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.

通过一个模拟物体检测系统的实验，我们研究了交互反馈对用户对智能系统及其准确性理解的影响，结果表明提供循环反馈降低了参与者对系统的信任和其对系统准确性的感知，这凸显了在设计智能系统时考虑用户反馈对用户信任的影响的重要性。