Designing Interactive Movement Sonification For Hip-Hop Dance Hip-hop dance battles are events where dancers improvise to an unfamiliar DJ’s mix. The dancers’ technicality in responding to the music, along with the collective dimensions of these encounters, represents a largely unexplored area of investigation in HCI. Using an autobiographical design approach grounded in the hip-hop practice of the first author, we developed five interaction scenarios on a hip-hop–specific movement vocabulary. Our interactive sonification enables both individual and collective improvisation through synchronized motion sensing and interactive sound loops. This approach allowed us to design three interconnected workshops to investigate how dancers use sonification in improvisation. Our findings show that sonification was perceived either as a validation of movement or as a medium for open-ended exploration. We contribute with: (1) the formalization of a movement vocabulary and the design of interactive scenarios for hip-hop movement sonification, (2) insights into how dancers experience sonification through exploration and improvisation, and (3) guidelines for the design of movement sonification in hip-hop contexts.2026LGLouise Grebel et al.Université Paris-SaclayEmotion Recognition & DetectionSpatial Audio & 3D SoundDance & Body Movement ComputingCHI
Designing Movement Generation Models in Collaboration With Voguing And Dancehall DancersRecent advances in Artificial Intelligence have enabled powerful generative models, yet few are tailored to dancers’ practices. We present a long-term collaboration with a Voguing and Dancehall collective to design movement generation models trained on their repertoire. Our initial study with the dancers revealed that, despite limited {physical} realism, the generated movements inspired them. Iterative development led to Korai, an interactive tool for monitoring training, visualizing motion data, and prompting generation, which improved output quality. A subsequent structured observation study compared three model variants with high, medium, and low fidelity to the original dataset's {style}. Results show that dancers favored either highly faithful or highly unfaithful outputs, rejecting medium fidelity as neither authentic to their style nor creatively stimulating. Our findings highlight how direct collaboration with dancers not only informs model design but also deepens understanding of AI’s role in supporting creative movement practices.2026LCLéo Chédin et al.Université Paris-SaclayGenerative AI (Text, Image, Music, Video)Brain-Computer Interface (BCI) & NeurofeedbackFull-Body Interaction & Embodied InputCHI
Artists on a Decade of AI Evolution: An Interview Study of Affordances, Culture, and Artistic Practice with Machine LearningIn the mid-2010s, media artists began developing practices using machine learning (ML) as an artistic medium. Since 2022, the rise of large generative models, the mainstreaming of AI as consumer products, and intensifying ethical disputes have reconfigured the conditions of their artistic practice. This paper aims to understand how artists working with ML over the past decade respond to these shifts, shedding light on how practices, tools, and culture co-evolve. We address this question through thematic analysis of semi-structured interviews with 30 artists active before 2020. Our findings show how artists experience narrowing aesthetics and reduced malleability of post-2020 ML systems, have diverging views on where to locate moral responsibility with large AI models, and face shifting cultural reception that challenges the legibility of their work. We map how artists envision their practice going forward and discuss those orientations with respect to HCI conversations on design and creativity.2026TSTéo Sanchez et al.Ludwig Maximilian University of MunichGenerative AI (Text, Image, Music, Video)AI-Assisted Creative WritingInclusive DesignCHI
Designing Counter-Choreographies: Embodied Choreographic Approaches for Critical Examination of Online TrackingThis paper describes a workshop conducted as part of practice-based research that investigates online tracking algorithms commonly found in everyday web environments. The workshop introduced participants to online tracking algorithms through choreographic lenses. A series of exercises informed a discussion on the topics and strategies to counteract data-driven extractivist technologies. We analysed the outcomes of our workshop and showed that it allowed individuals to become more aware of their lack of control over data harvesting and its use by digital services, and enabled them to develop strategies for reclaiming their agency over their personal data. We discuss how the choreographic approach used in the workshop contributes to engage people in critical examination of online tracking in their day-to-day and to inspire forms of countering those same extractive algorithmic systems. Our paper contributes with empirical insights on how choreography can be used to raise awareness of data tracking online.2025JCJoana Chicau et al.Dark Patterns RecognitionTechnology Ethics & Critical HCIC&C
