# Contestable Camera Cars: A Speculative Design Exploration of Public AI That Is Open and Responsive to Dispute

arXiv: https://arxiv.org/abs/2302.04603 · HTML: https://mlsanity.com/paper/2302.04603/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 86 references that are in the map.
- First posted on arXiv 9 Feb 2023.

## Builds on (most cited first, 4 of 4)

- [Fairness and Accountability Design Needs for Algorithmic Support in High-Stakes Public Sector Decision-Making](https://mlsanity.com/paper/1802.01029/) (2018)
- [A Framework of High-Stakes Algorithmic Decision-Making for the Public Sector Developed through a Case Study of Child-Welfare](https://mlsanity.com/paper/2107.03487/) (2021)
- [Machine Learning Uncertainty as a Design Material: A Post-Phenomenological Inquiry](https://mlsanity.com/paper/2101.04035/) (2021)
- [Efficient Data Collection in Multimedia Vehicular Sensing Platforms](https://mlsanity.com/paper/1311.6013/) (2013)

## Built on by (most cited first, 9 of 9)

- [Contestable AI needs Computational Argumentation](https://mlsanity.com/paper/2405.10729/) (2024)
- [A Systematic Literature Review of Human-Centered, Ethical, and Responsible AI](https://mlsanity.com/paper/2302.05284/) (2023)
- [(Beyond) Reasonable Doubt: Challenges that Public Defenders Face in Scrutinizing AI in Court](https://mlsanity.com/paper/2403.13004/) (2024)
- [Reflexis: Supporting Reflexivity and Rigor in Collaborative Qualitative Analysis through Design for Deliberation](https://mlsanity.com/paper/2601.15445/) (2026)
- [Explainable AI Systems Must Be Contestable: Here's How to Make It Happen](https://mlsanity.com/paper/2506.01662/) (2025)
- [Scenarios in Computing Research: A Systematic Review of the Use of Scenario Methods for Exploring the Future of Computing Technologies in Society](https://mlsanity.com/paper/2506.05605/) (2025)
- [What Makes LLM Agent Simulations Useful for Policy Practice? An Iterative Design Study in Emergency Preparedness](https://mlsanity.com/paper/2509.21868/) (2025)
- [Towards Meaningful Transparency in Civic AI Systems](https://mlsanity.com/paper/2510.07889/) (2025)
- [From Stem to Stern: Contestability Along AI Value Chains](https://mlsanity.com/paper/2408.01051/) (2024)

## Abstract (arXiv)

Local governments increasingly use artificial intelligence (AI) for automated decision-making. Contestability, making systems responsive to dispute, is a way to ensure they respect human rights to autonomy and dignity. We investigate the design of public urban AI systems for contestability through the example of camera cars: human-driven vehicles equipped with image sensors. Applying a provisional framework for contestable AI, we use speculative design to create a concept video of a contestable camera car. Using this concept video, we then conduct semi-structured interviews with 17 civil servants who work with AI employed by a large northwestern European city. The resulting data is analyzed using reflexive thematic analysis to identify the main challenges facing the implementation of contestability in public AI. We describe how civic participation faces issues of representation, public AI systems should integrate with existing democratic practices, and cities must expand capacities for responsible AI development and operation.