IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i16p8952-d611814.html
   My bibliography  Save this article

Green Artificial Intelligence: Towards an Efficient, Sustainable and Equitable Technology for Smart Cities and Futures

Author

Listed:
  • Tan Yigitcanlar

    (School of Architecture and Built Environment, Queensland University of Technology, 2 George Street, Brisbane, QLD 4000, Australia
    School of Technology, Federal University of Santa Catarina, Campus Universitario, Florianopolis, SC 88040-900, Brazil)

  • Rashid Mehmood

    (High Performance Computing Center, King Abdulaziz University, Al Ehtifalat St, Jeddah 21589, Saudi Arabia)

  • Juan M. Corchado

    (BISITE Research Group, University of Salamanca, 37007 Salamanca, Spain
    Air Institute, IoT Digital Innovation Hub, 37188 Salamanca, Spain
    Department of Electronics, Information and Communication, Faculty of Engineering, Osaka Institute of Technology, Osaka 535-8585, Japan)

Abstract

Smart cities and artificial intelligence (AI) are among the most popular discourses in urban policy circles. Most attempts at using AI to improve efficiencies in cities have nevertheless either struggled or failed to accomplish the smart city transformation. This is mainly due to short-sighted, technologically determined and reductionist AI approaches being applied to complex urbanization problems. Besides this, as smart cities are underpinned by our ability to engage with our environments, analyze them, and make efficient, sustainable and equitable decisions, the need for a green AI approach is intensified. This perspective paper, reflecting authors’ opinions and interpretations, concentrates on the “green AI” concept as an enabler of the smart city transformation, as it offers the opportunity to move away from purely technocentric efficiency solutions towards efficient, sustainable and equitable solutions capable of realizing the desired urban futures. The aim of this perspective paper is two-fold: first, to highlight the fundamental shortfalls in mainstream AI system conceptualization and practice, and second, to advocate the need for a consolidated AI approach—i.e., green AI—to further support smart city transformation. The methodological approach includes a thorough appraisal of the current AI and smart city literatures, practices, developments, trends and applications. The paper informs authorities and planners on the importance of the adoption and deployment of AI systems that address efficiency, sustainability and equity issues in cities.

