11:00 — 11:50am, August 05 [Zoom Room]

Session Chair: Sato Hiroyuki, University of Tokyo, Japan
Title: Artificial Creativity Vs Artificial Intelligence

Speaker: Prof. Hongji Yang

Professor Hongji Yang

Prof. HONGJI YANG received the B.Sc. and M.Sc. degrees in computer science from the Jilin University, China in 1982 and 1985, respectively, and the Ph.D. degree in computer science from Durham University, UK in 1994. He was a faculty member at Jilin University, China in 1985, at De Montfort University, UK in 1993, and at Bath Spa University, UK in 2013. Currently, Dr. Yang is a professor at School of Informatics at the University of Leicester, UK. He has published over 400 refereed journal and conference papers. His research interests include software engineering, creative computing, internet computing. He became IEEE Computer Society Golden Core member in 2010. He is a member of EPSRC Peer Review College since 2003 and the editor in chief of International Journal of Creative Computing.

Abstract:

The term of artificial creativity has been around for some time. Wikipedia suggested that it means the same as computational creativity, mechanical creativity, creative computing or creative computation, though its neutrality was declared to be disputed. Following the way of understanding the term of “artificial intelligence”, it is expected that products/outputs/results generated by artificial creativity will be useful to society. If so, what is the difference between artificial creativity and artificial intelligence? If not so, i.e., a possible reason can be that artificial creativity does always produce useful products/outputs/results while artificial intelligence does not, how to define artificial creativity? And ultimately, how to achieve artificial creativity?

Attempts have been made to approach the above issues in recent years from the angle of whether artificial creativity can be a separate discipline from artificial intelligence. Relevant thoughts have been summarised and are to be shared here. These include how observations and experiments were conducted, what possible theoretical supports could be obtained from other knowledge disciplines, whether new processes of completing tasks were regarded as creative outputs, how and what types of rules and algorithms could be developed, what example applications were and what speculations are made for future research.