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As artificial intelligence (AI) systems have already proven useful in human lives generally, there is an opportunity for specialized human-AI interaction (HAI) systems to support and provide care for older adults with mild cognitive impairment (MCI). However, the integration of this technology in this population must be thoughtfully designed to accommodate specific needs and limitations. This includes careful measurement of both humans and systems. We developed an evolving dataset categorizing relevant measurement tools into five groups: cognitive ability, demographics & personality, activity level, state of mind, and perceptions of the AI system. Each instance of the tool being used in the literature cataloged in the dataset is qualified in terms of how likely we would recommend using it in the domain of HAI for older adults with MCI based on contextual factors and internal reliability measures. This dataset will serve as a valuable resource for future research, aiding in the identification of promising areas and trends in AI systems for older adults with MCI as well as providing essential tools for future studies. [ABSTRACT FROM AUTHOR]

Research on robotic ostracism is still scarce and has only explored its effects on adult populations. Although the results revealed important carryover effects of robotic exclusion, there is no evidence yet that those results occur in child-robot interactions. This paper provides the first exploration of robotic ostracism with children. We conducted a study using the Robotic Cyberball Paradigm in a third-person perspective with a sample of 52 children aged between five to ten years old. The experimental study had two conditions: Exclusion and Inclusion. In the Exclusion condition, children observed a peer being excluded by two robots; while in the Inclusion condition, the observed peer interacted equally with the robots. Notably, even 5-year-old children could discern when robots excluded another child. Children who observed exclusion reported lower levels of belonging and control, and exhibited higher prosocial behaviour than those witnessing inclusion. However, no differences were found in children's meaningful existence, self-esteem, and physical proximity across conditions. Our user study provides important methodological considerations for applying the Robotic Cyberball Paradigm with children. The results extend previous literature on both robotic ostracism with adults and interpersonal ostracism with children. We finish discussing the broader implications of children observing ostracism in human-robot interactions. [ABSTRACT FROM AUTHOR]

This article aims to explore the potential impact of artificial emotional intelligence (AEI) on the ethical standing of social robots. By examining how AEI interacts with and potentially reshapes the two dominant perspectives on robots' moral status, namely the property-oriented approach and the social-relational approach, we aim to offer fresh insights into this pressing dilemma. Our analysis reveals that although the incorporation of AEI does not conclusively confer moral status to current social robots, it might challenge the boundaries that separate robots from other entities customarily considered to have more status, thereby increasing the complexity of the debate. [ABSTRACT FROM AUTHOR]

Due to challenges in communication and cognition (e.g., attention, memory, organization, etc.), individuals with cognitive-communication needs (CCNs) experience difficulties performing activities of daily living, or ADLs (e.g., self-care, meal preparation, managing different routines and appointments). Voice-assisted technology (VAT) has been shown to support these individuals for ADLs; however, there are limited clinician-guided VAT training programs available for individuals with CCNs to use VAT for ADLs. This study aims to design and implement a 6-week virtual VAT training program focused on using Amazon Alexa voice commands to improve independence in ADL tasks for three adults with CCNs. This research study describes the collaborative design process of the VAT Training program by a clinical team and the 6-week delivery of the training program. By analyzing training session videos and participant interviews, the benefits and challenges from the training, as well as future plans to improve the implementation of VAT for telehealth are discussed. [ABSTRACT FROM AUTHOR]

Traumatic brain injury (TBI) can cause cognitive, communication, and psychological challenges that profoundly limit independence in everyday life. Conversational Agents (CAs) can provide individuals with TBI with cognitive and communication support, although little is known about how they make use of CAs to address injury-related needs. In this study, we gave nine adults with TBI an at-home CA for four weeks to investigate use patterns, challenges, and design requirements, focusing particularly on injury-related use. The findings revealed significant gaps between the current capabilities of CAs and accessibility challenges faced by TBI users. We also identified 14 TBI-related activities that participants engaged in with CAs. We categorized those activities into four groups: mental health, cognitive activities, healthcare and rehabilitation, and routine activities. Design implications focus on accessibility improvements and functional designs of CAs that can better support the day-to-day needs of people with TBI. [ABSTRACT FROM AUTHOR]

