Cited by 319Smart Cities and TechnologiesEthics and Social Impacts of AIArtificial Intelligence Applications

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

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Yigitcanlar, Tan, Mehmood, Rashid, Corchado, Juan M.·2021·Sustainability

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.

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Research works printed but not linked: 3

  1. Kirwan, C.; Fu, Z. Smart Cities and Artificial Intelligence: Convergent Systems for Planning, Design, and Operations; Elsevier: Oxford, UK, 2020.
  2. Jothiswaran, V.; Velumani, T. Jayaraman, R. Application of artificial intelligence in fisheries and aquaculture. Biot. Res. Today 2020, 2, 499-502.
  3. Estevez, E., Pardo, T., Scholl, H., Eds.; Springer: Singapore, 2021; pp. 101-118. 130. Fisher, D.H. Computing and AI for a Sustainable Future. IEEE Intell. Syst. 2011, 26, 14-18.

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Authors
Yigitcanlar, T., Mehmood, R., & Corchado, J. M.
Affiliations
  • School of Architecture and Built Environment, Queensland University of Technology, 2 George Street, Brisbane, QLD 4000, Australia
  • King Abdulaziz University (SA)
  • Universidad de Salamanca (ES)
Venue
Sustainability
Publisher
MDPI AG
Published
2021-08-10
Volume
13
Issue
16
Pages
8952
ISSN
2071-1050 (ISSN-L)
OpenAlex
W3192495768
Cited by
319
References
119
Citations by year
2026: 71 · 2025: 82 · 2024: 76 · 2023: 47 · 2022: 39 · 2021: 4
FWCI
18.50
Type
journal article
Language
en
Open access
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 › Safety Research › Ethics and Social Impacts of AI
  • Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
Keywords
green AI, smart cities, urban sustainability, urban equity, AI efficiency, urban planning, urban future, technocentrism, urbanization

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