Public institutions are increasingly turning to technical fixes to solve structural problems, and consequently, sidelining questions of inequality, accountability, and justice. Within public benefits programs, federal and state governments are introducing algorithmic technologies to police vulnerable communities under the guise of rooting out fraud, waste and abuse, rather than passing and implementing policy in consultation with those communities and in response to their needs. These technologies introduce automated, algorithmic processes that lack transparency and mechanisms for appeal, putting the onus on vulnerable individuals with scarce resources to not only push back, but to advocate for services and benefits they have a right to expect from the state.

As the largest single funder of long-term services and supports, the United States government—through programs like Medicaid—plays a significant role in providing necessary care and support services for people with disabilities and older adults. As a result, greater public sector use of technology is impacting both the care workforce and the families they support. Just as the use of automated systems in areas like education, criminal justice, and welfare have already led to deeply inequitable outcomes, the adoption of these technologies in Medicaid home- and community-based programs may perpetuate extractive and punitive approaches towards managing, quantifying, and distributing care across American society.

The report, Electronic Visit Verification: the weight of surveillance and the fracturing of care, explores how the public sector adoption of EVV technology has ignored the needs of marginalised communities and has led to tangible harms. The mandatory rollout of EVV technology has eroded critical supports for people with disabilities and older adults and offloads significant, unacknowledged burdens onto workers and their clients within Medicaid home- and community-based services.

The implementation of EVV systems highlights the risks of uncritical adoption of data-centric technologies in the provision of public services. This policy brief describes the harms that EVV and—technologies like it—create, and the stakes of continued inaction by federal and state governments. It underscores the importance of the government’s commitment to community- and justice-informed uses of algorithmic systems.