Many robot-delivered health interventions aim to support people longitudinally at home to complement or replace in-clinic treatments. However, there is little guidance on how robots can support collaborative goal setting (CGS). CGS is the process in which a person works with a clinician to set and modify their goals for care; it can improve treatment adherence and efficacy. However, for home-deployed robots, clinicians will have limited availability to help set and modify goals over time, which necessitates that robots support CGS on their own. In this work, we explore how robots can facilitate CGS in the context of our robot CARMEN (Cognitively Assistive Robot for Motivation and Neurorehabilitation), which delivers neurorehabilitation to people with mild cognitive impairment (PwMCI). We co-designed robot behaviors for supporting CGS with clinical neuropsychologists and PwMCI, and prototyped them on CARMEN. We present feedback on how PwMCI envision these behaviors supporting goal progress and motivation during an intervention. We report insights on how to support this process with home-deployed robots and propose a framework to support HRI researchers interested in exploring this both in the context of cognitively assistive robots and beyond. This work supports designing and implementing CGS on robots, which will ultimately extend the efficacy of robot-delivered health interventions. [ABSTRACT FROM AUTHOR]

This paper describes a therapeutic full-body controlled video game for children with attention deficit / hyperactivity disorder (ADHD). The game supports a co-located gameplay with a depth-sensing camera and a large media screen. Children play the game in pairs for improved impulse and behavior control, self-monitoring, peer-communication, and emotion regulation. The gaming was implemented as a part of a neuropsychological group intervention for children with confirmed deficits in attention or diagnosed ADHD. We present a final design of the game and associated gaming routines, explain anticipated health benefits of the gaming, outline how the gaming can be used for research and therapeutic purposes, and provide directions for future research. [ABSTRACT FROM AUTHOR]

Dementia is a serious threat to social sustainability. As life expectancy increases, more people are developing dementia. At the same time, demographic change is reducing the economically active part of the population. Care of people with dementia imposes great emotional and financial strain on sufferers, their families and society at large. In response, significant research resources are being focused on dementia. One research thread is focused on using computer technology to monitor people in at-risk groups to improve rates of early diagnosis. In this paper we provide an overview of dementia monitoring research and identify a set of scientific challenges for the engineering of dementia-monitoring software, with implications for other mental health self-management systems. [ABSTRACT FROM AUTHOR]

Much research in healthcare robotics explores extending rehabilitative interventions to the home. However, for adults, little guidance exists on how to translate human-delivered, clinic-based interventions into robot-delivered, home-based ones to support longitudinal interaction. This is particularly problematic for neurorehabilitation, where adults with cognitive impairments require unique styles of interaction to avoid frustration or overstimulation. In this paper, we address this gap by exploring the design of robot-delivered neurorehabilitation interventions for people with mild cognitive impairment (PwMCI). Through a multi-year collaboration with clinical neuropsychologists and PwMCI, we developed robot prototypes which deliver cognitive training at home. We used these prototypes as design probes to understand how participants envision long-term deployment of the intervention, and how it can be contextualized to the lives of PwMCI. We report our findings and specify design patterns and considerations for translating neurorehabilitation interventions to robots. This work will serve as a basis for future endeavors to translate cognitive training and other clinical interventions onto a robot, support longitudinal engagement with home-deployed robots, and ultimately extend the accessibility of longitudinal health interventions for people with cognitive impairments. [ABSTRACT FROM AUTHOR]

Children are stakeholders of robotic technologies who deserve to have their voices heard in the design process just as much as adult stakeholders. This is especially true for robotic technologies explicitly designed for child-robot interaction, in areas like education, healthcare, and therapy. Researchers face the challenge of cultivating children's critical awareness on the design of robots and accompanying ethical concerns, as the types of exercises typically used to engage with adult stakeholders can be ineffective with children. This requires developmentally appropriate methods for understanding children's perspectives that also address the imbalanced power dynamics between children and adults-such that children feel comfortable sharing their ideas. In this work, we demonstrate that participatory design research techniques already accepted in the Human Robot Interaction (HRI) community can fulfill this purpose. Specifically, through the design and analysis of two co-design workshops with children of different ages at a school in Denver, Colorado, we demonstrate that co-design workshops can be used to effectively understand how children make sense of robotic technologies and to facilitate children's critical reflection on the ethical dilemmas surrounding their own relationships with robots. [ABSTRACT FROM AUTHOR]

