Study level

  • PhD
  • Master of Philosophy
  • Honours
  • Vacation research experience scheme


Topic status

We're looking for students to study this topic.

Research centre


Professor Kevin Desouza
Professor of Business, Technology and Strategy
Division / Faculty
Faculty of Business & Law
Professor Tan Yigitcanlar
Division / Faculty
Faculty of Engineering


Artificial intelligence (AI) is not only becoming an integral part of urban services, but also impacting and shaping the future of cities and societies. However, the current AI practice has shown that urban innovation without responsibility generates more problems than it solves. Especially, the absence of a deep understanding of the costs, benefits, risks, and impacts of deploying government AI systems creates negative externalities and serious concerns in the society.


The project aims to:

  • generate a consolidated understanding of the most appropriate approaches for local governments to engage with AI to achieve responsible urban innovation
  • advance knowledge regarding the methods used to balance costs, benefits, risks and impacts of developing, adopting, deploying and managing local government AI systems targeting responsible urban innovation
  • consolidate urban and innovation theories by integrating technology, policy and community perspectives in a framework concerning responsible local government AI systems.


The responsible urban innovation with local government AI conceptual framework developed for the project is available from the following open access journal article:

Yigitcanlar, T., Corchado, J., Mehmood, R., Li, R., Mossberger, K., & Desouza, K. (2021). Responsible urban innovation with local government artificial intelligence (AI): a conceptual framework and research agenda. Journal of Open Innovation: Technology, Market, and Complexity, 7(1), 71,

Research activities

Research objectives

The objectives of the project include to:

  • investigate (from the perspective of responsible urban innovation) the evolution, costs and benefits of local government AI systems, as well as the resulting risks and socio-spatial impacts
  • assemble a framework for the conceptualisation and assessment of local government AI systems from the perspective of responsible urban innovation
  • identify local government AI capabilities and implementation challenges by considering responsible urban innovation principles
  • capture the public perception of AI (including explainable and trustworthy AI), and understand community knowledge, expectations, attitudes, acceptance and affordances concerning responsible urban innovation
  • determine appropriate AI adoption and implementation pathways for local governments to achieve responsible urban innovation.

Research questions

The research questions of the project include:

  • Why do some local governments experiment with and adopt AI systems when the risks are not clearly known while others refrain and examine the approach?
  • How can local governments make trade-offs between costs, risks, benefits, and impacts, and utilise AI systems in their municipal operations and services?
  • How can the costs, risks, benefits, and impacts be distributed across the local government service users and communities, and how can equity concerns be addressed?
  • How can local governments align the public’s perceptions and expectations regarding AI, and mitigate the consequential negative externalities of AI systems on the environment and society?
  • How can local governments adopt, deploy, and manage AI systems to generate responsible urban innovation in their cities?

The target AI systems of the project in the context of local governments are:

  • AI for carbon footprint reduction
  • AI for personalised services
  • AI for predictive maintenance
  • AI for resource optimisation
  • AI for virtual agents or chatbots.


The project will generate insights into the responsible local government AI systems from the lenses of ‘technology, policy and community’ to the case study cities of Brisbane, Phoenix, Salamanca Jeddah, and Hong Kong.

Skills and experience

The project would suit candidates with a study/research background in urban and regional planning, urban studies, local government studies, public policy, urban policy, human geography, sociology, information and technology management, and computer science or other related disciplines.



Contact the supervisor for more information.