Applying artificial intelligence sensibly in smart cities to improve sustainable development outcomes: insights from a comparative research across cities in different regions
More than 50% of the world’s population currently live in cities and the proportion is likely to grow to 70% by 2050 (World Bank Group, 2023). Thus, cities arguably play a pivotal role in efforts to achieve the Sustainable Development Goals (SDGs). Specifically, smart cities, which integrate information and communications technology (ICT), energy, and transport to improve cities’ resilience and efficiency, could possibly drive much progress for the SDGs. The advent of artificial intelligence (AI) could also augment smart cities’ potential to contribute to the SDGs. However, AI could be a double-edged sword that brings both pros and cons on the economic, environmental, and social fronts. Moreover, people’s attitude and practices in using AI might differ due to various factors. This paper hypothesizes that sociocultural differences across regions could influence how their smart cities adopt AI to support sustainable development. To validate this hypothesis, this research employed a survey which yielded 401 responses. Four major population subgroups emerged from the responses, reflecting views from Africa, China, Singapore, and the Europe and North America (ENA) region. This paper presents the significant findings from the survey that could help in advancing the sustainable development agenda. For instance, people in the ENA region seem comparatively less comfortable in using AI, so relevant local authorities in the region might need to step up efforts to alleviate concerns. Through sharing such insights, this paper brings significant value to urban planners and policymakers in making decisions about sensible AI applications in smart cities for sustainable development.
Publication Details
- Journal
- AgEcon Search (University of Minnesota, USA)
- Published
- 2025-01-01
- DOI
- https://doi.org/10.22004/ag.econ.355396
- Primary Topic
- Smart Cities and Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00