1 citations · 1 across the 6 of their papers we have counts for
6 papers
Do Vision-Language Models See Urban Scenes as People Do? An Urban Perception Benchmark
Rashid Mushkani
Understanding how people read city scenes can inform design and planning. We introduce a small benchmark for testing vision-language models (VLMs) on urban perception using 100 Mon…
Right-to-Override for Critical Urban Control Systems: A Deliberative Audit Method for Buildings, Power, and Transport
Rashid Mushkani
Automation now steers building HVAC, distribution grids, and traffic signals, yet residents rarely have authority to pause or redirect these systems when they harm inclusivity, saf…
Prompt Commons: Collective Prompting as Governance for Urban AI
Rashid Mushkani
Large Language Models (LLMs) are entering urban governance, yet their outputs are highly sensitive to prompts that carry value judgments. We propose Prompt Commons - a versioned, c…
Urban AI Governance Must Embed Legal Reasonableness for Democratic and Sustainable Cities
Rashid Mushkani
This position paper argues that embedding the legal "reasonable person" standard in municipal AI systems is essential for democratic and sustainable urban governance. As cities inc…
Intersectoral Knowledge in AI and Urban Studies: A Framework for Transdisciplinary Research
Rashid Mushkani
Transdisciplinary approaches are increasingly essential for addressing grand societal challenges, particularly in complex domains such as Artificial Intelligence (AI), urban planni…
AI-EDI-SPACE: A Co-designed Dataset for Evaluating the Quality of Public Spaces
Shreeyash Gowaikar, Hugo Berard, Rashid Mushkani +3
Advancements in AI heavily rely on large-scale datasets meticulously curated and annotated for training. However, concerns persist regarding the transparency and context of data co…