Suggested Citation

  • Tan Yigitcanlar & Rashid Mehmood & Juan M. Corchado, 2021. "Green Artificial Intelligence: Towards an Efficient, Sustainable and Equitable Technology for Smart Cities and Futures," Sustainability, MDPI, vol. 13(16), pages 1-14, August.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:16:p:8952-:d:611814
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/16/8952/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/13/16/8952/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yigitcanlar, Tan & Han, Hoon & Kamruzzaman, Md. & Ioppolo, Giuseppe & Sabatini-Marques, Jamile, 2019. "The making of smart cities: Are Songdo, Masdar, Amsterdam, San Francisco and Brisbane the best we could build?," Land Use Policy, Elsevier, vol. 88(C).
    2. Desouza, Kevin C. & Dawson, Gregory S. & Chenok, Daniel, 2020. "Designing, developing, and deploying artificial intelligence systems: Lessons from and for the public sector," Business Horizons, Elsevier, vol. 63(2), pages 205-213.
    3. Kuziemski, Maciej & Misuraca, Gianluca, 2020. "AI governance in the public sector: Three tales from the frontiers of automated decision-making in democratic settings," Telecommunications Policy, Elsevier, vol. 44(6).
    4. Fosso Wamba, Samuel & Bawack, Ransome Epie & Guthrie, Cameron & Queiroz, Maciel M. & Carillo, Kevin Daniel André, 2021. "Are we preparing for a good AI society? A bibliometric review and research agenda," Technological Forecasting and Social Change, Elsevier, vol. 164(C).
    5. Lei Jin & Keran Duan & Xu Tang, 2018. "What Is the Relationship between Technological Innovation and Energy Consumption? Empirical Analysis Based on Provincial Panel Data from China," Sustainability, MDPI, vol. 10(1), pages 1-13, January.
    6. Tan Yigitcanlar & Marcus Foth & Md. Kamruzzaman, 2019. "Towards Post-Anthropocentric Cities: Reconceptualizing Smart Cities to Evade Urban Ecocide," Journal of Urban Technology, Taylor & Francis Journals, vol. 26(2), pages 147-152, April.
    7. Mora, Luca & Deakin, Mark & Reid, Alasdair, 2019. "Strategic principles for smart city development: A multiple case study analysis of European best practices," Technological Forecasting and Social Change, Elsevier, vol. 142(C), pages 70-97.
    8. Ya Zhou & Atreyi Kankanhalli, 2021. "AI Regulation for Smart Cities: Challenges and Principles," Public Administration and Information Technology, in: Elsa Estevez & Theresa A. Pardo & Hans Jochen Scholl (ed.), Smart Cities and Smart Governance, chapter 5, pages 101-118, Springer.
    9. Heidi Ledford, 2019. "Millions of black people affected by racial bias in health-care algorithms," Nature, Nature, vol. 574(7780), pages 608-609, October.
    10. Tan Yigitcanlar & Kevin C. Desouza & Luke Butler & Farnoosh Roozkhosh, 2020. "Contributions and Risks of Artificial Intelligence (AI) in Building Smarter Cities: Insights from a Systematic Review of the Literature," Energies, MDPI, vol. 13(6), pages 1-38, March.
    11. Song, Ma-Lin & Cao, Shao-Peng & Wang, Shu-Hong, 2019. "The impact of knowledge trade on sustainable development and environment-biased technical progress," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 512-523.
    12. Helen Margetts & Cosmina Dorobantu, 2019. "Rethink government with AI," Nature, Nature, vol. 568(7751), pages 163-165, April.
    13. Ricardo Vinuesa & Hossein Azizpour & Iolanda Leite & Madeline Balaam & Virginia Dignum & Sami Domisch & Anna Felländer & Simone Daniela Langhans & Max Tegmark & Francesco Fuso Nerini, 2020. "The role of artificial intelligence in achieving the Sustainable Development Goals," Nature Communications, Nature, vol. 11(1), pages 1-10, December.
    14. JinHyo Joseph Yun & Dooseok Lee & Heungju Ahn & Kyungbae Park & Tan Yigitcanlar, 2016. "Not Deep Learning but Autonomous Learning of Open Innovation for Sustainable Artificial Intelligence," Sustainability, MDPI, vol. 8(8), pages 1-20, August.
    15. Lena Bjørlo & Øystein Moen & Mark Pasquine, 2021. "The Role of Consumer Autonomy in Developing Sustainable AI: A Conceptual Framework," Sustainability, MDPI, vol. 13(4), pages 1-18, February.
    16. Tan Yigitcanlar & Md. Kamruzzaman, 2015. "Planning, Development and Management of Sustainable Cities: A Commentary from the Guest Editors," Sustainability, MDPI, vol. 7(11), pages 1-12, November.
    17. Tan Yigitcanlar & Federico Cugurullo, 2020. "The Sustainability of Artificial Intelligence: An Urbanistic Viewpoint from the Lens of Smart and Sustainable Cities," Sustainability, MDPI, vol. 12(20), pages 1-24, October.
    18. Didem Dizdaroglu & Tan Yigitcanlar, 2016. "Integrating urban ecosystem sustainability assessment into policy-making: insights from the Gold Coast City," Journal of Environmental Planning and Management, Taylor & Francis Journals, vol. 59(11), pages 1982-2006, November.
