  Mixed-initiative systems allow users to interactively provide feedback to
potentially improve system performance. Human feedback can correct model errors
and update model parameters to dynamically adapt to changing data.
Additionally, many users desire the ability to have a greater level of control
and fix perceived flaws in systems they rely on. However, how the ability to
provide feedback to autonomous systems influences user trust is a largely
unexplored area of research. Our research investigates how the act of providing
feedback can affect user understanding of an intelligent system and its
accuracy. We present a controlled experiment using a simulated object detection
system with image data to study the effects of interactive feedback collection
on user impressions. The results show that providing human-in-the-loop feedback
lowered both participants' trust in the system and their perception of system
accuracy, regardless of whether the system accuracy improved in response to
their feedback. These results highlight the importance of considering the
effects of allowing end-user feedback on user trust when designing intelligent
systems.