Human-Centered AI Communication in Co-Creativity: An Initial Framework and InsightsHow AI communicates with humans is crucial for effective human-AI co-creation. However, many existing co-creative AI systems cannot communicate effectively, limiting their collaborative potential. This paper presents the initial design of the Framework for AI Communication (FAICO) for co-creative AI, developed through a systematic review. FAICO highlights key aspects of AI communication and their impact on user experience, offering preliminary guidelines for designing human-centered AI communication. To improve the framework, we conducted a formative study with two focus groups involving skilled individuals in AI, HCI, and design. These sessions sought to understand participants' preferences for AI communication, gather their perceptions of the framework, collect feedback for refinement, and explore its use in co-creative domains like collaborative writing and design. Our findings reveal a preference for a human-AI feedback loop over linear communication and emphasize the importance of context in fostering mutual understanding. Based on these insights, we propose actionable strategies for applying the framework in practice and future directions, marking the first step toward developing comprehensive guidelines for designing effective human-centered AI communication in co-creation.2025JRJeba Rezwana et al.Human-LLM CollaborationCreative Collaboration & Feedback SystemsC&C
Lyric Poetry in the Face of Posthumanism: An Analysis of Generative AI-Assisted Poetry WritingGenerative AI seems poised to transform a wide range of endeavors once thought to be solely the domain of humans—from journalism to legal practice to creative expression—into collaborative activities involving both human and machine. Poetry is no exception, as even general-purpose language models now routinely generate convincing emulations of poetic form. While researchers have closely examined such machine-generated poetry, few have studied human-AI collaboration in poetry writing from a posthuman perspective. Through semi-structured interviews with ten participants in an AI English poetry contest and an analysis of their dialogs with AIs, we summarize the affordances and challenges of such collaborative practice using posthumanism as a lens. We then expose interesting tensions, for example, between human self-expression and the diminished (or relocated) agency that AI collaboration often entails. This collaborative, yet often adversarial, process provides insights into the nature of the posthuman condition as regards creative collaboration between human and machine.2025YHYuxuan Huang et al.Generative AI (Text, Image, Music, Video)AI-Assisted Creative WritingC&C
Cultural Erosion or Innovation? Artisans’ Attitudes Toward AI-Generated Patterns in Traditional Chinese SubculturesGenerative Artificial Intelligence (GAI), particularly text-to-image (T2I) generation tools, presents new possibilities for preserving and innovating traditional cultural patterns. However, AI-generated images often lack cultural context, which risks cultural bias and the loss of cultural significance. This study explores the use of GAI in generating culturally meaningful patterns, focusing on Chinese intangible cultural heritage Huayao cross-stitch as a case study. By applying Low-Rank Adaptation (LoRA) fine-tuning to optimize T2I tools and using in-situ interviews and focus groups, we collected feedback from 18 Huayao artisans. The results show that while fine-tuned models improved stylistic accuracy, the cultural meaning of the patterns remained insufficient. This research highlights AI’s limited role in cultural innovation and emphasizes the necessity for dynamically maintaining cultural authenticity through the daily practices of cultural holders. It also reflects on how AI might have a long-term impact on the creative position of artisan communities.2025XYXiaojing Yuan et al.Generative AI (Text, Image, Music, Video)Technology Ethics & Critical HCIMuseum & Cultural Heritage DigitizationDIS
Exploring Legal Journeys in Family Justice Systems: Towards Relational Design Approaches to Advance Access to Justice for Domestic Abuse Survivors Access to justice includes mechanisms enabling people to have their voice heard, exercise their rights, and hold decision-makers accountable. This paper reports on an exploratory study aiming to understand Domestic Abuse (DA) survivors’ experiences of legal journeys through Family Court (FC) and Family Justice Systems (FJS) in England and Wales, and the potential for digital technologies to support their access to justice. We used qualitative methods including interviews and designed prompts to engage eight DA survivors and three Family Court professionals. Designed prompts enabled discussions and articulation of perceptions of socio-technical systems’ potential to support access to justice in FJS. Our findings describe challenges faced by survivors when accessing FJS, participating in proceedings, and living with outcomes stemming from Family Courts processes. We discuss opportunities for digital interventions in these contexts and provide design orientations for relational approaches to design research seeking to advance access to justice for DA survivors across legal jurisdictions.2025CCClara Crivellaro et al.Empowerment of Marginalized GroupsParticipatory DesignDIS
