Following the success of CLIP 2026, The workshop brings together AI researchers, artists and industry practitioners building systems that collaborate with humans in real time across the performing arts including music, dance, drama and the visual arts. A central issue we will address is how to design AI systems that can meaningfully participate in real-time creative workflows so as to enhance human performance. Unlike generative AI that produces finished creative outputs, interactive creative AI must respond dynamically to human input, adapt to context, and facilitate on-going artist-AI collaboration.
The workshop will focus on the unique technical and methodological challenges that arise when people interact with AI systems during the creative process. Key questions include:
How can AI adapt to the improvised and subjective nature of performance, and do so in real-time?
What paradigms best support human-AI interactive collaboration?
How do we evaluate systems where the novelty of output and improvisation may be valued above correctness?
The second iteration sharpens this focus into three themes which recurred throughout the first workshop and remain open: how to evaluate such systems, how performers and models negotiate control over a performance as it unfolds, and what forms of interdisciplinary collaboration between AI researchers, artists and industry practitioners produce systems that work in live settings. The workshop aims to address this through sharing ideas via presentations, keynote speakers and round table discussions as well as sharing practice through live interactive demos.
This workshop will accept submissions primarily focusing on systems that facilitate real-time AI live performances. Specifically, we are interested in performance exploring how AI can be embodied in a way that it connects to our own bodies in new and creative ways. This might involve a wide range of modalities including touch, music and brain-computer interaction, as well as diverse sensors and actuators that might be attached to performers or to machines (e.g. human-robot interaction) so as to capture data for and deliver stimuli generated by AI. While much recent work on creative AI has focused on large-scale generative models, there has been less attention to how these models can be effectively integrated into live interactive performances.
The other specific area of emerging interest is the social, legal, and cultural implications of AI. As these systems become more prevalent in creative industries, questions arise about authorship. Therefore, the workshop is interested in both technical approaches to building trustworthy creative AI as well as frameworks for understanding the broader impact on creative communities and practices.
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