  Deployed AI systems often do not work. They can be constructed haphazardly,
deployed indiscriminately, and promoted deceptively. However, despite this
reality, scholars, the press, and policymakers pay too little attention to
functionality. This leads to technical and policy solutions focused on
"ethical" or value-aligned deployments, often skipping over the prior question
of whether a given system functions, or provides any benefits at all. To
describe the harms of various types of functionality failures, we analyze a set
of case studies to create a taxonomy of known AI functionality issues. We then
point to policy and organizational responses that are often overlooked and
become more readily available once functionality is drawn into focus. We argue
that functionality is a meaningful AI policy challenge, operating as a
necessary first step towards protecting affected communities from algorithmic
harm.