Cracking Aegis: An Adversarial LLM-based Game for Raising Awareness of Vulnerabilities in Privacy ProtectionTraditional methods for raising awareness of privacy protection often fail to engage users or provide hands-on insights into how privacy vulnerabilities are exploited. To address this, we incorporate an adversarial mechanic in the design of the dialogue-based serious game Cracking Aegis. Leveraging LLMs to simulate natural interactions, the game challenges players to impersonate characters and extract sensitive information from an AI agent, Aegis. A user study (n=22) revealed that players employed diverse deceptive linguistic strategies, including storytelling and emotional rapport, to manipulate Aegis. After playing, players reported connecting in-game scenarios with real-world privacy vulnerabilities, such as phishing and impersonation, and expressed intentions to strengthen privacy control, such as avoiding oversharing personal information with AI systems. This work highlights the potential of LLMs to simulate complex relational interactions in serious games, while demonstrating how an adversarial strategy provides a unique perspective in designing for social good, particularly in privacy protection.2025JFJiaying Fu et al.Serious & Functional GamesPrivacy Perception & Decision-MakingDark Patterns RecognitionDIS
Generative AI in Documentary Photography: Exploring Opportunities and Challenges for Visual StorytellingGenerative AI is increasingly used to create images from text, but its role in documentary photography remains under-explored. This paper investigates how generative AI can be integrated into documentary practice while maintaining ethical standards. Through interviews with six documentary photographers, we explored their views on AI’s potential to support community-driven storytelling. While AI presents opportunities for creative expression and community involvement, concerns about trust, authenticity, and decontextualization of images persist. Photographers expressed doubts about AI’s ability to accurately represent lived experiences, fearing it could compromise narrative integrity. Our findings suggest that AI tools should be designed to enhance collaboration and transparency in storytelling, complementing rather than replacing traditional documentary methods. This study contributes to the ongoing discourse on AI in photography, advocating for the development of tools that preserve the ethical foundations of documentary storytelling while empowering communities.2025LMLenny Martinez et al.Sorbonne Université, Institut des Systèmes Intelligents et de RobotiqueGenerative AI (Text, Image, Music, Video)AI-Assisted Creative WritingCHI
Human-Computer Counter-Choreographies: raising awareness of data tracking through live codingIn this paper we describe how we designed the performance Human-Computer Counter-Choreographies (HCCC) using a methodology that borrows from artistic research, critical design, choreography, and embodied sense-making. HCCC is a live-coding performance in which I (the first author) manipulate JavaScript code and use a modified version of the open-source DuckDuckGo privacy extension to unveil online tracking algorithms on stage. Throughout the performance, the audience is encouraged to participate in a sequence of choreographic prompts where they embody aspects of online tracking such as fingerprinting and profiling. We analysed audience responses to questionnaires after three performances of HCCC and found that it allows audience members to gain awareness and engage their bodies to critically reflect on online tracking. We contribute a new approach to live-coding that bridges choreography with online tracking, and present empirical findings on the efficacy of this approach to engage audiences in reflecting on data tracking.2025JCJoana Chicau et al.University of the Arts London, Creative Computing InstituteContext-Aware ComputingHuman-Nature Relationships (More-than-Human Design)Dance & Body Movement ComputingCHI
Tuning In to Intangibility: Reflections from My First 3 Years of Theremin LearningThis paper presents an autoethnography of 3 years of learning to play the theremin, an instrument lacking tangible feedback. While the theremin is typically invoked in HCI to emphasize the importance of the tactile modality, we interrogate how I, the player, attained musical proficiency without touch. Through a thematic analysis of 235 journal entries, our study distills my strategies for navigating the instrument as well as my personal transformations along the way. We discover that without touch, accurate and musical playing on the theremin relies on continuous auditory feedback, proprioception, and imaginative processes. We discuss challenges and opportunities for embodied and tangible interaction in light of these findings.2024XXXiao Xiao et al.Full-Body Interaction & Embodied InputDance & Body Movement ComputingDIS
