[willsewell]

How long is not "anytime soon"?

Quoting from the excellent "Wait But Why?" blog post The AI Revolution: Our Immortality or Extinction (http://waitbutwhy.com/2015/01/artificial-intelligence-revolu...):

> In 2013, Vincent C. Müller and Nick Bostrom conducted a survey that asked hundreds of AI experts at a series of conferences the following question: “For the purposes of this question, assume that human scientific activity continues without major negative disruption. By what year would you see a (10% / 50% / 90%) probability for such [Human-Level Machine Intelligence] to exist?” It asked them to name an optimistic year (one in which they believe there’s a 10% chance we’ll have AGI), a realistic guess (a year they believe there’s a 50% chance of AGI—i.e. after that year they think it’s more likely than not that we’ll have AGI), and a safe guess (the earliest year by which they can say with 90% certainty we’ll have AGI). Gathered together as one data set, here were the results:

  > Median optimistic year (10% likelihood): 2022
  > Median realistic year (50% likelihood): 2040
  > Median pessimistic year (90% likelihood): 2075

> So the median participant thinks it’s more likely than not that we’ll have AGI 25 years from now. The 90% median answer of 2075 means that if you’re a teenager right now, the median respondent, along with over half of the group of AI experts, is almost certain AGI will happen within your lifetime.

> A separate study, conducted recently by author James Barrat at Ben Goertzel’s annual AGI Conference, did away with percentages and simply asked when participants thought AGI [Artificial General Intelligence] would be achieved—by 2030, by 2050, by 2100, after 2100, or never. The results:

  > By 2030: 42% of respondents
  > By 2050: 25%
  > By 2100: 20%
  > After 2100: 10%
  > Never: 2%

This might be longer than "anytime soon". But when I read it (as a layperson), I was surprised how relatively first these experts believed it would happen.

[Berobero]

Counterpoint: this article (https://pdfs.semanticscholar.org/5a12/80f783e4ce6ba31b821f4d...)...

TL;DR: Experts have a poor track record for predicting AI development, they aren't particularly qualitatively different in their predictions from non-experts, and "15-25 years" has been a staple prediction for decades now.

[tim333]

Counter-counterpoint - Kurzweil's project Moore's law technique predicted computers being chess champ within a year of the event and has predicted passing the Turing test for 2029 for ages now, which I guess if roughly equivalent to general intelligence.

[argonaut]

There is a certain irony in saying we should believe in Kurzweil just because his n=1 predictions came true.

(Statisticians often deride machine learning people for having a poor understanding of statistics).

[tim333]

There's more to the Moore's law argument than the one prediction from Kurzweil. For example there's Hans Moravec's essay from 97 predicting "the required hardware will be available in cheap machines in the 2020s" and I remember writing about the stuff for my uni entrance exam in 1981 before I'd heard of Kurzweil or Moravec. The basic idea is that when brain equivalent hardware is available cheaply so hackers can hack on it, the software will follow not long after if not before. Given the recent progress and the sheer number of talented people flooding into AI research that seems quite likely to me.

[AJ007]

Big questions to me are -

a) What is the computational power required? (stuff figured out back in the 80s turned out to work well for deep learning, but it took another two decades until the power was there at an economical price.)

b) What kind of mistakes do human-like thinking machine make? Additionally, are those mistakes actually a fundamental piece of general intelligence?

Some of the core pieces to general intelligence may be solved soon, but it could take a long time for the economics to become compelling or even possible. Presumably you can collapse time by throwing more resources at an "AI", but humans, with their brains running more or less 24/7 take many years before they can start producing really valuable work. We have assumed you can preload an "AI" with concepts or just copy and paste, but this might magnifying weaknesses just as if every employee at Google was a copy of Sergey Brin.

I except we will start seeing things, very soon, that begins to look very much like general intelligence, but the hardware limits will be an issue.

[denzil_correa]

> But when I read it (as a layperson), I was surprised how relatively first these experts believed it would happen

Remember, the same experts predicted flying cars in the 1960s. We are yet to have self driving cars.