While reciprocal self-disclosure drives intimacy, digital tools seldom scaffold autonomy, competence, and relatedness—the motivational underpinnings defined by Self-Determination Theory (SDT) that enable deep exchange. We introduce a chatbot employing dual-layer scaffolding to satisfy these needs: first providing enabling affordances (instrumental support) for vulnerability, then mediating affordances (relational support) for responsiveness. In a randomized study (N = 72; 36 couples) comparing Partner Support (PS: both layers), Direct Support (DS: enabling only), and Basic Prompt (BP: questions only), results reveal a critical distinction. While enabling affordances (PS, DS) were sufficient to deepen disclosure, only mediating affordances (PS) reliably elicited partner-provided need support and increased perceived closeness. Furthermore, controlled motivation decreased across conditions, and scaffolding buffered vitality, which remained stagnant in BP. We contribute empirical evidence that SDT-guided mediation fosters connection, offering a practical framework for designing AI-mediated conversations that support, rather than replace, human intimacy.

Nudging participants with text-based reflective nudges enhances deliberation quality on online deliberation platforms. The effectiveness of multimodal reflective nudges, however, remains largely unexplored. Given the multi-sensory nature of human perception, incorporating diverse modalities into self-reflection mechanisms has the potential to better support various reflective styles. This paper explores how presenting reflective nudges of different types (direct: persona and indirect: storytelling) in different modalities (text, image, video and audio) affects deliberation quality. We conducted two user studies with 20 and 200 participants respectively. The first study identifies the preferred modality for each type of reflective nudges, revealing that text is most preferred for persona and video is most preferred for storytelling. The second study assesses the impact of these modalities on deliberation quality. Our findings reveal distinct effects associated with each modality, providing valuable insights for developing more inclusive and effective online deliberation platforms.

Mutual reminiscence, defined as revisiting shared positive memories through reciprocal self-disclosure, strengthens emotional bonds, enhances well-being, and deepens intimacy. However, most technology-mediated reminiscence tools emphasize individual reflection or one-way storytelling, which overlooks the dynamic, interactive dialogue essential for meaningful mutual reminiscence. To address this limitation, we introduce Remini, a chatbot designed to support reciprocal self-disclosure between close partners such as couples, friends, or family members. Grounded in the Social Functions of Autobiographical Memory (SFAM) framework, Remini uses conversational AI to guide emotionally rich exchanges through five narrative phases: rapport building, memory narration, elaboration, reflection, and summary. In a mixed-method, both between- and within- subjects study (N = 48, 24 dyads), we compare Remini to a baseline chatbot that offers minimal memory-trigger prompts. Our findings show that structured guidance from Remini significantly improves positive affect, feeling of connection, and engagement. It also fosters more detailed narrative co-construction and greater reciprocal self-disclosure. Participant feedback highlights the practical value, perceived benefits, and design considerations of chatbot-mediated reminiscence. We contribute empirically grounded design implications for conversational agents that strengthen human connection through mutual reminiscence.

Social robots are rarely confined to a task-specific or problem-specific work envelope. For instance, an assistive robot working in a senior center can incidentally become a companion or even a trusted confidante. Increasingly operating in public spaces, social robots can be easily caught in mundane yet morally ambivalent urban situations that are often dynamic, complex, and unpredictable, presenting novel factors and agencies that can quickly exceed the scope of any projected human-robot interaction. Anticipating how a robot should respond in these situations may mitigate interaction failures. To improve foresight in these situations, we propose the frame of “Situated Ethics for Urban Encounters” (SEUE) and probe this frame through 18 mundane yet morally ambivalent scenarios of human-robot interaction in a public library using the speed-dating research method with storyboards. Our findings suggest: (i) There are ambiguous but morally important interactions even in a public library; (ii) Unlike humans, robots are expected to do many things at once and some actions may risk deception; (iii) The importance of children’s rights in these situations; (iv) A need for creatively opportunistic interaction when responding to the ethical challenges of the situation; and (v) Residual risks exist even in a perceived ethical response on the part of the robot. We contribute to empirical HRI ethics by demonstrating how the speed-dating technique in a participatory design setting could be used to unpack, interpret, discuss, and elicit possible HRI responses in urban situations, which are expected to only become more important as robots show up in cities.

Could robotic furnishings become reading companions for children? This paper investigates how a socially interactive robotic bookshelf may influence children’s enthusiasm, persistence, and enjoyment in reading when they are absorbed in other, usually more addictive activities such as playing iPad games or toys. We designed and developed a low-fidelity, elephant-like robotic bookshelf, and used WoZ technique to conduct an experiment in a public library in Singapore with 7 child-parent pairs to assess the effectiveness of this socially interactive, mobile robotic bookshelf in attracting children to read physical books while iPad games and toys were present. The results indicate that the robotic bookshelf was successful in attracting 5 out of 7 children to read books, with variations observed in the timing of switching to book reading from playing iPad games or toys. Currently, most robot reading companions are tabletop robots passively waiting for children to come to the robots and read with them. This study, however, highlights a unique approach in which a mobile, robotic bookshelf reading companion proactively engages children in reading by bringing physical books to them. In a modern world where screen and other addictions become increasingly real for children, such mobile robotic bookshelves have great potential to benefit children’s literacy and overall development.