    19. Sarah Dennis & Alexander Paz & Tan Yigitcanlar, 2021. "Perceptions and Attitudes Towards the Deployment of Autonomous and Connected Vehicles: Insights from Las Vegas, Nevada," Journal of Urban Technology, Taylor & Francis Journals, vol. 28(3-4), pages 75-95, October.
    20. Di Vaio, Assunta & Palladino, Rosa & Hassan, Rohail & Escobar, Octavio, 2020. "Artificial intelligence and business models in the sustainable development goals perspective: A systematic literature review," Journal of Business Research, Elsevier, vol. 121(C), pages 283-314.
    21. Tan Yigitcanlar & Md. Kamruzzaman, 2019. "Smart Cities and Mobility: Does the Smartness of Australian Cities Lead to Sustainable Commuting Patterns?," Journal of Urban Technology, Taylor & Francis Journals, vol. 26(2), pages 21-46, April.
    22. Wenjuan Sun & Paolo Bocchini & Brian D. Davison, 2020. "Applications of artificial intelligence for disaster management," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 103(3), pages 2631-2689, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Fabio De Felice & Marta Travaglioni & Antonella Petrillo, 2021. "Innovation Trajectories for a Society 5.0," Data, MDPI, vol. 6(11), pages 1-30, November.
    2. Helen Onyeaka & Phemelo Tamasiga & Uju Mary Nwauzoma & Taghi Miri & Uche Chioma Juliet & Ogueri Nwaiwu & Adenike A. Akinsemolu, 2023. "Using Artificial Intelligence to Tackle Food Waste and Enhance the Circular Economy: Maximising Resource Efficiency and Minimising Environmental Impact: A Review," Sustainability, MDPI, vol. 15(13), pages 1-20, July.
    3. Claudio Sassanelli & Tiziano Arriga & Stefano Zanin & Idiano D'Adamo & Sergio Terzi, 2022. "Industry 4.0 Driven Result-oriented PSS: An Assessment in the Energy Management," International Journal of Energy Economics and Policy, Econjournals, vol. 12(4), pages 186-203, July.
    4. Aurélie Halsband, 2022. "Sustainable AI and Intergenerational Justice," Sustainability, MDPI, vol. 14(7), pages 1-11, March.
    5. Eman Alqahtani & Nourah Janbi & Sanaa Sharaf & Rashid Mehmood, 2022. "Smart Homes and Families to Enable Sustainable Societies: A Data-Driven Approach for Multi-Perspective Parameter Discovery Using BERT Modelling," Sustainability, MDPI, vol. 14(20), pages 1-65, October.
    6. Ana Cristina Fachinelli & Tan Yigitcanlar & Jamile Sabatini-Marques & Tatiana Tucunduva Philippi Cortese & Debora Sotto & Bianca Libardi, 2023. "Urban Smartness and City Performance: Identifying Brazilian Smart Cities through a Novel Approach," Sustainability, MDPI, vol. 15(13), pages 1-24, June.
    7. Tan Yigitcanlar, 2021. "Greening the Artificial Intelligence for a Sustainable Planet: An Editorial Commentary," Sustainability, MDPI, vol. 13(24), pages 1-9, December.
    8. Jieyin Lyu & Shouqin Zhou & Jingang Liu & Bingchun Jiang, 2023. "Intelligent-Technology-Empowered Active Emergency Command Strategy for Urban Hazardous Chemical Disaster Management," Sustainability, MDPI, vol. 15(19), pages 1-28, September.
    9. Tao Li & Junlin Zhu & Jianqiang Luo & Chaonan Yi & Baoqing Zhu, 2023. "Breaking Triopoly to Achieve Sustainable Smart Digital Infrastructure Based on Open-Source Diffusion Using Government–Platform–User Evolutionary Game," Sustainability, MDPI, vol. 15(19), pages 1-24, October.
    10. Nala Alahmari & Sarah Alswedani & Ahmed Alzahrani & Iyad Katib & Aiiad Albeshri & Rashid Mehmood, 2022. "Musawah: A Data-Driven AI Approach and Tool to Co-Create Healthcare Services with a Case Study on Cancer Disease in Saudi Arabia," Sustainability, MDPI, vol. 14(6), pages 1-41, March.
    11. Kris Hartley, 2023. "Public Perceptions About Smart Cities: Governance and Quality-of-Life in Hong Kong," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 166(3), pages 731-753, April.
    12. Wadim Strielkowski & Andrey Vlasov & Kirill Selivanov & Konstantin Muraviev & Vadim Shakhnov, 2023. "Prospects and Challenges of the Machine Learning and Data-Driven Methods for the Predictive Analysis of Power Systems: A Review," Energies, MDPI, vol. 16(10), pages 1-31, May.
    13. Istiak Ahmad & Fahad Alqurashi & Ehab Abozinadah & Rashid Mehmood, 2022. "Deep Journalism and DeepJournal V1.0: A Data-Driven Deep Learning Approach to Discover Parameters for Transportation," Sustainability, MDPI, vol. 14(9), pages 1-72, May.
    14. Muhammad Asgher Nadeem & Scott Uk-Jin Lee & Muhammad Usman Younus, 2022. "A Comparison of Recent Requirements Gathering and Management Tools in Requirements Engineering for IoT-Enabled Sustainable Cities," Sustainability, MDPI, vol. 14(4), pages 1-18, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tan Yigitcanlar, 2021. "Greening the Artificial Intelligence for a Sustainable Planet: An Editorial Commentary," Sustainability, MDPI, vol. 13(24), pages 1-9, December.
