strand of AI as urban artificial intelligences-where AIs are embodied in urban spaces, urban infrastructures, and urban technologies, which together are turning cities into autonomous entities operating in an unsupervised manner [15].”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [15] Cugurullo, 2020, Urban artificial intelligence: From automation to autonomy in the smart city, Front. Sustain. Cities source

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    Premisecitation

    AI applications can potentially contribute to achieving 17 Sustainable Development Goals (SDGs).

    “Overall, as Vinuesa et al. [104] have argued, AI applications can potentially contribute to achieving 17 Sustainable Development Goals (SDGs).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [104] Vinuesa, 2020, The role of artificial intelligence in achieving the sustainable development goals, Nat. Commun. source

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    Interpretationcitation

    Sustainability should not be approached in a one-dimensional way, but rather holistically as the equilibrium among diverse social, environmental, and economic spheres.

    “sustainability should not be approached in a one-dimensional way, but rather holistically as the equilibrium among diverse social, environmental, and economic spheres [81][82][83].”
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    • cites [81][82][83]

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    Premisecitation

    AI is one of the most powerful and disruptive technologies of our time, and its influence on urban settlements and activities is growing rapidly, ultimately affecting everyday life.

    “AI is one of the most powerful and disruptive technologies of our time, and its influence on urban settlements and activities is growing rapidly, ultimately affecting everyday life [121,122].”
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    • cites [121] Greenfield, A. (2018). Radical Technologies: The Design of Everyday Life, Verso Books.

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    • cites [122] Lu, 2018, Brain intelligence: Go beyond artificial intelligence, Mob. Netw. Appl. source

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    Interpretationcitation

    Active collaboration among a wide and inclusive range of stakeholders in the development and deployment stages will improve the sustainability potential of AI.

    “Active collaboration among a wide and inclusive range of stakeholders-ideally in the form of quadruple helix model participation of public, private, academia and community-in the development and deployment stages, in particular, will improve the caliber of the sustainability potential of AI [180,181].”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [180] Erskine, M. (2019, January 20–22). Artificial intelligence, the emerging needs for human factors engineering, risk management and stakeholder engagement. Proceedings of the World Engineers Convention, Engineers Australia, Melbourne, Australia.

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    • cites [181] Loi, D., Wolf, C.T., Blomberg, J.L., Arar, R., and Brereton, M. (2019, January 23–28). Co-designing AI futures: Integrating AI ethics, social computing, and design. Proceedings of the 2019 on Designing Interactive Systems Conference, San Diego, CA, USA. source

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    • Rests on an assumption: AI technologies are created exclusively by technology companies without any or much consultation with wider interest groups or stakeholders.

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    Premisecitation

    An AI for all would require establishing AI commons, and a similar attempt has been made to establish digital commons.

    “An AI for all would require establishing AI commons [201] and a similar attempt has been previously made to establish digital commons [202].”
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    • cites [201] Tzimas, T. (2018, January 22–23). Artificial intelligence as global commons and the “international law supremacy” principle. Proceedings of the 10th International RAIS Conference on Social Sciences and Humanities, Princeton, NJ, USA. source

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    • cites [202] Rottz, M., Sell, D., Pacheco, R., and Yigitcanlar, T. (2019). Digital commons and citizen coproduction in smart cities: Assessment of Brazilian municipal e-government platforms. Energies, 12. source

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  • Probably not a substantial claim: may not pass S2 (checkable), S4 (based). May combine two claims.

    Interpretationreasoning

    Unresolved issues of transparency, fairness, ethics, and preservation of human values are intrinsic to AI and hinder its sustainability.

    “These unresolved issues are intrinsic to AI and thus hinder its sustainability.”
    Quote in the paperNot a substantial claim

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    Premisereasoning

    Numerous smart-city projects have been implemented and an even larger number is under development, while the evolution of AI has reached only two levels out of four.

