Okay, so here I took the the predicted date for AI, and from that I subtracted expected year of death for a person. So if they predict that AI will be created 20 years before their death, this comes out as -20, and if they say it will be created 20 years after their death, 20.

This had the minor issue that I was assuming everyone's life expectancy to be 80, but some people lived to make predictions after that age. That wasn't an issue in just calculating true/false values for "will this event happen during one's lifetime", but here it was. So I redefined life expectancy to be 80 years if the person is at most 80 years old, or X years if the person is X years old. That's somewhat ugly, but aside for actually looking up actuarial statistics for each age and year separately, I don't know of a better solution.

These are the values of that calculation. I used only the data with multiple predictions by the same people eliminated, as doing otherwise would give an undue emphasis on a very small number of individuals and the dataset is small enough as it is:

-41, -41, -39, -28, -26, -24, -20, -18, -12, -10, -10, -9, -8, -8, -7, -5, 0, 0, 2, 3, 3, 8, 9, 11, 16, 19, 20, 30, 34, 51, 51, 52, 59, 75, 82, 96, 184.

Eyeballing that, looks pretty evenly distributed to me. Also, here's a scatterplot of age of predictor vs. time to AI: http://kajsotala.fi/Random/ScatterAgeToAI.jpg

And here's age of predictor vs. the (prediction-lifetime) figure, showing that younger people are more likely to predict AI within their lifetimes, which makes sense: http://kajsotala.fi/Random/ScatterAgeToPredictionLifetime.jpg