I like this, but I feel it's a little optimistic (or pessimistic depending on your view). Isn't asking ML researchers when AI will dominate human performance a bit like asking a barber if you need a haircut?
How does the ML researcher gain from lying "In year X" if they don't believe that to be true? It's a tenuous connection.
Perhaps the analogy works better if the barber is a friendly, honest person, who takes professional umbrage when they see other people with longer hair :)
Philip Tetlock has written on this topic for years. Two of his books are Expert Political Judgment and Superforecasting.
[1]: https://en.wikipedia.org/wiki/The_Good_Judgment_Project
Edit: So to directly answer your question, rather than AI experts, I'd prefer technology experts (AI or otherwise) with a track record of well-calibrated predictions.
I don't believe ML researchers are unqualified -- it's more of a potential incentive problem. I don't think it's unreasonable to suggest that people involved with / employed by a technology may have a tendency to exaggerate its benefits.
Ideally I'd trust the numbers here more if there was at least a cross-section of knowledgeable people being surveyed across a few different disciplines (or at least more than one).
It has less to do with title than systematized knowledge of models, but people with those titles are more likely to have invested in acquiring this knowledge and these models.