  Optimization of human-AI teams hinges on the AI's ability to tailor its
interaction to individual human teammates. A common hypothesis in adaptive AI
research is that minor differences in people's predisposition to trust can
significantly impact their likelihood of complying with recommendations from
the AI. Predisposition to trust is often measured with self-report inventories
that are administered before interactions. We benchmark a popular measure of
this kind against behavioral predictors of compliance. We find that the
inventory is a less effective predictor of compliance than the behavioral
measures in datasets taken from three previous research projects. This suggests
a general property that individual differences in initial behavior are more
predictive than differences in self-reported trust attitudes. This result also
shows a potential for easily accessible behavioral measures to provide an AI
with more accurate models without the use of (often costly) survey instruments.