    “As Sections 3 and 4 have illustrated, numerous smart-city projects have been implemented and an even larger number is under development, while the evolution of AI has reached only two levels out of four.”
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  • Classified as probably not a substantial claim. May combine two claims.

    Premisecitation

    Automated technology repetitively follows patterns previously established by a human intelligence, while autonomous technology establishes its own patterns, seldom repeating the exact same action.

    “The key difference between automation and autonomy is that an automated technology repetitively follows patterns previously established by a human intelligence, while an autonomous technology establishes its own patterns, seldom repeating the exact same action [15].”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [15] Cugurullo, 2020, Urban artificial intelligence: From automation to autonomy in the smart city, Front. Sustain. Cities source

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    Interpretationnone given

    A monopolistic structure behind technology development and deployment is problematic because a lack of competition limits technological variation.

    “A monopolistic structure behind technology development and deployment is problematic as a lack of competition limits technological variation.”
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  • Probably not a substantial claim: may not pass S2 (checkable). May combine two claims.

    Premisecitation

    There is neither an ideal AI system nor an ideal smart and sustainable city that can serve as a universal model of development, and the idea of a global paradigm is questionable given geographical differences.

    “For sure, at the moment there is neither an ideal AI system, nor an ideal smart and sustainable city that can serve as a universal model of development and, given the many geographical differences that exist in the world, the very idea of having a global paradigm is questionable in the first place [68,174,175].”
    Quote in the paperNot a substantial claim0 of 3 sources checked
    • cites [68] Karvonen, A., Cugurullo, F., and Caprotti, F. (2018). Inside Smart Cities: Place, Politics and Urban Innovation, Routledge. source

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    • cites [174] Yigitcanlar, 2018, Smart city policies revisited: Considerations for a truly smart and sustainable urbanism practice, World Technopolis Rev.

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    • cites [175] Yigitcanlar, 2009, Planning for smart urban ecosystems: Information technology applications for capacity building in environmental decision making, Theor. Empir. Res. Urban. Manag.

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    Interpretationreasoning

    Avoiding AI monopolies would promote democratization of AI research and practice and decrease the risk of a singleton.

    “This, in turn, would also promote the democratization of AI research and practice, as well as decrease the risk of the formation of a singleton [188,189].”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [188] Allen, 2019, Democratizing AI, J. Am. Coll. Radiol. source

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    • cites [189] Moreau, E., Vogel, C., and Barry, M. (2019). A paradigm for democratizing artificial intelligence research. Innovations in Big Data Mining and Embedded Knowledge, Springer. source

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  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Interpretationreasoning

    Avoiding AI monopolies can make AI technologies more affordable and support open AI development.

    “Avoiding AI monopolies can make AI technologies more affordable and support current efforts in 'open AI' development.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing). May combine two claims.

    Premisenone given

    The fields of smart and sustainable cities and AI are in constant evolution.

    “Furthermore, it is important to recognize that both the fields of smart and sustainable cities and AI are in constant evolution.”
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    Premisecitation

    A study by Yigitcanlar et al. investigated these questions through a thorough systematic literature review of 99 peer-reviewed research articles concentrating on both smart cities and AI.

    “A study by Yigitcanlar et.al. [124] investigated these questions through a thorough systematic literature review-99 peer-reviewed research articles concentrating on both smart cities and AI.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [124] Yigitcanlar, T., Desouza, K., Butler, L., and Roozkhosh, F. (2020). Contributions and risks of artificial intelligence (AI) in building smarter cities: Insights from a systematic review of the literature. Energies, 13. source

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  • May combine two claims.

    Interpretationreasoning

    A singleton is unlikely for Level 1 and 2 AIs, but not a remote possibility if only one tech company can build an artificial superintelligence.

    “This is an unlikely situation when it comes to Level 1 and 2 AIs, but it might not be a remote possibility if only one tech company in the world has the capacity to build an artificial super intelligence.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S4 (based). May combine two claims.

