Even though Kurzweil was some way off, not just quantitatively but also in the way he imagined change taking place, he is right in principle that there is no existential force-field separating artistic behaviour from any other kind of human activity, that would place it out of reach for AI.
The artless robot is a myth begging to be disproved.
On the other end of the scale, IBM’s “learning program” Watson is benefiting universities and life insurers, and the discussion has broadened beyond Skynet scenarios, serious though they are.
A host of utopian and dystopian scenarios are coming into view as our understanding grows.
Another popular expectation of computational creativity is that it might make art production available to all, not just a trained “elite”, by reducing the barrier to entry to zero. This may be a meaningful objective in some sense, particularly in the case of assistive technologies for the disabled, or rapid access to free content in a commercial world that seeks to push every efficiency to its limit (as any screen composer will know).
In the general sense that it makes making art more accessible, this is perhaps an evasive goal: it has always been the case that we can all enjoy amateur art-making.
Programs like Melomics use AI techniques to mass produce copyright-free music on demand for commercial applications.
AI techniques are also being used to support, for example, the adapting of musical content to on-screen or in-game scenarios, and indeed in the context of video games and interactive TV, such automation can even be seen as a necessity, not a luxury, if the entire process is generative and can’t be entirely pre-prepared.
Even if it was simple, art is such a socially embedded thing that there is questionable power in framing the challenge just in terms of individual minds.
Cultural dynamics count a great deal, and these are poorly understood; computational creativity is indeed an ill-defined and scarily multidisciplinary subject with a monumental task ahead of it.