Transparency is an important aspect of human-robot interaction (HRI), as it can improve system trust and usability leading to improved communication and performance. However, most transparency models focus only on the amount of information given to users. In this paper, we propose a bidirectional transparency model, termed a transparency-based action (TBA) model, which in addition to providing transparency information (robot-to-human), allows the robot to take actions based on transparency information received from the human (robot-of-human and human-to-robot). We implemented a three-level (High, Medium and Low) TBA model on a robotic system trainer in two pilot studies (with students as participants) to examine its impact on acceptance and HRI. Based on the pilot studies results, the Medium TBA level was not included in the main experiment, which was conducted with older adults (aged 75-85). In that experiment, two TBA levels were compared: Low (basic information including only robot-to-human transparency) and High (including additional information relating to predicted outcomes with robot-of-human and human-to-robot transparency). The results revealed a significant difference between the two TBA levels of the model in terms of perceived usefulness, ease of use, and attitude. The High TBA level resulted in improved user acceptance and was preferred by the users.

翻译：透明度是人机交互（HRI）的一个重要方面，因为它能够提升系统信任度和可用性，从而改善沟通与任务表现。然而，大多数透明度模型仅关注向用户提供的信息量。本文提出了一种双向透明度模型，称为基于透明度的动作（TBA）模型，该模型除了提供透明度信息（机器人到人）外，还允许机器人根据从人类接收到的透明度信息（机器人对人的理解以及人到机器人）采取行动。我们在两项先导研究（以学生为参与者）中，在一个机器人系统训练器上实现了三级（高、中、低）TBA模型，以检验其对接受度和人机交互的影响。基于先导研究结果，在主要实验（参与者为75-85岁的老年人）中未包含中等TBA水平。在该实验中，比较了两种TBA水平：低（仅包含机器人到人透明度的基本信息）和高（包含与预测结果相关的额外信息，涉及机器人对人的理解以及人到机器人透明度）。结果显示，模型的两个TBA水平在感知有用性、易用性和态度方面存在显著差异。高TBA水平提高了用户接受度，并更受用户青睐。