Religion and spirituality (R/S) shape billions of lives, yet they remain marginal in Human–Computer Interaction (HCI) research. Prior literature reviews mapped fragments of this space but missed key contributions and the lived realities of its researchers. We extend this picture through a review of 206 ACM and IEEE publications and a survey of R/S scholars in HCI (n = 19). Our analysis shows a field in transition: Research on R/S is growing slightly in volume and diversity, with design-oriented work emerging as the dominant form of engagement. Yet the ACM and IEEE corpora remain largely separate, reflecting distinct epistemic traditions. Researchers report persistent challenges, including marginalization, exposing a deeper tension in HCI: While HCI claims to center the full range of human experience, R/S experience is still treated with suspicion. Our findings call for a reconsideration: If HCI is serious about human experience, it must take R/S experiences seriously as well.

The global prevalence of mental health disorders has created a substantial treatment gap. To support clinicians and increase access to care, researchers in the field of Artificial Intelligence (AI) and Virtual Reality (VR) have investigated technology-mediated psychotherapy for years. However, research about stakeholders' concerns and their readiness to use AI in psychotherapy remains scarce. This study focuses on a user-centered approach to accommodate patients' concerns and, based on the results, implement measures to foster self-disclosure and trust towards an embodied AI therapist in VR. First, we conducted an online study with mental health patients $(N=152)$, which identified data autonomy and transparency as their primary ethical concerns. In a subsequent in-person VR study $(N=90)$ we compared effects of increased data autonomy and transparency on self-disclosure and trust towards an embodied AI therapist. Results indicated that higher data autonomy led to greater self-disclosure, while transparency had no significant effect. Manipulating data autonomy and transparency did not affect perceived trust, though exploratory calculations revealed that women reported significantly higher trust levels than men. These findings illuminate patients' priorities and provide implications for technical designs for AI-driven mental health care.

This paper presents an interaction study with a mixed-cultural Intelligent Virtual Agent (IVA) that investigates the impact of perceived ingroup similarity on the empathy of human interlocutors, and the perceived competence and warmth of the IVA. We herefore implemented an interactive scenario with either an IVA that should be perceived as an ingroup member or a neutral IVA. Our results show that the IVA in the ingroup condition triggered significantly more empathy and was rated significantly more competent than the IVA in the neutral condition. Regarding perceived warmth, both IVAs were rated rather high, revealing no significant differences. With these results we contribute to the goal of raising empathy towards IVAs with mixed-cultural backgrounds, to be potentially used in scenarios that aim at studying and reducing implicit racial bias.

This paper presents an interaction study that investigates whether participants adapt their verbal and non-verbal behaviour towards an IVA that shows non-native speech patterns in a way that is congruent to observations previously made in human-human and human-agent interaction. In a between-subjects design, participants either interacted with an IVA speaking native-accented German, an IVA speaking German with a non-native accent, or an IVA speaking grammatically incorrect German with a non-native accent in VR. The results reveal that participants partly adapt their verbal and non-verbal behaviour when interacting with the IVAs with non-native speech patterns, which constitutes important implications for the cost-efficient design of enculturated IVAs.

This paper presents an exploratory study investigating the impact of non-native accented speech on the perception of Intelligent Virtual Agents (IVAs). In an online study, native English speakers watched a video of an IVA holding a monologue whilst speaking English with either a Spanish, Hindi or Mandarin accent that was either recorded by native speakers of that respective language (natural speech) or synthetically generated (synthetic speech). The results showed a significant impact of naturalness of speech on the IVAs perceived warmth and a significant interaction of accent and naturalness of speech on its perceived competence. The naturalness of speech impacted the participants’ perception of the IVA as a non-native speaker of English, and the correctness of the attributed mother tongue in the Spanish and the Mandarin accent condition. These results are a valuable contribution to research on mixed-cultural IVAs in general and non-native speech as a cultural cue more specifically.

This paper presents an exploratory study which investigates the impact of different non-native accents and the naturalness of speech on the correct assignment of an Intelligent Virtual Agent’s (IVA) mother tongue, as well as its perceived warmth, competence and intelligibility. An online-experiment with a between subjects design was conducted, in which the participants, who were native speakers of German, watched a video of an IVA that spoke German with a non-native accent. The IVA’s speech was either synthetically generated or pre-recorded using non-native speakers. The participants experienced an IVA with either a Turkish, Italian or Polish accent, based on the most frequent accents in the German-speaking area. The results revealed that the IVA’s accent impacted its perceived warmth, but not its perceived competence and intelligibility. The IVA’s naturalness of speech played no role in its classification as a non-native speaker of German but on the correctness of the assigned mother tongue within the Polish accent condition. These results give valuable insight in the perception of non-native speaking IVAs and constitute helpful implications for future research with mixed-cultural IVAs.