Being Watched: Embedding Ethics in Public Cameras
‘Smart cities’ infrastructures have won fans among many officials, city planners, and infrastructure manufacturers. A collection of hardware devices such as cameras, sensors, and controllers linked to software-driven intelligence—often with an Internet, grid or network element and deployed at scale—these systems promise cities, regions and even nations better services, improved management capabilities and sometimes lower costs. Increasingly, the voluminous and diverse data they produce will be analyzed by AI or machine-learning routines, raising questions regarding how those machine-based procedures operate and the ethical systems undergirding their analyses.
As more of such city-based infrastructures move toward automated and algorithmically-optimized capabilities, the human and broader machine and platform environments present legal, ethical and accountability issues. These affect the strata of planners and managers in cities, the technologists producing (and selling) the software and hardware systems and companies, as well as citizens living and working with these systems. Our project will seek to build technical, legal and social approaches to maximize the trusted use of public camera-generated video data.
- How do citizens and city management conceptualize privacy in the smart city context?
- What data management practices are appropriate for ethical algorithmically-derived data in the smart city context?
- How can AI for camera systems be designed to embody important values and apply to use cases?
- How can we identify and assess best practices for cultivating citizenry awareness of and engagement with smart cities technologies?
Scope of Work
- Conduct focus groups and surveys to assess local attitudes toward city-deployed cameras, particularly traffic cameras
- Investigate the concrete requirements for public camera data currently used across different institutional units to define relevant data management practices and issues
- Build and test differential access models that allow camera-generated visual data to be used productively
- Design and test public literacy trainings, and initiate policy and public engagement efforts