  As Artificial Intelligence (AI) plays an ever-expanding role in
sociotechnical systems, it is important to articulate the relationships between
humans and AI. However, the scholarly communities studying human-AI
relationships -- including but not limited to social computing, machine
learning, science and technology studies, and other social sciences -- are
divided by the perspectives that define them. These perspectives vary both by
their focus on humans or AI, and in the micro/macro lenses through which they
approach subjects. These differences inhibit the integration of findings, and
thus impede science and interdisciplinarity. In this position paper, we propose
the development of a framework AI-Mediated Exchange Theory (AI-MET) to bridge
these divides. As an extension to Social Exchange Theory (SET) in the social
sciences, AI-MET views AI as influencing human-to-human relationships via a
taxonomy of mediation mechanisms. We list initial ideas of these mechanisms,
and show how AI-MET can be used to help human-AI research communities speak to
one another.