    Interpretationreasoning

    Expensive AIs are ultimately elitist AIs, which only a rich minority can afford.

    “Expensive AIs are ultimately elitist AIs, which only a rich minority can afford.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationreasoning

    AI cannot achieve sustainability and the common good if it is not regulated.

    “AI cannot achieve sustainability and the common good if it is not regulated.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S4 (based). May combine two claims.

    Interpretationreasoning

    Elitist AIs can only be unevenly distributed, creating a divide among richer and poorer cities and internal fractures within cities.

    “Elitist AIs can only be unevenly distributed, thus creating a divide among richer and poorer cities, as well as internal fractures within individual cities where small premium enclaves coexist next to disadvantaged districts.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S4 (based).

    Interpretationreasoning

    No common future can be envisioned and realized unless proper forms of democratic governance are in place.

    “Given that the ethos of sustainability is about achieving a common future, we argue that no common future can be envisioned and realized unless proper forms of democratic governance are in place.”
    Quote in the paperNot a substantial claim

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    Premisecitation

    An autonomous Uber was incapable of dealing with the uncertainty typical of unconfined urban spaces, and its incapacity killed a woman crossing a road outside the designated crossing lane.

    “An autonomous Uber was incapable of dealing with the uncertainty that is typical of unconfined urban spaces, and its incapacity killed a woman that was crossing a road outside the designated crossing lane [173].”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [173] Stilgoe, J. (2019). Who’s Driving Innovation? New Technologies and the Collaborative State, Springer Nature. source

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    Interpretationreasoning

    If different AI users can do whatever they want, it is extremely unlikely that the common good will be achieved.

    “In a situation in which different AI users (or potentially different mindful and super intelligent AIs) can do whatever they want, it is extremely unlikely that the common good will be achieved.”
    Quote in the paperNot a substantial claim

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    Interpretationreasoning

    Whether the AI revolution creates a utopian or dystopian future depends on how we tackle the drawbacks of AI and how we utilize AI in cities, businesses, and lives.

    “The answer to this question fully depends on how we are going to tackle the drawbacks of AI, and how we are going to utilize AI in our cities, businesses and, more in general, lives.”
    Quote in the paperNot a substantial claim

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    Premisecitation

    AI commons are supposed to allow anyone, anywhere, to enjoy the multiple benefits that AI can provide.

    “AI commons are supposed to allow anyone, anywhere, to enjoy the multiple benefits that AI can provide [203].”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [203] Cath, 2018, Artificial intelligence and the ‘good society’: The US, EU, and UK approach, Sci. Eng. Ethics

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    AI is an arcane technology: although it is part of everyday life for many people, its mechanics and actual functioning are understood by only a few.

    “This is a challenging problem because, as Greenfield [121] notes, AI is an arcane technology meaning that, although it is already part of the everyday of many people, its mechanics and actual functioning are understood by only a few.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [121] Greenfield, A. (2018). Radical Technologies: The Design of Everyday Life, Verso Books.

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S2 (checkable).

    Premisecitation

    Affordability is critical for a wider uptake of AI across cities through public sector funds.

    “This is critical for a wider uptake of AI across cities through public sector funds [186,187].”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [186] Masanja, 2020, The application of open source artificial intelligence as an approach to frugal innovation in Tanzania, Int. J. Res. Innov. Appl. Sci.

      Not checked in the free run.

    • cites [187] Brock, 2019, Demystifying AI: What digital transformation leaders can teach you about realistic artificial intelligence, Calif. Manag. Rev. source

      Not checked in the free run.

40 of 40

  • The paper relies on this without support.

    AI technologies are created exclusively by technology companies without any or much consultation with wider interest groups or stakeholders.

    “In general, AI technologies are created exclusively by technology companies without any or much consultation with wider interest groups or stakeholders.”

  • The paper relies on this without support.

    The blackbox nature of AI decisions, the possibility of AI failing in life-or-death contexts, and cybersecurity vulnerabilities limit public trust.

