Theoretical Issues
As measured by the amount of activity in the field (e.g., publications, conferences and workshops), computational creativity is a growing area of research. But the field is still hampered by a number of fundamental problems:
- Creativity is very difficult, perhaps even impossible, to define in objective terms.
- Creativity takes many forms in human activity, some eminent (meaning "recognized" or "ingenious", e.g., Einstein's creativity; sometimes referred to as "Creativity" with a capital C) and some mundane.
- Creativity can mean different things in different contexts: Is it a state of mind, a talent or ability, or a process? Does it describe a person, an activity or an end-product? Can collaborative work in which exceptional products emerge from simple interactions be considered creative?
These are problems that complicate the study of creativity in general, but certain problems attach themselves specifically to computational creativity:
- Can creativity be hard-wired? In existing systems to which creativity is attributed, is the creativity that of the system or that of the system's programmer or designer?
- How do we evaluate computational creativity? What counts as creativity in a computational system? Are natural language generation systems creative? Are machine translation systems creative? What distinguishes research in computational creativity from research in artificial intelligence generally?
- If eminent creativity is about rule-breaking or the disavowal of convention, how is it possible for an algorithmic system to be creative? In essence, this is a variant of the Ada Lovelace objection to machine intelligence, as recapitulated by modern theorists such as Teresa Amabile: If a machine can do only what it was programmed to do, how can its behavior ever be called creative?
Read more about this topic: Computational Creativity
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