HAI-GEN 2021: 2nd Workshop on Human-AI Co-Creation with Generative Models

Recent advances in generative AI have resulted in a rapid and dramatic increase to the fidelity of created artifacts, from realistic-looking images of faces [10] to antimicrobial peptide sequences that treat diseases [5] to faked videos of prominent business leaders [4, 11]. 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. Our workshop will bring together researchers and practitioners from both the HCI and AI disciplines to explore and better understand the opportunities and challenges in building, using, and evaluating human-AI co-creative systems.

[1]  Timo Aila,et al.  A Style-Based Generator Architecture for Generative Adversarial Networks , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[2]  Yoshua Bengio,et al.  Generative Adversarial Nets , 2014, NIPS.

[3]  Jürgen Schmidhuber,et al.  Long Short-Term Memory , 1997, Neural Computation.

[4]  Mark Chen,et al.  Language Models are Few-Shot Learners , 2020, NeurIPS.

[5]  Cícero Nogueira dos Santos,et al.  PepCVAE: Semi-Supervised Targeted Design of Antimicrobial Peptide Sequences , 2018, 1810.07743.

[6]  Max Welling,et al.  Auto-Encoding Variational Bayes , 2013, ICLR.