Computational Creativity

In Computational Creativity research, we study how to engineer software which can take on creative responsibilities in arts and science projects. At the heart of most creative systems is a generative engine, and constructive machine learning has the potential to drive forward Computational Creativity research with new generative processes and the production of new cultural artifacts such as paintings and musical compositions. In an effort to help the emerging field of constructive machine learning to fast-track to having cultural (as well as scientific) impact, in the talk, I’ll describe some of the practical projects I’ve been involved with and what lessons I’ve learned about the value of creative software in society at large. I’ll describe some foundational philosophical issues that have arise in the field over recent years, and discuss how we’ve addressed these issues to make scientific progress, but also to lay the groundwork for creative software to have an important and lasting impact in certain cultural spheres.