Transformative robot sound can improve perceptions of robots, but its implementation will likely require more hardware and cost. Does the addition of transformative sound yield an increase in value to offset this cost? Using the van Westendorp Price Sensitivity Meter, a questionnaire from marketing research, n = 97 participants measured acceptable price points for a robot with (and without) transformative sound. Results showed similar perceptual improvements as past studies, as well as a significant increase in perceived value, when transformative sound was included. These increases in social and value perceptions of robots confirm the utility of adding transformative sound to robots. This work benefits the broader human-robot interaction research community by sharing more ways to understand and validate the incorporation of transformative robot sound and other robot features.

All robots create consequential sound—sound produced as a result of the robot’s mechanisms—yet little work has explored how sound impacts human-robot interaction. Recent work shows that the sound of different robot mechanisms affects perceived competence, trust, human-likeness, and discomfort. However, the physical sound characteristics responsible for these perceptions have not been clearly identified. In this paper, we aim to explore key characteristics of robot sound that might influence perceptions. A pilot study from our past work showed that quieter and higher-pitched robots may be perceived as more competent and less discomforting. To better understand how variance in these attributes affects perception, we performed audio manipulations on two sets of industrial robot arm videos within a series of four new studies presented in this paper. Results confirmed that quieter robots were perceived as less discomforting. In addition, higher-pitched robots were perceived as more energetic, happy, warm, and competent. Despite the robot’s industrial purpose and appearance, participants seemed to prefer more "cute" (or "kawaii") sound profiles, which could have implications for the design of more acceptable and fulfilling sound profiles for human-robot interactions with practical collaborative robots.

Cognitive biases are hard-wired behaviors that influence developer actions and can set them on an incorrect course of action, necessitating backtracking. While researchers have found that cognitive biases occur in development tasks in controlled lab studies, we still don't know how these biases affect developers' everyday behavior. Without such an understanding, development tools and practices remain inadequate. To close this gap, we conducted a 2-part field study to examine the extent to which cognitive biases occur, the consequences of these biases on developer behavior, and the practices and tools that developers use to deal with these biases. About 70% of observed actions that were reversed were associated with at least one cognitive bias. Further, even though developers recognized that biases frequently occur, they routinely are forced to deal with such issues with ad hoc processes and sub-optimal tool support. As one participant (IP12) lamented: There is no salvation!