    2. Tan Yigitcanlar & Federico Cugurullo, 2020. "The Sustainability of Artificial Intelligence: An Urbanistic Viewpoint from the Lens of Smart and Sustainable Cities," Sustainability, MDPI, vol. 12(20), pages 1-24, October.
    3. Tao Li & Jianqiang Luo & Kaitong Liang & Chaonan Yi & Lei Ma, 2023. "Synergy of Patent and Open-Source-Driven Sustainable Climate Governance under Green AI: A Case Study of TinyML," Sustainability, MDPI, vol. 15(18), pages 1-21, September.
    4. Palmyra Repette & Jamile Sabatini-Marques & Tan Yigitcanlar & Denilson Sell & Eduardo Costa, 2021. "The Evolution of City-as-a-Platform: Smart Urban Development Governance with Collective Knowledge-Based Platform Urbanism," Land, MDPI, vol. 10(1), pages 1-25, January.
    5. Tan Yigitcanlar & Kevin C. Desouza & Luke Butler & Farnoosh Roozkhosh, 2020. "Contributions and Risks of Artificial Intelligence (AI) in Building Smarter Cities: Insights from a Systematic Review of the Literature," Energies, MDPI, vol. 13(6), pages 1-38, March.
    6. Seng Boon Lim & Jalaluddin Abdul Malek & Md Farabi Yussoff Md Yussoff & Tan Yigitcanlar, 2021. "Understanding and Acceptance of Smart City Policies: Practitioners’ Perspectives on the Malaysian Smart City Framework," Sustainability, MDPI, vol. 13(17), pages 1-31, August.
    7. Li, Wenda & Yigitcanlar, Tan & Liu, Aaron & Erol, Isil, 2022. "Mapping two decades of smart home research: A systematic scientometric analysis," Technological Forecasting and Social Change, Elsevier, vol. 179(C).
    8. D’Amico, Gaspare & Arbolino, Roberta & Shi, Lei & Yigitcanlar, Tan & Ioppolo, Giuseppe, 2022. "Digitalisation driven urban metabolism circularity: A review and analysis of circular city initiatives," Land Use Policy, Elsevier, vol. 112(C).
    9. Gaspare D’Amico & Roberta Arbolino & Lei Shi & Tan Yigitcanlar & Giuseppe Ioppolo, 2021. "Digital Technologies for Urban Metabolism Efficiency: Lessons from Urban Agenda Partnership on Circular Economy," Sustainability, MDPI, vol. 13(11), pages 1-23, May.
    10. Henrik Skaug Sætra, 2021. "AI in Context and the Sustainable Development Goals: Factoring in the Unsustainability of the Sociotechnical System," Sustainability, MDPI, vol. 13(4), pages 1-19, February.
    11. Wilson, Christopher & van der Velden, Maja, 2022. "Sustainable AI: An integrated model to guide public sector decision-making," Technology in Society, Elsevier, vol. 68(C).
    12. Mirko Guaralda & Greg Hearn & Marcus Foth & Tan Yigitcanlar & Severine Mayere & Lisa Law, 2020. "Towards Australian Regional Turnaround: Insights into Sustainably Accommodating Post-Pandemic Urban Growth in Regional Towns and Cities," Sustainability, MDPI, vol. 12(24), pages 1-13, December.
    13. Hanna Obracht-Prondzyńska & Ewa Duda & Helena Anacka & Jolanta Kowal, 2022. "Greencoin as an AI-Based Solution Shaping Climate Awareness," IJERPH, MDPI, vol. 19(18), pages 1-25, September.
    14. JinHyo Joseph Yun & Xiaofei Zhao & KwangHo Jung & Tan Yigitcanlar, 2020. "The Culture for Open Innovation Dynamics," Sustainability, MDPI, vol. 12(12), pages 1-21, June.
    15. Carmen Isensee & Kai-Michael Griese & Frank Teuteberg, 2021. "Sustainable artificial intelligence: A corporate culture perspective [Sustainable artificial intelligence: Eine unternehmenskulturelle Perspektive]," NachhaltigkeitsManagementForum | Sustainability Management Forum, Springer, vol. 29(3), pages 217-230, December.
    16. Noha Diab & Nicoleta Isac & Cosmin Dobrin, 2022. "Artificial Intelligence (AI) and Jobs: The Impact of Pandemic on Governmental Organizations in Istanbul - Turkey," REVISTA DE MANAGEMENT COMPARAT INTERNATIONAL/REVIEW OF INTERNATIONAL COMPARATIVE MANAGEMENT, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 23(1), pages 46-64, March.
    17. Tao Li & Junlin Zhu & Jianqiang Luo & Chaonan Yi & Baoqing Zhu, 2023. "Breaking Triopoly to Achieve Sustainable Smart Digital Infrastructure Based on Open-Source Diffusion Using Government–Platform–User Evolutionary Game," Sustainability, MDPI, vol. 15(19), pages 1-24, October.
    18. Jalaluddin Abdul Malek & Seng Boon Lim & Tan Yigitcanlar, 2021. "Social Inclusion Indicators for Building Citizen-Centric Smart Cities: A Systematic Literature Review," Sustainability, MDPI, vol. 13(1), pages 1-29, January.
    19. Sanaz Honarmand Ebrahimi & Marinus Ossewaarde & Ariana Need, 2021. "Smart Fishery: A Systematic Review and Research Agenda for Sustainable Fisheries in the Age of AI," Sustainability, MDPI, vol. 13(11), pages 1-20, May.
    20. Isensee, Carmen & Griese, Kai-Michael & Teuteberg, Frank, 2022. "Sustainable Artificial Intelligence im Marketing am Beispiel des SDG 12," PraxisWISSEN Marketing: German Journal of Marketing, AfM – Arbeitsgemeinschaft für Marketing, vol. 7(01/2022), pages 33-46.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:13:y:2021:i:16:p:8952-:d:611814. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.