INTRODUCTION

Recent advances in deep learning approaches to generative AI, such as generative adversarial networks (GANs), variational autoencoders (VAEs), and language models will enable new kinds of user experiences around content creation. These advances have enabled content to be produced with an unprecedented level of fidelity. In many cases, content generated by generative models is either indistinguishable from human-generated content or could not be produced by human hands. We believe that people skilled within their creative domain can realize great benefits by incorporating generative models into their own work: as a source of inspiration, as a tool for manipulation, or as a creative partner. However, recent deep-fake examples of prominent business leaders highlight the significant societal, ethical, and organizational challenges generative AI poses around issues such as security, privacy, and ownership.

The goal of this workshop is to bring together researchers and practitioners from the domains of HCI & AI to establish a joint community to deepen our understanding of the human-AI co-creative process and to explore the opportunities and challenges of creating powerful user experiences with deep generative models. We envision that the user experience of creating both physical and digital artifacts will become a partnership between people and AI: people will take the role of specification, goal setting, steering, high-level creativity, curation, and governance, whereas AI will augment human abilities through inspiration, creativity, low-level detail work, and the ability to design at scale.

The central question of our workshop is: how can we build co-creative systems that make people feel that they have “creative superpowers”? How will user needs drive the development of generative AI algorithms, and how can the capabilities of generative models be leveraged to create effective co-creative user experiences?

SUBMISSION GUIDELINES

We are accepting submissions in the form of short papers (6 pages), long papers (14 pages), and demos (6 pages) following the IUI submission guidelines for papers.

Submissions are encouraged, but not limited to, the following topics:

• Novel, AI-augmented user experiences that support the creation of physical and/or digital artifacts}
• Business use cases & novel applications of generative models
• Techniques, methodologies, & algorithms that enable new user experiences and interactions with generative models and allow for directed and purposeful manipulation of the model output
• Issues of governance, privacy, and ownership of AI-generated or human-AI co-created content
• Security, including forensic tools and approaches for deep fake detection
• Evaluations of human-AI co-creative processes and quality metrics of AI-generated or human-AI co-created content
• User research on needs & algorithmic requirements for co-creative systems, perceptions of human-AI co-creative systems, trust of co-creative tools & artifacts, and/or implications for HCI theories
• Lessons learned from computational art & design and generative design, and how these impact research

All papers will undergo a single blind peer review (i.e. author names and affiliations should be listed). If accepted, at least one of the authors must attend the workshop to present the work. A workshop summary will be included in the ACM Digital Library for IUI 2021. Although papers and demos are not part of the archival ACM IUI proceedings, we intend to publish them online at CEUR: http://ceur-ws.org/

Please submit your papers & demos to EasyChair: https://easychair.org/conferences/?conf=haigen2021