EAGER: SAI: Community-Informed Surveillance Infrastructure for Public Safety and Equity

Strengthening American Infrastructure (SAI) is an NSF Program seeking to stimulate human-centered fundamental and potentially transformative research that strengthens America’s infrastructure. Effective infrastructure provides a strong foundation for socioeconomic vitality and broad quality of life improvement. Strong, reliable, and effective infrastructure spurs private-sector innovation, grows the economy, creates jobs, makes public-sector service provision more efficient, strengthens communities, promotes equal opportunity, protects the natural environment, enhances national security, and fuels American leadership.

To achieve these goals requires expertise from across the science and engineering disciplines. SAI focuses on how knowledge of human reasoning and decision making, governance, and social and cultural processes enables the building and maintenance of effective infrastructure that improves lives and society and builds on advances in technology and engineering.

Security cameras that collect data processed with artificial intelligence are being widely adopted as a key element of urban public safety infrastructure in the United States. This development is enabled further by a new public-private-community partnership model--a collaboration of the police department, city government, private business owners, and community officials.

The technology, meant to secure buildings and help police identify criminals, enable facial recognition and identification of people. Citizens and scholars have raised concerns about biases embedded in these surveillance technologies that can perpetuate prejudices and further disadvantage poor communities. This project is investigating how surveillance infrastructure affects community power relationships and whether such systems could lead to unintended consequences for communities experiencing marginalization.

The project is investigating how individuals and communities perceive and interact with surveillance infrastructure, and whether individuals’ and communities’ needs for public safety are fulfilled. The project's ultimate aim is to create and develop fair and equitable public safety infrastructures in the United States.

Through an ethnography and a community-based participatory approach, this project examines past and ongoing transformations of surveillance infrastructure in order to envision the future of public safety infrastructure in communities experiencing marginalization. The proposed research is identifying both perceptions of safety and any tensions around the public-private-community partnership in data-driven surveillance and public safety infrastructure.

The research will uncover the social, technical, and political impact resulting from the public-private partnership in developing and implementing public safety infrastructure. It is investigating the voices, history, and experiences of members of the public and those experiencing marginalization. It will propose what equitable public safety infrastructure might look like in the future and inform the design and development process of future public safety infrastructure.

Contributions include empirical and theoretical insights to surveillance studies and critical infrastructure studies. This investigation will also advance the fields of social computing concerning fairness, justice, and equity of socio-technical infrastructure and systems.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.