  Designing seamless, frictionless user experiences has long been a dominant
trend in both applied behavioral science and artificial intelligence (AI), in
which the goal of making desirable actions easy and efficient informs efforts
to minimize friction in user experiences. However, in some settings, friction
can be genuinely beneficial, such as the insertion of deliberate delays to
increase reflection, preventing individuals from resorting to automatic or
biased behaviors, and enhancing opportunities for unexpected discoveries. More
recently, the popularization and availability of AI on a widespread scale has
only increased the need to examine how friction can help or hinder users of AI;
it also suggests a need to consider how positive friction can benefit AI
practitioners, both during development processes (e.g., working with diverse
teams) and to inform how AI is designed into offerings. This paper first
proposes a "positive friction" model that can help characterize how friction is
currently beneficial in user and developer experiences with AI, diagnose the
potential need for friction where it may not yet exist in these contexts, and
inform how positive friction can be used to generate solutions, especially as
advances in AI continue to be progress and new opportunities emerge. It then
explores this model in the context of AI users and developers by proposing the
value of taking a hybrid "AI+human" lens, and concludes by suggesting questions
for further exploration.
