Machine Learning for Creativity and Design

NeurIPS 2019 Workshop, Vancouver, Canada

Saturday December 14ᵗʰ 8:30 — 18:00

Image credit: Mario Klingemann's Neural Glitch from the NeurIPS 2018 creativity art gallery.


Generative machine learning and machine creativity have continued to grow and attract a wider audience to machine learning. Generative models enable new types of media creation across images, music, and text - including recent advances such as StyleGAN, MuseNet and GPT-2. This one-day workshop broadly explores issues in the applications of machine learning to creativity and design. We will look at algorithms for generation and creation of new media, engaging researchers building the next generation of generative models (GANs, RL, etc). We investigate the social and cultural impact of these new models, engaging researchers from HCI/UX communities and those using machine learning to develop new creative tools. In addition to covering the technical advances, we also address the ethical concerns ranging from the use of biased datasets to the use of synthetic media such as “DeepFakes”. Finally, we’ll hear from some of the artists and musicians who are adopting machine learning including deep learning and reinforcement learning as part of their own artistic process. We aim to balance the technical issues and challenges of applying the latest generative models to creativity and design with philosophical and cultural issues that surround this area of research.

The goal of this workshop is to bring together researchers interested in advancing art and music generation to present new work, foster collaborations and build networks.

Invited Speakers

Important Dates

9 September 2019: Submission date for papers and art

1 October 2019: Acceptance notification for papers and art

1 December 2019: Deadline for final copy of accepted papers

8–14 December 2019: NeurIPS Conference

14 December 2019: Workshop


If you have any questions, please contact us at

Workshop website:


Luba Elliott, AI Curator

Sander Dieleman, DeepMind

Rebecca Fiebrink, Goldsmiths University of London

Adam Roberts, Magenta, Google Brain

Jesse Engel, Magenta, Google Brain

Tom White, Victoria University of Wellington

Christine Payne, OpenAI

Parag K. Mital, HyperSurfaces, Mogees, Ltd

Nao Tokui, Keio University