Understanding how novices reason about coding at a neurological level has implications for training the next generation of software engineers. In recent years, medical imaging has been increasingly employed to investigate patterns of neural activity associated with coding activity. However, such studies have focused on advanced undergraduates and professionals. In a human study of 31 participants, we use functional near-infrared spectroscopy to measure the neural activity associated with introductory programming. In a controlled, contrast-based experiment, we relate brain activity when coding to that of reading natural language or mentally rotating objects (a spatial visualization task). Our primary result is that all three tasks--coding, prose reading, and mental rotation--are mentally distinct for novices. However, while those tasks are neurally distinct, we find more significant differences between prose and coding than between mental rotation and coding. Intriguingly, we generally find more activation in areas of the brain associated with spatial ability and task difficulty for novice coding compared to that reported in studies with more expert developers. Finally, in an exploratory analysis, we also find a neural activation pattern predictive of programming performance 11 weeks later. While preliminary, these findings both expand on previous results (e.g., relating expertise to a similarity between coding and prose reading) and also provide a new understanding of the cognitive processes underlying novice programming. [ABSTRACT FROM AUTHOR]

SIGACCESS and SIGCHI are being shaped by new members as they integrate feminist theory, critical race theory, postcolonial studies, and critical disability studies into the field. What happens when we begin to hold each other accountable to the impact our work has on marginalized users and communities? How do we develop a community of collaborative personal growth and institutional transformation? In this experience report, the authors retell the tangled events that brought them together. Through the passionate witnessing of critical analysis and critique, what might have been a contentious adversarial relationship became a potent partnership devoted to pushing the field toward a transformative future. From our story, we present reflections for the "Prefigurative Politics" of socially conscious computing. [ABSTRACT FROM AUTHOR]

We present a large-scale study of a series of seven lessons designed to help young children learn English vocabulary as a foreign language using a social robot. The experiment was designed to investigate 1) the effectiveness of a social robot teaching children new words over the course of multiple interactions (supported by a tablet), 2) the added benefit of a robot's iconic gestures on word learning and retention, and 3) the effect of learning from a robot tutor accompanied by a tablet versus learning from a tablet application alone. For reasons of transparency, the research questions, hypotheses and methods were preregistered. With a sample size of 194 children, our study was statistically well-powered. Our findings demonstrate that children are able to acquire and retain English vocabulary words taught by a robot tutor to a similar extent as when they are taught by a tablet application. In addition, we found no beneficial effect of a robot's iconic gestures on learning gains. [ABSTRACT FROM AUTHOR]

Most robots currently being sold or developed are either stylized with white material or have a metallic appearance. In this research we used the shooter bias paradigm and several questionnaires to investigate if people automatically identify robots as being racialized, such that we might say that some robots are "White" while others are "Asian", or "Black". To do so, we conducted an extended replication of the classic social psychological shooter bias paradigm using robot stimuli to explore whether effects known from human-human intergroup experiments would generalize to robots that were racialized as Black and White. Reaction-time based measures revealed that participants demonstrated 'shooter-bias' toward both Black people and robot racialized as Black. Participants were also willing to attribute a race to the robots depending on their racialization and demonstrated a high degree of inter-subject agreement when it came to these attributions. [ABSTRACT FROM AUTHOR]

Adults with Autism Spectrum Disorders (ASD) are unemployed at a high rate, in part because the constraints and expectations of traditional employment can be difficult for them. In this paper, we report on our work in introducing people with ASD to remote work on a crowdsourcing platform and a prototype tool we developed by working with participants. We conducted a six-week long user-centered design study with three participants with ASD. The early stage of the study focused on assessing the abilities of our participants to search and work on micro-tasks available on the crowdsourcing market. Based on our preliminary findings, we designed, developed, and evaluated a prototype tool to facilitate image transcription tasks that are increasingly popular on crowd labor markets. Our findings suggest that people with ASD have varying levels of ability to work on micro-tasks, but are likely to be able to work on tasks like image transcription. The tool we introduce, Assistive Task Queue (ATQ), facilitated our participants' completion of image transcription tasks by removing ambiguity in finding the next task to work on and in simplifying tasks into discrete steps. ATQ may serve as a general platform for finding and delivering appropriate tasks to workers with autism. [ABSTRACT FROM AUTHOR]

After a long history of being viewed as a children's disorder, it is now recognized that Attention-Deficit/Hyperactivity Disorder (ADHD) can affect adults as well. Individuals with ADHD often exhibit work habits significantly different from neurotypical individuals. This paper investigates the use of time management tools among adults with ADHD with the goal of determining where there may be room for improvement in current digital tools so that they may better assist our target demographic. We present findings from a survey of adults with and without ADHD. Our findings indicate dissatisfaction among ADHD adults with the tools currently available to them and highlight key areas for potential development. [ABSTRACT FROM AUTHOR]