  Many AI systems are deployed even when they do not work. Some AI will simply
never be able to perform the task it claims to perform. We call such systems
Impossible AI. This paper seeks to provide an integrated introduction to
Impossible AI in the United States and guide advocates, both technical and
policy, to push forward regulation of Impossible AI in the U.S. The paper
tracks three examples of Impossible AI through their development, deployment,
criticism, and government regulation (or lack thereof). We combine this with an
analysis of the fundamental barriers in the way of current calls for Impossible
AI regulation and then offer areas and directions in which to focus advocacy.
In particular, we advance a functionality-first approach that centers the
fundamental impossibility of these systems and caution against criti-hype. This
work is part of a broader shift in the community to focus on validity
challenges to AI, the decision not to deploy technical systems, and connecting
technical work with advocacy.
