Katie Seaborn 교수

Social robots, conversational agents, voice assistants, and other embodied AI are increasingly a feature of everyday life. What connects these various types of intelligent agents is their ability to interact with people through voice. Voice is becoming an essential modality of embodiment, communication, and interaction between computer-based agents and end-users. This survey presents a meta-synthesis on agent voice in the design and experience of agents from a human-centered perspective: voice-b

Gender/ing guides how we view ourselves, the world around us, and each other-including non-humans. Critical voices have raised the alarm about stereotyped gendering in the design of socially embodied artificial agents like voice assistants, conversational agents, and robots. Yet, little is known about how this plays out in research and to what extent. As a first step, we critically reviewed the case of Pepper, a gender-ambiguous humanoid robot. We conducted a systematic review (n=75) involving m

Computer voice is experiencing a renaissance through the growing popularity of voice-based interfaces, agents, and environments. Yet, how to measure the user experience (UX) of voice-based systems remains an open and urgent question, especially given that their form factors and interaction styles tend to be non-visual, intangible, and often considered disembodied or “body-less.” As a first step, we surveyed the ACM and IEEE literatures to determine which quantitative measures and measurements ha

Critical voices within and beyond the scientific community have pointed to a grave matter of concern regarding who is included in research and who is not. Subsequent investigations have revealed an extensive form of sampling bias across a broad range of disciplines that conduct human subjects research called "WEIRD": Western, Educated, Industrial, Rich, and Democratic. Recent work has indicated that this pattern exists within human-computer interaction (HCI) research, as well. How then does huma

The online version contains supplementary material available at 10.1007/s12369-022-00925-7.

An extended design and evaluation framework of eudaimonia (personal growth, expressiveness) and hedonia (pleasure, comfort) was applied to a cooperative game for older adults who rely on power mobility. The purpose was to address two psychosocial well-being needs (perceptions of performance mastery and empathy enhancement) through a game with an interaction format that augments the experience of powered chair use: mixed reality with power mobility-based interaction and movement. Two versions of

The advent of affordable and powerful mobile technology has allowed for explorations in mixed reality that merges virtual and physical space. However, the social and entertainment value and efficacy of mixed reality platforms for adult powered chair users has not been widely explored. In this article, we introduce the Mobility Games project, which aims to produce a series of inclusive entertainment technologies and services for people who use powered chairs. We describe our first offering: an ac

CRD42021235288.

Psychological resilience has emerged as a key factor in mental health during the global COVID-19 pandemic. However, no work to date has synthesised findings across review work or assessed the reliability of findings based on review work quality, so as to inform public health policy. We thus conducted a meta-review on all types of review work from the start of the pandemic (January 2020) until the last search date (June 2021). Of an initial 281 papers, 30 were included for review characteristic r

The Japanese notion of “kawaii” or expressions of cuteness, vulnerability, and/or charm is a global cultural export. Work has explored kawaii-ness as a design feature and factor of user experience in the visual appearance, nonverbal behaviour, and sound of robots and virtual characters. In this initial work, we consider whether voices can be kawaii by exploring the vocal qualities of voice assistant speech, i.e., kawaii vocalics. Drawing from an age-inclusive model of kawaii, we ran a user perce

Critical scholarship has elevated the problem of gender bias in data sets used to train virtual assistants (VAs). Most work has focused on explicit biases in language, especially against women, girls, femme-identifying people, and genderqueer folk; implicit associations through word embeddings; and limited models of gender and masculinities, especially toxic masculinities, conflation of sex and gender, and a sex/gender binary framing of the masculine as diametric to the feminine. Yet, we must al

Competency models have been widely employed within education, training and development contexts. In particular, medical education programs have become a platform of exploration around innovations in competency-based assessment. Approaches that employ dynamic, flexible models in a social context are now being sought. In this paper, we present the design of a deliberately gamifiable competency model system that encourages pre-professional development through collaborative peer appraisals. We propo

Gender is a social framework through which people organize themselves-and non-human subjects, including robots. Research stretching back decades has found evidence that people tend to gender artificial agents unwittingly, even with the slightest cue of humanlike features in voice, body, role, and other social features. This has led to the notion of gender neutrality in robots: ways in which we can avoid gendering robots in line with human models, as well explorations of extra-human genders. This

Voice assistants (VAs) are becoming a feature of our everyday life. Yet, the user experience (UX) is often limited, leading to underuse, disengagement, and abandonment. Co-designing interactions for VAs with potential end-users can be useful. Crowdsourcing this process online and anonymously may add value. However, most work has been done in the English-speaking West on dialogue data sets. We must be sensitive to cultural differences in language, social interactions, and attitudes towards techno