ExtendAI makes plan for action extends user's plan by embedding feedback makes sense of plan containing AI's feedback makes final decision RecommendAI makes sense of AI's suggestions makes suggestion for action makes final decision Figure 1: Illustrative comparison of the thought process when interacting with two 'types' of AI -RecommendAI and ExtendAI.

Navigating emotional conflicts within relationships can be challenging. People often struggle to express their emotions during a conflict, which can lead to misunderstandings and unresolved feelings. To facilitate deeper emotional expression, we developed TogetherReflect, a multi-user Virtual Reality (VR) experience designed for couples. Partners first draw their emotions related to a shared conflict in VR, allowing for individual expression and self-reflection. They then invite each other into their drawings to discuss their feelings, before drawing together on a shared canvas to reaffirm their love and commitment. Throughout this process, TogetherReflect provides prompts and guidance, aiming to foster self-reflection and communication skills. We exploratory evaluated the experience with 10 couples (n=20). Our findings indicate that TogetherReflect deepens personal emotional insights, fosters mutual understanding, and strengthens relational bonds. We highlight the potential of guided VR experiences to transform conflict resolution in intimate relationships and offer design considerations for future development.

Negative emotions such as sadness or anger are often seen as something to be avoided. However, recognising, processing and regulating challenging emotional experiences can facilitate personal growth and is essential for long-term well-being. To support people in regulating and reflecting on negative emotions, we designed MoodShaper — a VR experience where participants autonomously create a virtual environment combined with emotion regulation (ER) interventions. Our system included three different interventions designed based on interviews with psychotherapists. We evaluated MoodShaper in a mixed-method between-subject study with n = 60 participants. Participants experienced one of the three ER interventions, allowing them to manipulate visual representations of negative emotions through externalisation, seclusion, or appreciation. We found that MoodShaper significantly increased positive affect while decreasing difficulties in ER and negative affect. Our work demonstrates how VR can provide technology-mediated support to reflect on, engage with and manage negative emotions. We contribute insights for future VR systems which support ER for challenging situations.

Adolescence is a period of growth and exploration, marked by influential relationships with peers and parents. These relationships are essential for teenagers’ well-being, highlighting the need to support their interpersonal interactions. Emotional expression is key in resolving conflicts that can frequently arise. This paper investigates the potential of TeenWorlds, a Virtual Reality (VR) application, to facilitate emotional expression and shared understanding among teenagers and their peers and parents. In our study, teenagers, accompanied by either a peer or a parent (total n=42), used TeenWorlds to visually represent their emotions during a shared conflict, discuss them, and collaborate on a joint VR drawing. Our findings indicate that TeenWorlds can foster communication, reflection, and strengthen interpersonal relationships. However, notable differences were observed in interactions with peers versus parents. We contribute insights into designing VR systems that support reflective experiences and meaningful family interactions, ultimately enhancing the well-being of adolescents, parents, and families.

Whether it is sleep, diet, or procrastination, changing behaviours can be challenging. Individuals could design and build their own personalised digital interventions to help them reach their goals, but little is known about this process. Building upon previous research we propose the Behaviour Change with Trigger-Action Programming (BC-TAP) model which describes how individuals could bridge the gap between their current and desired behaviour through the creation of 'Do-It-Yourself' (DIY) digital interventions. We conducted a two-day participatory workshop based on the BC-TAP model with 28 participants. Participants articulated plans to change a behaviour of their choice and represented these plans in mobile device automations. After using their interventions for up to three weeks, participants reflected on their experience. Our findings report opportunities and challenges at each stage of the process. While formulating a digital proxy for certain behaviours was challenging, both failures and successes facilitated participants' awareness of their behaviour, and their ability to change it.

Reflecting on personal challenges can be difficult. Without encouragement, the reflection process often remains superficial, thus inhibiting deeper understanding and learning from past experiences. To allow people to immerse themselves in and deeply reflect on past challenges, we developed SelVReflect, a VR experience which offers active voice-based guidance and a space to freely express oneself. SelVReflect was developed in an iterative design process (N=5) and evaluated in a user study with N=20 participants. We found that SelVReflect enabled participants to approach their challenge and its (emotional) components from different perspectives and to discover new relationships between these components. By making use of the spatial possibilities in VR, participants developed a better understanding of the situation and of themselves. We contribute empirical evidence of how a guided VR experience can support reflection. We discuss opportunities and design requirements for guided VR experiences that aim to foster deeper reflection.

With rapid advances in artificial intelligence and natural language processing, voice assistants are evolving into advanced digital personal assistants capable of complex tasks. As they become more proficient at understanding people’s behaviors, preferences, intentions, and surroundings, opportunities for proactive interactions emerge. However, despite their potential benefits, people still find certain proactive agent interactions inappropriate and invasive, such as correcting or nudging the user. This study investigates humor’s potential to enhance the desirability of proactive agent comments, given its stress-relieving and acceptance-promoting characteristics. We investigate how infusing humor into VA statements affects perceptions of appropriateness and desirability in proactive interventions. We designed storyboards showcasing voice assistants’ proactive actions in everyday situations and social contexts. Participants () assessed these scenarios in an online questionnaire across multiple criteria. Our results reveal that humor’s impact on proactive statement desirability is contingent on participants’ perceptions of voice assistants and their subjective judgment of the humor.

Voice assistants have become hugely popular in the home as domestic and entertainment devices. Recently, there has been a move towards developing them for work settings. For example, Alexa for Business and IBM Watson for Business were designed to improve productivity, by assisting with various tasks, such as scheduling meetings and taking minutes. However, this kind of assistance is largely limited to planning and managing user's work. How might they be developed to do more by way of empowering people at work? Our research is concerned with achieving this by developing an agent with the role of a facilitator that assists users during an ongoing task. Specifically, we were interested in whether the modality in which the agent interacts with users makes a difference: How does a voice versus screen-based agent interaction affect user behavior? We hypothesized that voice would be more immediate and emotive, resulting in more fluid conversations and interactions. Here, we describe a user study that compared the benefits of using voice versus screen-based interactions when interacting with a system incorporating an agent, involving pairs of participants doing an exploratory data analysis task that required them to make sense of a series of data visualizations. The findings from the study show marked differences between the two conditions, with voice resulting in more turn-taking in discussions, questions asked, more interactions with the system and a tendency towards more immediate, faster-paced discussions following agent prompts. We discuss the possible reasons for why talking and being prompted by a voice assistant may be preferable and more effective at mediating human-human conversations and we translate some of the key insights of this research into design implications.