Smarter places or deeper exclusion? AI, urban planning and disability discrimination law: a case study using Smart Places in New South Wales

Megan Taylo & Karena Viglianti-Northway

Pacific Rim Property Research Journal2025https://doi.org/10.64361/14445921.2025.212320article
ABDC C
Weight
0.50

What the paper says

Artificial Intelligence (AI) is often touted as the future of urban planning, promising better urban environments for citizens. In New South Wales (NSW), the State Government’s “Smart Places” initiative reflects this optimism in the use of AI in urban planning. Behind the rhetoric though there is a current regulatory gap on how AI can be used in a way that will not unlawfully discriminate against people with disability (PWD). Our research builds on existing critical literature in urban planning that focuses on the regulatory and socio-ethical concerns of AI in urban governance and smart city making. Drawing from both urban planning and legal perspectives, we adopt a cross-disciplinary approach to the issues clearly identified in this scholarship on the use of AI and corresponding risks of its use to PWD. We use the NSW Government’s approach to Smart Places as a case study to exemplify how currently applicable discrimination laws could be adapted to address some of the concerns set out in the scholarship surrounding inclusivity, transparency and accountability on the use of AI in urban planning. The discussion in this paper is thus specifically intended to build on previous scholarship in its calls to adopt specific measures to mitigate the risks posed by AI to PWD in urban planning, including through legal regulation of the technology.

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https://doi.org/https://doi.org/10.64361/14445921.2025.212320

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@article{megan2025,
  title        = {{Smarter places or deeper exclusion? AI, urban planning and disability discrimination law: a case study using Smart Places in New South Wales}},
  author       = {Megan Taylo & Karena Viglianti-Northway},
  journal      = {Pacific Rim Property Research Journal},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.64361/14445921.2025.212320},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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