It’s an interesting methodology, but the Maes-Garreau data is just terrible quality. For every person I know on that list, the attached point estimate is misleading to grossly misleading. For instance, it gives Nick Bostrom as predicting a Singularity in 2004, when Bostrom actually gives a broad probability distribution over the 21st century, with much probability mass beyond it as well. 2004 is in no way a good representative statistic of that distribution, and someone who had read his papers on the subject or emailed him could easily find that out. The Yudkowsky number was the low end of a range (if I say that between 100 and 500 people were at an event, that’s not the same thing as an estimate of 100 people!), and subsequently disavowed in favor of a broader probability distribution regardless. Marvin Minsky is listed as predicting 2070, when he has also given an estimate of most likely “5 to 500” years, and this treatment is inconsistent with the treatment of the previous two estimates. Robin Hanson’s name is spelled incorrectly, and the figure beside his name is grossly unrepresentative of his writing on the subject (available for free on his website for the ‘researcher’ to look at). The listing for Kurzweil gives 2045, which is when Kurzweil expects a Singularity, as he defines it (meaning just an arbitrary benchmark for total computing power), but in his books he suggests that human brain emulation and life extension technology will be available in the previous decade, which would be the “living long enough to live a lot longer” break-even point if he were right about that.
I’m not sure about the others on that list, but given the quality of the observed date, I don’t place much faith in the dataset as a whole. It also seems strangely sparse: where is Turing, or I.J. Good? Dan Dennett, Stephen Hawking, Richard Dawkins, Doug Hofstadter, Martin Rees, and many other luminaries are on record in predicting the eventual creation of superintelligent AI with long time-scales well after their actuarially predicted deaths. I think this search failed to pick up anyone using equivalent language in place of the term ‘Singularity,’ and was skewed as a result. Also, people who think that a technological singularity or the like will probably not occur for over 100 years are less likely to think it an important issue to talk about right now, and so are less likely to appear in a group selected by looking for attention-grabbing pronouncements.
A serious attempt at this analysis would aim at the following:
1) Not using point estimates, which can’t do justice to a probability distribution. Give a survey that lets people assign their probability mass to different periods, or at least specifically ask for an interval, e.g. 80% confidence that an intelligence explosion will have begun/been completed after X but before Y.
2) Emailing the survey to living people to get their actual estimates.
3) Surveying a group identified via some other criterion (like knowledge of AI, note that participants at the AI@50 conference were electronically surveyed on timelines to human-level AI) to reduce selection effects.
It’s an interesting methodology, but the Maes-Garreau data is just terrible quality.
See, this is the sort of response I would expect: a possible bias is identified, some basic data is collected which suggests that it’s plausible, and then we begin a more thorough inspection. Complete silence, though, was not.
where is Turing
Turing would be hard to do. He predicts in 1950 a machine could pass his test 70% of the time in another 50 years (2000; Turing was born 1912, so he would’ve been 88), and that this would be as good as a real mind. But is this a date for the Singularity or a genuine consciousness?
Yes, I considered that ambiguity, and certainly you couldn’t send him a survey. But it gives a lower bound, and Turing does talk about machines equaling or exceeding human capacities across the board.
Hm. Would it be justifiable to extrapolate Turing’s predictions? Because we know that he was off by at least a decade on just the AI; presumably any Singularity would be have to be that much or more.
It’s an interesting methodology, but the Maes-Garreau data is just terrible quality. For every person I know on that list, the attached point estimate is misleading to grossly misleading. For instance, it gives Nick Bostrom as predicting a Singularity in 2004, when Bostrom actually gives a broad probability distribution over the 21st century, with much probability mass beyond it as well. 2004 is in no way a good representative statistic of that distribution, and someone who had read his papers on the subject or emailed him could easily find that out. The Yudkowsky number was the low end of a range (if I say that between 100 and 500 people were at an event, that’s not the same thing as an estimate of 100 people!), and subsequently disavowed in favor of a broader probability distribution regardless. Marvin Minsky is listed as predicting 2070, when he has also given an estimate of most likely “5 to 500” years, and this treatment is inconsistent with the treatment of the previous two estimates. Robin Hanson’s name is spelled incorrectly, and the figure beside his name is grossly unrepresentative of his writing on the subject (available for free on his website for the ‘researcher’ to look at). The listing for Kurzweil gives 2045, which is when Kurzweil expects a Singularity, as he defines it (meaning just an arbitrary benchmark for total computing power), but in his books he suggests that human brain emulation and life extension technology will be available in the previous decade, which would be the “living long enough to live a lot longer” break-even point if he were right about that.
I’m not sure about the others on that list, but given the quality of the observed date, I don’t place much faith in the dataset as a whole. It also seems strangely sparse: where is Turing, or I.J. Good? Dan Dennett, Stephen Hawking, Richard Dawkins, Doug Hofstadter, Martin Rees, and many other luminaries are on record in predicting the eventual creation of superintelligent AI with long time-scales well after their actuarially predicted deaths. I think this search failed to pick up anyone using equivalent language in place of the term ‘Singularity,’ and was skewed as a result. Also, people who think that a technological singularity or the like will probably not occur for over 100 years are less likely to think it an important issue to talk about right now, and so are less likely to appear in a group selected by looking for attention-grabbing pronouncements.
A serious attempt at this analysis would aim at the following:
1) Not using point estimates, which can’t do justice to a probability distribution. Give a survey that lets people assign their probability mass to different periods, or at least specifically ask for an interval, e.g. 80% confidence that an intelligence explosion will have begun/been completed after X but before Y.
2) Emailing the survey to living people to get their actual estimates.
3) Surveying a group identified via some other criterion (like knowledge of AI, note that participants at the AI@50 conference were electronically surveyed on timelines to human-level AI) to reduce selection effects.
See, this is the sort of response I would expect: a possible bias is identified, some basic data is collected which suggests that it’s plausible, and then we begin a more thorough inspection. Complete silence, though, was not.
Turing would be hard to do. He predicts in 1950 a machine could pass his test 70% of the time in another 50 years (2000; Turing was born 1912, so he would’ve been 88), and that this would be as good as a real mind. But is this a date for the Singularity or a genuine consciousness?
Yes, I considered that ambiguity, and certainly you couldn’t send him a survey. But it gives a lower bound, and Turing does talk about machines equaling or exceeding human capacities across the board.
Hm. Would it be justifiable to extrapolate Turing’s predictions? Because we know that he was off by at least a decade on just the AI; presumably any Singularity would be have to be that much or more.