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We examined whether a robot that proactively offers moral advice promoting the norm of honesty can discourage people from cheating. Participants were presented with an opportunity to cheat in a die-rolling game. Prior to playing the game, participants received from either a NAO robot or a human, a piece of moral advice grounded in either deontological, virtue, or Confucian role ethics, or did not receive any advice. We found that moral advice grounded in Confucian role ethics could reduce cheating when the advice was delivered by a human. No advice was effective when a robot delivered moral advice. These findings highlight challenges in building robots that can possibly guide people to follow moral norms. 

The field of human-robot interaction (HRI) research is multidisciplinary and requires researchers to understand diverse fields including computer science, engineering, informatics, philosophy, psychology, and more disciplines. However, it is hard to be an expert in everything. To help HRI researchers develop methodological skills, especially in areas that are relatively new to them, we conducted a virtual workshop, Workshop Your Study Design (WYSD), at the 2021 International Conference on HRI. In this workshop, we grouped participants with mentors, who are experts in areas like real-world studies, empirical lab studies, questionnaire design, interview, participatory design, and statistics. During and after the workshop, participants discussed their proposed study methods, obtained feedback, and improved their work accordingly. In this paper, we present 1) Workshop attendees’ feedback about the workshop and 2) Lessons that the participants learned during their discussions with mentors. Participants’ responses about the workshop were positive, and future scholars who wish to run such a workshop can consider implementing their suggestions. The main contribution of this paper is the lessons learned section, where the workshop participants contributed to forming this section based on what participants discovered during the workshop. We organize lessons learned into themes of 1) Improving study design for HRI, 2) How to work with participants - especially children -, 3) Making the most of the study and robot’s limitations, and 4) How to collaborate well across fields as they were the areas of the papers submitted to the workshop. These themes include practical tips and guidelines to assist researchers to learn about fields of HRI research with which they have limited experience. We include specific examples, and researchers can adapt the tips and guidelines to their own areas to avoid some common mistakes and pitfalls in their research. 

It is critical for designers of language-capable robots to enable some degree of moral competence in those robots. This is especially critical at this point in history due to the current research climate, in which much natural language generation research focuses on language modeling techniques whose general approach may be categorized as “fabrication by imitation” (the titular mechanical “bull”), which is especially unsuitable in robotic contexts. Furthermore, it is critical for robot designers seeking to enable moral competence to consider previously under-explored moral frameworks that place greater emphasis than traditional Western frameworks on care, equality, and social justice, as the current sociopolitical climate has seen a rise of movements such as libertarian capitalism that have undermined those societal goals. In this paper we examine one alternate framework for the design of morally competent robots, Confucian ethics, and explore how designers may use this framework to enable morally sensitive human-robot communication through three distinct perspectives: (1) How should a robot reason? (2) What should a robot say? and (3) How should a robot act? 

This paper introduces a new testbed called Cooking with Humans and Autonomy in Overcooked!2 for studying Performance and Teaming (CHAOPT). A validation study was conducted to examine the viability of Overcooked!2 as a research platform to explore teamwork and communication in human-autonomy teams. Unique measures derived from this platform such as productive chef actions (PCA), team expertise score and chef role contribution (CRC) distinguished performance between levels and players. Our findings demonstrate that we can derive meaningful team process, performance and communication measures and that the interactions within Overcooked!2 meet the requirements of psychological fidelity of teaming research.