    “The blackbox nature of the decisions taken by AIs without much transparency (which, at times, are wrong), the possibility of AI failing in a life-or-death context, and cybersecurity vulnerabilities all limit public trust.”

  • The paper relies on this without support.

    AI technology is progressing fast, thereby gaining more and more autonomy in cities.

    “From an urban point of view, AI technology is progressing fast, thereby gaining more and more autonomy in cities.”

  • The paper relies on this without support.

    In experimental cities, parts of the built environment are already not automated but rather autonomous.

    “Especially in experimental cities, where the pace of technological innovation is usually rapid, we can already see parts of the built environment that are not automated but rather autonomous.”
4 of 4

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • Five autonomy levels are described as Levels 0 through 5

    Minor

    The paper says there are five levels of autonomy, but its numbering includes Level 0 and Levels 1-5, making six levels.

1 of 1

Cites

Flagged first, then by citations

Research works printed but not linked: 12

  1. Schalkoff, R.J. (1990). Artificial Intelligence: An Engineering Approach, McGraw-Hill.
  2. Bostrom, N. (2017). Superintelligence, Oxford University Press.
  3. Gould-Wartofsky, M.A. (2015). The Occupiers: The Making of the 99 Percent Movement, Oxford University Press.
  4. Accord, 2017, Trump decision on climate change ‘major disappointment’: United Nations, Waste Water Manag. Aust., 44, 35
  5. Russell, S.J., and Norvig, P. (2016). Artificial Intelligence: A Modern Approach, Pearson Education Limited.
  6. Bach, 2020, When artificial intelligence becomes general enough to understand itself. Commentary on Pei Wang’s paper “on defining artificial intelligence”, J. Artif. Gen. Intell., 11, 15
  7. Gurzadyan, G.A. (1996). Theory of Interplanetary Flights, CRC Press.
  8. Tegmark, M. (2017). Life 3.0: Being Human in the Age of Artificial Intelligence, Penguin.
  9. Agrawal, A., Gans, J., and Goldfarb, A. (2018). Prediction Machines: The Simple Economics of Artificial Intelligence, Harvard Business Press.
  10. O’Neil, C. (2016). Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy, Penguin.
  11. Yigitcanlar, 2009, Planning for smart urban ecosystems: Information technology applications for capacity building in environmental decision making, Theor. Empir. Res. Urban. Manag., 4, 5
  12. Masanja, 2020, The application of open source artificial intelligence as an approach to frugal innovation in Tanzania, Int. J. Res. Innov. Appl. Sci., 5, 36

Cited by

Sorted by citations

Related

Authors
Yigitcanlar, T., & Cugurullo, F.
Affiliations
  • School of Built Environment, Queensland University of Technology, 2 George Street, Brisbane, QLD 4000, Australia
  • Trinity College Dublin (IE)
ORCID
Venue
Sustainability
Publisher
MDPI AG
Published
2020-10-15
Volume
12
Issue
20
Pages
8548
ISSN
2071-1050 (ISSN-L)
DOI
10.3390/su12208548
OpenAlex
W3092843175
Semantic Scholar
21b413bbc7fac83c8c75a94125a0c8642e154d3b
Cited by
337
References
199
Citations by year
2026: 51 · 2025: 65 · 2024: 74 · 2023: 62 · 2022: 45 · 2021: 34 · 2020: 6
FWCI
18.91
Type
journal article
Language
en
Open access
Licence
Locations
  • Sustainability (publishedVersion, cc-by)
  • QUT ePrints (Queensland University of Technology) (submittedVersion, cc-by)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Physical Sciences › Engineering › Media Technology › Smart Cities and Technologies
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Impact of AI and Big Data on Business and Society
  • Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
Keywords
artificial intelligence, smart cities, sustainable cities, urbanism, urban planning, urban sustainability, urban transport, energy management, air quality monitoring, garbage collection, urban infrastructure

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-08.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-08.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

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