# Can an AI be creative?

Go back to [[Week 4 - Introduction]] or see [[Autogeneration of news content]]

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## Mark Sagar on BabyX and creating life-like animations

**Your work has often stood at the intersection of creativity and science. Do you think machines can someday be taught to be innately creative?**

Yes, I do. We want to start exploring what may be the motivating systems with the version of BabyX under development. I think creativity play is key to exploration and discovery, so making an AI machine play and be naturally curious is key. Beauty is a really interesting question, but I think it—partially, at least—comes down to harmony and clarity and resonance in stimuli which have or suggest biological value. For example, we seem to be innately rewarded to seek harmony in nature—it resonates with our evolutionarily refined pleasure circuits—so we seek beauty. So does this mean we need to bootstrap this at the core of our AI? Or is it something that emerges? But what a wonderful question to explore.

- Quote has implications for the question, "Could an AI ever compete with a journalist's creativity?"

What’s next for AI - Mark Sagar. (2015, September 11). IBM Cognitive Advantage Reports. http://www.ibm.com/watson/advantage-reports/future-of-artificial-intelligence/mark-sagar.html


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##  Yoshua Bengio on how long until elements of AI will be ready

We’ll probably see systems that can understand and do a good job at generating natural language ready within the next five years, while deep unsupervised learning is likely to be farther out. That will take many years of patient, fundamental research.

What’s next for AI - Yoshua Bengio. (2015, September 11). IBM Cognitive Advantage Reports. http://www.ibm.com/watson/advantage-reports/future-of-artificial-intelligence/yoshua-bengio.html

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## Margaret Boden on AI's relationship to creativity

**Creativity has been a major interest of yours. Do you see AI as a means of unleashing creativity or as a way of enabling us to understand human creativity?**

I’m interested in how computational technology can help us understand human creativity. Many examples of creativity involve learning and exploring in a hierarchical style. Neural and multilayer network systems can help us construct different frameworks to better understand those hierarchies, but there’s much more to learn and discover. If you have a computer that comes up with random combinations of musical notes, most of that stuff will be utterly uninteresting rubbish, but some of it will not be. A human being who has sufficient insight and time could well pick up an idea or two. A gifted artist, on the other hand, might hear the same random compilation and come away with a completely novel idea, one that sparks a totally new form of composition. That’s a very different type of creativity. About 95% of what professional artists and scientists do is either exploratory or combinational, and the other 5% is transformational creativity. At the moment, we don’t really have a good understanding of these processes. That’s where AI has the potential to play a powerful role.

Also see [[We just don't understand understanding]]

What’s next for AI - Margaret Boden. (2015, September 11). IBM Cognitive Advantage Reports. http://www.ibm.com/watson/advantage-reports/future-of-artificial-intelligence/margaret-boden.html