Computational evolutionary art has been an active practice for at least 20 years. Given the remarkable advances in that time in other realms of computing, including other forms of evolutionary computing, for many a vague feeling of disappointment surrounds evolutionary art. Aesthetic improvement in evolutionary art has been slow, and typically achieved in ways that are not widely generalizable or extensible. So what is the problem with evolutionary art? And, frankly, why isn’t it better? In this paper I respond to these questions from my point of view as a practicing artist applying both a technical and art theoretical understanding of evolutionary art. First the lack of robust fitness functions is considered with particular attention to the problem of computational aesthetic evaluation. Next the issue of genetic representation is discussed in the context of complexity and emergence. And finally, and perhaps most importantly, the need for art theory around evolutionary and generative...