Using Incongruous Genres to Explore Music Making with AI Generated ContentDeep learning generative AI models trained on huge datasets are capable of producing complex and high quality music. However, there are few studies of how AI Generated Content (AIGC) is actually used or appropriated in creative practice. We present two first-person accounts by musician-researchers of explorations of an interactive generative AI system trained on Irish Folk music. The AI is intentionally used by musicians from incongruous genres of Punk and Glitch to explore questions of how the model is appropriated into creative practice and how it changes creative practice when used outside of its intended genre. Reflections on the first-person accounts highlight issues of control, ambiguity, trust, and filtering AIGC. The accounts also highlight the role of AI as an audience and critic and how the musicians’ practice changed in response to the AIGC. We suggest that our incongruous approach may help to foreground the creative work and frictions in human-AI creative practice.2024NBNick Bryan-Kinns et al.Generative AI (Text, Image, Music, Video)AI-Assisted Creative WritingMusic Composition & Sound Design ToolsC&C
Reflection Across AI-based Music CompositionReflection is fundamental to creative practice. However, the plurality of ways in which people reflect when using AI Generated Content (AIGC) is underexplored. This paper takes AI-based music composition as a case study to explore how artist-researcher composers reflected when integrating AIGC into their music composition process. The AI tools explored range from Markov Chains for music generation to Variational Auto-Encoders for modifying timbre. We used a novel method where our composers would pause and reflect back on screenshots of their composing after every hour, using this documentation to write first-person accounts showcasing their subjective viewpoints on their experience. We triangulate the first-person accounts with interviews and questionnaire measures to contribute descriptions on how the composers reflected. For example, we found that many composers reflect on future directions in which to take their music whilst curating AIGC. Our findings contribute to supporting future explorations on reflection in creative HCI contexts.2024CFCorey Ford et al.Generative AI (Text, Image, Music, Video)Music Composition & Sound Design ToolsCreative Collaboration & Feedback SystemsC&C
SnapInflatables: Designing Inflatables with Snap-through Instability for Responsive InteractionSnap-through instability, like the rapid closure of the Venus flytrap, is gaining attention in robotics and HCI. It offers rapid shape reconfiguration, self-sensing, actuation, and enhanced haptic feedback. However, conventional snap-through structures face limitations in fabrication efficiency, scale, and tunability. We introduce SnapInflatables, enabling safe, multi-scale interaction with adjustable sensitivity and force reactions, utilizing the snap-through instability of inflatables. We designed six types of heat-sealing structures enabling versatile snap-through passive motion of inflatables with diverse reaction and trigger directions. A block structure enables ultra-sensitive states for rapid energy release and force amplification. The motion range is facilitated by geometry parameters, while force feedback properties are tunable through internal pressure settings. Based on experiments, we developed a design tool for creating desired inflatable snap-through shapes and motions, offering previews and inflation simulations. Example applications, including a self-locking medical stretcher, interactive animals, and a bounce button, demonstrate enhanced passive interaction with inflatables.2024YYYue Yang et al.Zhejiang UniversityShape-Changing Interfaces & Soft Robotic MaterialsCHI
Thinking with Sound: Exploring the Experience of Listening to an Ultrasonic Art Installation Entanglement theories are well established in HCI discourse. These involve a commitment to view human experience in encounters with technology as relational and contingent, and research apparatuses as co-producers rather than passive observers of phenomena. In this paper, we argue that sound is the sensory modality best suited to the investigation of entanglements. Materialist theories of sound and listening guide both the design of a novel interactive sound installation and the methodological approach of a participant study exploring the experience of listening. We present a diffractive analysis whereby micro-phenomenological interview data is read with sonic theories, generating accounts that might otherwise remain mute: the temporal fluctuation and physical feeling of proximity in listener entanglements with sound, somatic intention setting, and plural interpretations of interactivity. Finally, we offer a series of provocations for HCI to embrace qualities of the sonic and consider epistemological positions grounded in other sense modalities.2024NRNicole Robson et al.Queen Mary University of LondonMid-Air Haptics (Ultrasonic)Digital Art Installations & Interactive PerformanceCHI
