Publication: Responsible or Sustainable AI? Circular Economy Models in Smart Cities
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Issued Date
2026-01-01
Resource Type
eISSN
20711050
Scopus ID
2-s2.0-105027432176
Journal Title
Sustainability Switzerland
Volume
18
Issue
1
Rights Holder(s)
SCOPUS
Bibliographic Citation
Sustainability Switzerland Vol.18 No.1 (2026)
Suggested Citation
Daovisan H. Responsible or Sustainable AI? Circular Economy Models in Smart Cities. Sustainability Switzerland Vol.18 No.1 (2026). doi:10.3390/su18010398 Retrieved from: https://hdl.handle.net/20.500.14740/55363
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Abstract
Responsible artificial intelligence (RAI) has been increasingly embedded within circular economy (CE) models to facilitate sustainable artificial intelligence (SAI) and to enable data-driven transitions in smart-city contexts. Despite this progression, limited synthesis has been undertaken to connect RAI and SAI principles with their translation into policy, particularly within deep learning contexts. Accordingly, this study was designed to integrate RAI and SAI research within CE-oriented smart-city models. A science-mapping and knowledge-translation design was employed, with data retrieved from the Scopus database in accordance with the PRISMA 2020 flow protocol. From an initial yield of 3842 records, 1176 studies published between 1 January 2020 and 20 November 2025 were included for analysis. The first set of results indicated that publication trends in RAI and SAI for CE models within smart-city frameworks were found to be statistically significant ((Formula presented.) = 0.94, p < 0.001). The second set of results revealed that circular manufacturing, waste management automation, predictive energy optimisation, urban data platforms, and smart mobility systems were increasingly embedded within RAI and SAI applications for CE models in smart-city contexts. The third set of results demonstrated that RAI and SAI within CE models were found to yield a significant effect (M = −0.61, SD = 0.09, t(9) = 7.42, p < 0.001) and to correlate positively with policy alignment (r = 0.34, p = 0.042) in smart-city contexts. It was therefore concluded that policy-responsive AI governance is required to ensure inclusive and sustainable smart-city transformation within frameworks of RAI.