Terran Mott’s research while affiliated with Colorado School of Mines and other places

To critically analyze and adapt to the risks and benefits of social robotics, future user communities will require technology and AI literacy: the ability to use new robotic technologies, understand their strengths and limitations, and critically evaluate the implications of their use. Research shows that collaborative, creative, and informal learning experiences can support AI literacy among non-technologists. Therefore, we designed Degrees of Freedom, a multiplayer interactive storytelling game that supports technology literacy about social robots. Degrees of Freedom supports technology literacy competencies by encouraging players to explore how values are encoded in robot designs, compelling players to consider the risks and limitations of robots, and encouraging them to make connections to their own lives and values. We present both the design of Degrees of Freedom and the results of game playtesting. Our results show that the narrative, collaborative nature of the game supported players in critical thinking about the role robots can or should have in their communities.

Wizard-of-Oz (WoZ) is one of the most widely used experimental methodologies across the field of Human-Robot Interaction (HRI), making WoZ teleoperation interfaces a critical tool for HRI research. Yet current WoZ teleoperation interfaces are overwhelmingly tailored towards a narrow set of HRI interaction paradigms. In this work, we conducted a set of interviews with HRI researchers to better understand the diversity of teleoperation needs across the HRI community. Our analysis highlighted (1) human challenges, with respect to wizards' expertise, the need for quick responses, and research participants' unpredictability; (2) robot challenges, with respect to robot malfunctions, delays, and robot-driven complexity, and (3) interaction challenges, with respect to researchers' varying control requirements and the need for precise experimental control. Moreover, our results revealed unexpected parallels between the experiences of HRI researchers and real-world teleoperators, which open up fundamentally new possibilities for future work in robot control interfaces and encourage radically different perspectives on what types of interfaces are even needed to best facilitate WoZ experimentation. Leveraging these insights, we recommend that WoZ interfaces (1) be designed with extensibility and customization in mind, (2) ease interaction management by accounting for unpredictability and multi-robot interactions, and (3) consider WoZ teleoperators beyond the context of experimentation.

As robots become increasingly used in space exploration , it is important to ensure that space robots are developed with the appropriate level of autonomy. Semiautonomous robots operating in space contexts face unique challenges, as these robots often operate in situations that may be safety-critical, environments that are not fully known, and with communication delay to operators on Earth. Due to these challenges, there exist both advantages and risks to developing systems with high levels of autonomy to operate in space contexts. Therefore, we aim to investigate perspectives on the trade-offs of increased autonomy for space robotic systems and the human factors considerations that should be evaluated when designing these systems. We conducted qualitative interviews with five professionals in the space robotics industry to explore these perspectives. Our findings demonstrate that decisions regarding the level of autonomy of space robots is shaped not only by technical considerations, but also by operators' willingness to accept new technology, financial considerations, and even human operators' sense of control. Based on these results, we present design recommendations for roboticists and human factors engineers in the space robotics domain.

For social robots to succeed in human environments, they must respond in effective yet appropriate ways when humans violate social and moral norms, e.g., when humans give them unethical commands. Humans expect robots to be competent and proportional in their norm violation responses, and there are a wide range of strategies robots could use to tune the politeness of their utterances to achieve effective, yet appropriate responses. Yet it is not obvious whether all such strategies are suitable for robots to use. In this work, we assess a robot's use of human-like Face Theoretic linguistic politeness strategies. Our results show that while people expect robots to modulate the politeness of their responses, they do not expect them to strictly mimic human linguistic behaviors. Specifically, linguistic politeness strategies that use direct, formal language are perceived as more effective and more appropriate than strategies that use indirect, informal language.

Robots' use of natural language is one of the key factors that leads humans to anthropomorphize them. But it is not yet well understood what types of language most lead to such language-based anthropomorphization (or, Linguistic Anthropomorphism). In this paper, we present a brief literature survey that suggests six broad categories of linguistic factors that lead humans to anthropomor-phize robots: autonomy, adaptability, directness, politeness, propor-tionality, and humor. By contextualizing these six factors through the lens of Jackson and Williams' Theory of Social Agency for Human-Robot Interaction, we are able to show how and why these particular factors are those responsible for language-based robot anthropomorphism. CCS CONCEPTS • Computer systems organization → Robotics; • Human-centered computing → Human computer interaction (HCI); HCI theory, concepts and models. KEYWORDS linguistic anthropomorphism, social agency ACM Reference Format:

The use of robotics in space exploration and space sustainability has become increasingly more prevalent in recent years. Aerospace contexts pose unique challenges to both robotic capabilities as well as human operator control as these robots often operate in safety-critical situations, unknown environments, and with significant communication latency to Earth. There exist both advantages and potential risks to increased levels of autonomy in these contexts. Therefore, this paper aims to elucidate perspectives on the future role of human operators and the trade-offs when deciding on the level of autonomy for a system. To investigate these perspectives, we conducted qualitative interviews with five professionals in the space robotics industry. Our findings show that-in addition to straightforward technical considerations-financial concerns, op-erators' willingness to accept new technology, and even humans' emotional experiences during missions will likely play a role in the future of shared control in space robotics.

The Wizard-of-Oz (WoZ) method is a common and beneficial means of enabling researchers with control over robots in experimental settings. However, there is a lack of general robot control tools for WoZ that are publicly available and easily adaptable to various research domains and needs. In particular, existing control interfaces that may be used in WoZ experiments often do not support the control of multi-robot interactions. As such, in this work, we present the design of three prototypes for a multi-robot speech control interface that would enable the control of multi-robot dialogue interactions.

Robots' ability to act as social agents means they have the potential to engage in many aspects of humans' lives. However, it also means that people will encounter situations where they must judge a ro-bot's trustworthiness or fallibility. A key challenge to appraising a robot's cognition, moral competence, or trustworthiness is that the same social behaviors may be generated by a variety of different computational processes-including cognitive architectures or neural networks. In this brief paper, we explore people's varied assumptions about robot cognition revealed in qualitative data from a user study on robot moral communication. These qualitative data show that participants made varied assumptions about how robots think and speak-even based on viewing the same interactions. We reflect on the ramifications and potential risks of users making these assumptions inaccurately and affirm that roboticists can pursue transparent design that supports users in understanding how robots function and how they may fail.

For robots to be effective at collaborating with humans, they must be able to effectively communicate about entities in open-world tasks. Existing research on natural language generation and referring expression generation has yet to address how gesture and cognitive status impact how humans or robots decide how to refer to entities, a process known as Referring Form Selection. To address these issues we present a novel experimental testbed that leverages the Givenness Hierarchy to produce an entity's cognitive status. We also discuss challenges in developing this testbed and how we surmounted them.

Socially assistive robots play an effective role in children’s therapy and education. Robots engage children and provide interaction that is free of the potential judgment of human peers and adults. Research in socially assistive robots for children generally focuses on therapeutic and educational outcomes for those children, informed by a vision of autonomous robots. This perspective ignores therapists and educators, who operate these robots in practice. Through nine interviews with individuals who have used robots to deliver socially assistive services to neurodivergent children, we (1) define a dual-cycle model of therapy that helps capture the domain expert view of therapy, (2) identify six core themes of teleoperator needs and patterns across these themes, (3) provide high-level guidelines and detailed recommendations for designing teleoperated socially assistive robot systems, and (4) outline a vision of robot-assisted therapy informed by these guidelines and recommendations that centers teleoperators of socially assistive robots in practice.