Yes, I think this kind of requirement would lead us to a very interesting specification exercise which would address questions like:
(1) what are the different use cases relevant to identifying 'as yet unaddressed' programming language design issues?
(2) what are the 'success metrics' of a new language design?
(3) what are the 'unresolved shortcomings' of existing languages?
(4) What are the issues related to 'non-human language design'?
This last question is kind of about the opposite to 'readability as we know it', where you could anticipate a language suited to creating non-human-intelligible code, which might require tools to translate it into human intelligible form, kind of like the assembly-language to higher-level language issue but kind of in reverse.
Then how would you train that - show it what computer languages have come before, would it weight it upon how well they are used to get an idea of what humans prefer - the prospects of some java-C-Cobol mutant language do seem a logical output perhaps.
Area's in which I'd like to see AI focus would be - optimisation and code auditing. Which may well prove easier as you have a solid defined goal. Also such endeavours would prove invaluable down the line if you wanted to have AI come up with a programming language. As to do that you would need to train how humans communicate/think and how computers communicate/think and meet in the middle.
[EDIT - spelongs]