Embodying an Interactive AI for Dance Through Movement IdeationWhat expectations exist in the minds of dancers when interacting with a generative machine learning model? During two workshop events, experienced dancers explore these expectations through improvisation and role-play, embodying an imagined AI-dancer. Through discussions with the participants we identify a variety of ways an AI-dancer might be useful to human dancers. The dancers explored how intuited flow, shared images, and the concept of a human replica might work in their imagined AI-human interaction. Our findings challenge existing assumptions about what is desired from generative models of dance, such as expectations of realism, and how such systems should be evaluated. We further advocate that such models should celebrate non-human artefacts, focus on the potential for serendipitous moments of discovery, and that dance practitioners should be included in their development. Our concrete suggestions show how our findings can be adapted into the development of improved generative and interactive machine learning models for dancers' creative practice.2023BWBenedikte Wallace et al.Generative AI (Text, Image, Music, Video)Digital Art Installations & Interactive PerformanceDance & Body Movement ComputingC&C
Fluid Speculations: Drawing Artefacts in Watercolour as Experimentation in Research Through DesignThis pictorial paper presents design experimentations using drawing, watercolour and storytelling as forms of speculation about artefacts and technologies. The use of watercolour, a medium that bleeds and has leaky boundaries, allowed ambiguity, defamiliarization and critical reflection to enter the research space, encouraging new understandings of artefacts and their latent possibilities. Watercolour was also valuable for speculating about designs that deal with bodily fluids, and for Drawing Conversations that facilitated reinterpretations of artefacts through drawings created by two different people. Intersecting themes about cognition, creativity and technology, this pictorial presents examples that illustrate how watercolour drawing can impact on the representation of speculative concepts, including the creation of visual conversations. The drawings shown here are presented as representations embodying families of ideas and themes related to the objects they symbolize, together with the design spaces they suggest and the stories they invite us to imagine.2022PYPaulina YurmanDesign FictionDigital Art Installations & Interactive PerformanceC&C
Drawing Conversations Mediated by AIIn this pictorial paper, we present a series of drawing conversations held between two humans, mediated by computational GAN models. We consider how this creative collaboration is affected by the hybrid inclusion of more-than-human participants in the form of watercolour and artificial intelligence. Our drawing experiments were an extension of our search for new ways of seeing and telling, which includes a reflection of the extent to which more-than-human elements took part in our creative process. We discuss our tendencies to form strange interpretations and assign meaning to the unpredictable and ambiguous spaces we created with them. We further speculate on the characteristic material agencies they revealed in our interactions with them. Finally, we contend how such collaborations are already and always embedded and embodied in our ways of seeing and knowing in design and creativity research.2022PYPaulina Yurman et al.Generative AI (Text, Image, Music, Video)3D Modeling & AnimationDigital Art Installations & Interactive PerformanceC&C
Keep the VRhythm Going: a Musician-Centred Study Investigating How Virtual Reality Can Support Creative Musical PracticeThe acoustic and visual experiences of musicians in the spaces they perform in is complex and organic in nature, entailing a continuous interaction with the environment. With this project, we leverage the power of Virtual Reality (VR) to support musicians in their creative practice by transporting them to novel sonic and visual worlds. For this, we developed a musician-centered VR system, featuring various acoustic and visual virtual environments, VR Rehearse & Perform, based on design requirements gathered with musicians and performance experts. To investigate how VR can be designed to support music-makers in their creative musical practice, we performed iterative tests with 19 musicians followed by semi-structured interviews. Our findings suggest that VR has the potential to support different aspects of the creative musical practice such as rehearsing, performing and improvising. Our research provides insights and inspirations toward designing musician-centred VR experiences for a variety of musical activities.2022SPSophia Ppali et al.University of the Arts, University of KentSocial & Collaborative VRImmersion & Presence ResearchCHI