The Tower of Babel. Generative Art by Mauro Martino.
Recent advances in generative modeling through deep learning approaches such as generative adversarial networks (GANs), variational autoencoders (VAEs), and sequence-to-sequence models will enable new kinds of user experiences around content creation, giving us “creative superpowers” and move us toward co-creation and curation. While the areas of computational design, generative design, and computational art have existed for some time, content with unprecedented fidelity is now being produced due to breakthroughs in generative modeling using deep learning. Ian Goodfellow’s work on face generation and StyleGan, OpenAI’s GPT-2, or recent deep fake videos of Mark Zuckerberg and Bill Gates are prominent examples of content generated by AI that is almost indistinguishable from human-generated content. These examples also highlight some of the significant societal, ethical and organizational challenges generative AI is posing including security, privacy, ownership, quality metrics and evaluation of generated content.
The goal of this half-day workshop is to bring together researchers and practitioners from both fields HCI and AI to explore and better understand both the opportunities and challenges of generative modelling from an HCI perspective. We envision that the user experience of creating both physical and digital artifacts will become a partnership of humans and AI: Humans will take the role of specification, goal setting, steering, high-level creativity, curation, and governance. AI will augment human abilities through inspiration, low level creativity and detail work, and the ability to test ideas at scale.
Submissions are encouraged but not limited to the following topics:
- Novel user experiences supporting the creation of both physical and digital artifacts in an AI augmented fashion
- Business use cases of generative models
- 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
- Governance, privacy, content ownership
- Security including forensic tools and approaches for deep fake detection
- Evaluation of generative approaches and quality metrics
- User studies
- Lessons learned from computational art and design, and generative design and how these impact research
Cathedral in Cagliari, Sardinia, Co-Creation Experience with GANPaint Studio by Hendrik Strobelt et al.
Business (mis)Use Cases of Generative AI Stephanie Houde, Vera Liao, Jacquelyn Martino, Michael Muller, David Piorkowski, John Richards, Justin Weisz and Yunfeng Zhang
Novice-AI Music Co-Creation via AI-Steering Tools for Deep Generative Models Ryan Louie, Andy Coenen, Cheng-Zhi Anna Huang, Michael Terry and Carrie Cai
Latent Chords: Generative Piano Chord Synthesis with Variational Autoencoders Agustin Macaya, Manuel Cartagena, Rodrigo Cadiz and Denis Parra
How Novelists Use Generative Language Models: An Exploratory User Study Alex Calderwood, Katy Ilonka Gero and Lydia B. Chilton
Demo: Literary Style Transfer with Content Preservation Katy Gero, Chris Kedzie and Lydia B. Chilton
Guest paper: Draw with Me: Human-in-the-Loop for Image Restoration Thomas Weber, Zhiwei Han, Stefan Matthes, Yuanting Liu and Heinrich Hussmann
We are encouraging submissions of full and short papers following the IUI Paper Guidelines as well as demos of generative deep learning systems that highlight co-creation user experiences or other topics listed above. The submission of demos also follows IUI Demo Guidelines.
All papers will be peer reviewed, single blind (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 2020. While papers and demos are not part of the archival ACM IUI proceedings, we will be published them online at CEUR Workshop Proceedings.
Please submit your papers & demos to EasyChair: https://easychair.org/my/conference?conf=haigen2020#
December 20, 2019: Paper & Demo Submissions Due
January 14, 2020: Author Notification
February 18, 2020: Camera-Ready Version of Papers and Demos Due
March 17: Workshop Day Yay
Douglas Eck, Google AI, Magenta Team
- Werner Geyer, IBM Research AI, Cambridge, MA
- Lydia Chilton, Columbia University
- Ranjitha Kumar, University of Illinois at Urbana-Champaign
- Adam Tauman Kalai, Microsoft Research, Cambridge, MA
- Nancy Baym, Microsoft Research
- Zoya Bylinskii, Adobe Research
- Carrie Cai, Google
- Elizabeth Clark, University of Washington
- Sebastian Gehrmann, Harvard School of Engineering
- Katy Gero, Columbia University
- Per Ola Kristensson, University of Cambridge
- Jacquelyn Martino, IBM Research AI
- Mauro Martino, IBM Research AI
- Michael Mateas, University of California, Santa Cruz
- Antti Oulasvirta, Aalto University
- Dafna Shahaf, Hebrew University of Jerusalem
- Akash Srivastava, IBM Research AI
- Hendrik Strobelt, IBM Research AI
- Michael Terry, Google
- Steven Wu, University of Minnesota
- Haiyi Zhu, Carnegie Mellon University