Chinese ceramic-making involves complex and interdependent steps, making it technically demanding. Digital fabrication methods attempt to make the process more accessible, but for craft-creators, technical challenges such as CAD and CAM skills remain major obstacles. To address this, we designed a hybrid workflow that integrates Generative AI with clay 3D printing to support new creative possibilities. We evaluated the workflow through ClayScape, a design tool that operationalizes this approach, with four ceramic creators. Our findings show that the workflow supports accessible ceramic creation while revealing both expanded opportunities for creative exploration and challenges in balancing agency and control. This work demonstrates how hybrid workflows can lower barriers to digital fabrication while supporting creative possibilities in culturally grounded ceramic practices.

Cradle of Success is an interactive artwork that examines how human tendencies toward wishful thinking and stereotyping are transformed and amplified through interactions with Generative AI. Practices such as fortune-telling have long reflected desires to predict and control the future, often revealing underlying hopes, fears, and biases. As GenAI enters increasingly personal and social domains, these motivations are reframed through technological authority. In this installation, visitors select a baby photograph and a toy symbolizing a potential career. GenAI generates speculative life trajectories through videos and textual “fortunes,” exposing how societal stereotypes are reproduced and normalized through AI systems. Drawing inspiration from Japanese omikuji practices, visitors tie these AI-generated fortunes to a shrine-like structure, transforming biased predictions into moments of reflection. The work uses creativity as a critical lens to question how GenAI shapes notions of identity, destiny, and societal change.

Dreams are sources of inspiration for artists tapping into their subconscious states, but the uncertainty of fragmented elements and difficulty of recall make it challenging to harness dream-based inspiration for creative work. Generative AI shares a similar ambiguity with dreams, producing unexpected outputs that offer reinterpretation in the creative process. It suggests GenAI may help engage with such materials. To explore how artists work with dream content using GenAI, we held a four-week online residency with six artists including weekly sessions to process dream materials, followed by artistic creation for exhibition. Artists adapted their use of GenAI across stages: during early preparation, unexpected outputs were embraced as inspiration; during production, accuracy and coherence from GenAI were demanded. As artistic creation moves from abstract to concrete, GenAI shifts from inspirational reinterpretation to generative support. This work highlights differences in preparation and creative production when tapping into dreams for creativity.

Intangible Cultural Heritage (ICH) like traditional culinary practices face increasing pressure to adapt to globalization while maintaining their cultural authenticity.Centuries-old traditions in Chinese cuisine are subject to rapid changes for adaptation to contemporary tastes and dietary preferences.The preservation of these cultural practices requires approaches that can enable ICH practitioners to reimagine and recreate ICH for modern contexts.To address this, we created workshops where experienced practitioners of traditional Chinese cuisine co-created recipes using GenAI tools and realized the dishes.We found that GenAI inspired ICH practitioners to innovate recipes based on traditional workflows for broader audiences and adapt to modern dining contexts.However, GenAIinspired co-creation posed challenges in maintaining the accuracy of original ICH workflows and preserving traditional flavors in the culinary outcomes.This study offers implications for designing human-AI collaborative processes for safeguarding and enhancing culinary ICH.

It is difficult to tangibly feel climate change because it must be imagined into the future. The original cave painting in pre-historic times, too was an attempt to imagine the future in a creative space that we no longer understand. Generative AI (GenAI) serves as a tool for us today much as cave paintings were for pre-historic humans to imagine a climate future by interfacing our tools into drawings of our visions. TIME ENOUGH is a collective voice of today concerning the future narrated using GenAI, showing both how we envision challenges of the climate and how we may adapt to them in the future. These images and videos recreate a modern version of the age-old cave painting in the first truly creative space in human history, showing how our imaginations and anxieties of today are mere echoes of what concerned our ancestors from a seemingly remote time.

Dreams are a source of inspiration for writers, artists, and creative professionals for generations, but recent Generative AI (GenAI) tools make it possible to use natural language to record details of dreams in image form for creativity support. This workshop invites Creativity and Cognition participants working in creative fields with interest in recording and utilizing their dream materials to use GenAI to support their dream documentation. We aim to highlight the unique contribution of dream experiences to art and design inspiration and how it can be supported by technology. Participants bring their dream sketches or records for sharing, reinterpreting, and applying GenAI for visualization. Participants will use GenAI with partners to transcribe their dreams, then create an original visual story based on their own practice and the dream inspiration. The outcome is a hands-on experience with sharing dream inspiration and applying it to creative work, allowing participants to share their insights and enrich the emerging community of dream-supported creativity in HCI.

Robots are increasingly deployed in crowded, large-scale environments where the demands on their services can outweigh their ability to respond. When robots fail to respond, humans may interpret the unintended consequence negatively as a form of rejection, leading to a loss of trust. How do service robots recover from such rejection to remediate human trust due to perceived rejection? We created a task mimicking shopping malls where the robot arm is asked to provide coffee, juice, or tea to participants. When the robot rendered service elsewhere, participants reported feeling excluded and less trusting of the robot. When the robot subsequently apologized or provided promise of future favor, participants regained trust in the robot, with favor rendering yielding significantly more trust responses. This study highlights the importance of understanding inadvertently negative consequences of robot behaviors, and suggests design solutions for overcoming this negative perception through remediation strategies.

The increasing virtualization of the performance process has resulted in passive interactions between performer and audience based on the observing paradigm, but without the presence of in-person staging. We designed a more interactive paradigm of remote performance using a multimedia exhibition strategy where visitors can alter the environment of the performer's location by changing its music and lighting, whereas the performer can create engagement in the exhibition space by affecting a remote robotic arm. We conducted a case study with five participating performers, investigating their expectations, workflows, and perceptions before and after the performance-exhibition, and examining the video footage of their interactions with visitors to understand how they adapt and respond to this remote performance paradigm. We found that the robot arm was perceived as a mediating character with its own distinct identity, that musical changes have implicit behavioral effects on the performance, that lighting manipulations actively changed performer actions during improvisation, and that audiences appear to identify themselves and the robot as integral co-performers in this setup. This work provides insights into how performers learn to engage with audiences in novel distanced spaces and diverse interactive media, generating insights for future virtualized performative interactions beyond the classical stage metaphor.