Das, P., Woods, O., & Kong, L. (2025). Navigating AI–nature frictions: Autonomous vehicle testing and nature-based constraints. Big Data & Society, 12(4). https://doi.org/10.1177/20539517251406123 (Original work published 2025)
AI technologies are increasingly embedded in urban environments, with expanding applications across transportation, healthcare, disaster management, and public safety. Often promoted by tech firms and policymakers as a transformative tool for more efficient urban management, AI is often imagined as operating smoothly across urban spaces. In practice, however, urban environments are inherently erratic, shaped by complex and unpredictable social, political, cultural, and ecological interactions. These interactions and conditions are not always compatible with AI systems. Rather than viewing such challenges as temporary obstacles, our work foregrounds the tensions and frictions that fundamentally shape how AI is integrated into urban life.
In our recent paper, we focus on one specific dimension of AI–urban friction: the unpredictability of nature-based factors such as weather patterns and vegetation growth. We explore this through the case of autonomous vehicle (AV) testing in Singapore. The study forms part of a larger research project on smart city knowledge transfer in Southeast Asia, spanning Singapore, Thailand, Indonesia, and Vietnam. As a leader in digital transformation, Singapore positions itself as a testbed for advanced technologies such as AI and digital twins. During our fieldwork, AV testing emerged as a key site where frictions between AI systems and urban nature became especially visible in Singapore.
To make sense of these dynamics, we introduce the concept of frictional urbanisms in our paper. This framework captures how the smooth operational demands of AI comes into conflict with the rough and unpredictable conditions of urban environments. Our findings show that such frictions are not exceptional circumstances, but everyday conditions that shape how AI systems are tested, adapted, and governed.
The paper also lays the foundation for our next research project, “Autonomizing environmental governance in Asian cities: AI, climate change and frictional urbanisms,” funded by the Ministry of Education, Singapore. Beginning in January 2026, the project will examine how AI is reshaping urban environmental governance across South and Southeast Asia, with a focus on the emerging challenges at the intersection of two rapidly evolving fields: AI and urban climate change governance.
