人在回路中的用户反馈会影响感知准确性和信任，但任务主观性很重要
Human-in-the-Loop User Feedback Affects Perceived Accuracy and Trust, but Task Subjectivity Matters
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中文总结 AI 辅助
研究人在回路的用户反馈对智能系统的影响，通过三项对照实验，发现在客观反馈情境下提供反馈会降低用户对系统的信任和准确性感知，主观反馈则无此负面偏差，强调设计智能系统时考虑用户反馈对信任影响的重要性。
中文摘要 AI 辅助
虽然机器学习可以生成比人类手动生成更复杂的模型，但纳入人类输入通常可以提高性能。在许多情况下，经常使用系统的最终用户会自然了解其缺陷并希望能改变系统行为。征求最终用户反馈可随时间显著改进模型，但也会影响一些未被充分理解的人为因素。为此进行了三项对照实验，研究交互式反馈收集在客观和主观反馈领域对用户印象的影响。结果表明，在有客观正确答案的情况下，提供人在回路反馈会降低参与者对系统的信任和对系统准确性的感知，而在主观反馈情况下则未观察到这种负面偏差。此外，在客观情境中参与者对系统的不信任随时间增加，而在主观情境中则不然。这些结果凸显了在设计智能系统时考虑不同类型最终用户反馈对用户信任影响的重要性。
英文摘要
While ML can produce complex models beyond those that a human could produce manually, incorporating human input can often improve performance beyond purely data-driven models. While this feedback could come from system designers or domain experts, in many cases, the end users who regularly use the system will naturally develop an understanding of its flaws and desire the ability to change the system's behavior based on their knowledge. While soliciting feedback from end users can result in significant model improvement over time, introducing these feedback techniques can also affect several human factors-such as trust or perception of system accuracy-that are not yet fully understood and have different effects reported in the existing literature. Therefore, we sought to build on the existing research to further explore how the act of providing feedback can affect user understanding of an intelligent system and its accuracy in different contexts. We present three controlled experiments that study the effects of interactive feedback collections on user impressions in domains with objective and subjective feedback. The results show that in a context where there is an objectively correct answer, providing HITL 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. However, when the feedback being provided involved subjective opinion, no such negative bias was observed. Furthermore, in the objective context, participants distrusted the system over time, whereas participants in the subjective context mistrusted the system over time. These results highlight the importance of considering the effects of allowing different types of end-user feedback on user trust when designing intelligent systems.
发表机构
- University of Florida（佛罗里达大学）
- Northeastern University（东北大学）
机构由 AI 辅助整理，请以论文原文为准。
