What values do technologists cite when evaluating technologies intended for application in “real world” social contexts like domestic settings? This paper examines the negotiation of values among the organizers who design and run the world’s largest domestic service robotics competition, RoboCup@Home. We perform an interpretive analysis of collaborative discussions from the organization’s open GitHub repositories and meeting notes from the years 2015-2023, informed by participatory digital ethnography and on-site fieldwork at the annual competition. Our analysis reveals the pervasive invocation of values, such as “realistic” and antivalues, such as “unfair”, in these discussions. We find that the perception of infeasibility strongly discouraged adoption of proposals that organizers otherwise agreed would have made RoboCup@Home, and domestic service robotics, more realistic, natural, and fair. We suggest future work pay attention to polysemy in negotiation of values, trace the shared values yet unrealized in negotiated settings, and consider infrastructural interventions that expand the feasibility of realizing values. The “real worlds” and values negotiated within spaces of competitive evaluation, be they imagined, realized, or unrealized, nonetheless shape the sociotechnical realities we and our technologies come to create and inhabit.

ABSTRACT This study examines how socially compliant robot behaviours, operationalized as body language and verbal cues, affect human perceptions of social intelligence and compliance with a quadruped robot during incidental human–robot encounters. Extending prior work that primarily focused on direct human–robot interactions, this study addresses the understudied context of incidental encounters, which are brief, unplanned interactions between bystanders and autonomous robots in public environments. In an online video‐based study with 385 participants using a within‐subject design, we found that both verbal and body language behaviours significantly improved the robot's perceived social intelligence (PSI), which in turn positively correlated with human compliance. Verbal communication alone increased compliance likelihood more than body language, and combining both yielded the highest PSI ratings and compliance scores. To validate these findings beyond controlled video scenarios, a follow‐up real‐world study with 26 participants replicated the results: 11 out of 13 of participants complied in the Body Language + Verbal condition versus only 1 in the baseline condition. Free‐text responses revealed the importance of clearly stated intentions, politeness, and concerns about robot legitimacy and safety. Together, these findings highlight the critical role of perceived social intelligence in fostering human assistance for robots during incidental encounters and offer design strategies to support robot deployment in public environments.

Abstract Information systems serve as the “source of truth” for much of social reality, from credit scores to eligibility for boarding an airplane to the current time. In contexts of practical consensus, the system makes it so. I label this phenomenon system‐dependent truth. This paper advances a theory of performative truthmaking, wherein the agencies of giving as and taking as produce facts and truth as relations. I introduce the term systems of record to denote information systems that contain facts rather than propositions. I develop a suitable performative approach to the phenomenon of system‐dependent truth by synthesizing John Searle's social ontology, an account of truth, facts, and social reality, with Karen Barad's agential realism, an onto‐epistemology of human and nonhuman agency. Using several specific examples drawn from travel and migration contexts, including the US government's No Fly List, I show that system‐dependent truth arises when an agent takes information from a system as fact during the performance of sociotechnical truth. I argue that the agencies of truthmaking and factmaking are a distinct form of power, that the coordination of these agencies constitutes institutional rationalities of potentially global scale, and that systems of record are therefore critical sites for justice‐oriented information studies.

HRI research using autonomous robots in real-world settings can produce results with the highest ecological validity of any study modality, but many difficulties limit such studies’ feasibility and effectiveness. We propose Vid2Real HRI, a research framework to maximize real-world insights offered by video-based studies. The Vid2Real HRI framework was used to design an online study using first-person videos of robots as real-world encounter surrogates. The online study (n=385) distinguished the within-subjects effects of four robot behavioral conditions on perceived social intelligence and human willingness to help the robot enter an exterior door. A real-world, between-subjects replication (n=26) using two conditions confirmed the validity of the online study’s findings and the sufficiency of the participant recruitment target (n=22) based on a power analysis of online study results. The Vid2Real HRI framework offers HRI researchers a principled way to take advantage of the efficiency of video-based study modalities while generating directly transferable knowledge of real-world HRI. Code and data from the study are provided at vid2real.github.io/vid2realHRI.

The Longitudinal Social Impacts of HRI over Long-Term Deployments Workshop seeks to bring together researchers working on all aspects of thoroughly understanding such deployments. This includes researchers working in contributing areas, such as longitudinal studies of human-robot interaction, long-term autonomy, and real-world reployments. This workshop seeks to grow the study of how real-world, deployed robot systems impact the people who interact with them and the social structure of the places that they inhabit. Historically, research in this area has been high-impact. As the world sees robots begin to inhabit places designed for people - delivery robots on city streets, and robots with jobs in airports, shopping malls, and in the home - we expect the importance of understanding these impacts to grow.