[1] S. Legg, M. Hutter, Universal Intelligence: A Definition of Machine Intelligence. https://arxiv.org/abs/0712.3329
Consider AI as a newly discovered species. If you were trying to discern if a previously unknown cetacean were intelligent, or if life discovered on a distant planet were intelligent, would you only say "intelligence discovered!" after it equaled-or-surpassed human performance on many or most kinds of thinking historically valued by humans? I wouldn't. I think that AI is already here and that the people waiting for artificial general intelligence will keep raising the bar and shifting the goalposts long after "boring" narrow AI has economically out-competed half the human population.
Most people will not be impressed by a machine that can master backgammon, chess and poker, despite it being a great technical feat. They would be impressed by one that can successfully teach a 5th grade math class, even though there are hundreds of thousands of people who can do this.
This would require more than teaching the kids math, but also how to deal with the kid who loses a parent during the school year. How to deal with bullying in the class, with misbehaving students. None of it is "specialized knowledge" like playing GO. And we are nowhere even remotely close to this.
There has been an uptick in people pondering the economic implications of driverless vehicles and a more robotic future. That discussion seems kind of oddly isolated from re-considering the nature of intelligence, human and otherwise. It's as if after the Industrial Revolution people kept narrowly scoping the meaning of "power" to "muscle power" rather than acknowledging mechanical forms. Oh, yes, that coal fired pump can remove water from the mine faster than I can... but it just uses clever tricks for faking power.
Woah wait what? Non-human animals successfully navigate >7 miles of mountain terrain all the time.
Machine intelligence doesn't seem like "real" intelligence because it just doesn't seem as generalizable. Taking the engines and hydraulics used to great effect in water pumps and applying them to construction cranes required engineering work, sure, but no new physics. But you can't just take the convolutional neural nets that are breaking new ground in computer vision and apply them to natural language processing, you need new computer science research to develop long short-term memory networks.
The cool thing about AlphaGo, from my understanding, was that it was able to train the deep learning-based heuristics for board evaluation by playing a ton of games against itself. This is especially awesome because those heuristics are (were?) our main edge over machines [1]. But in CV and NLP, playing against yourself isn't really a thing, so again, this work doesn't automatically generalize the way engines and hydraulics did.
From the other end, the merits of production AI will be measured against isolated properties pulled out of the intellgence black-box, and since intelligence remains undefined (in a strict ontological sense), debate ensues.
I believe cognitive scientists have a considerably better idea than that.
When I said "make a big fuss" i didn't mean "herald it as the gold standard", but they do go on about it even though they might disagree about what it utlimately signifies.
A tardigrade achieves its goals in a wide range of environments; I don't think anyone would call it intelligent. I've known quite a few 15-year-old juvenile delinquents that I'm certain were able to achieve their goals in a much wider range of environments than Albert Einstein; were they all much more intelligent than Einstein?
> But it is a great step towards AI.
How do you know how big a step it is? None of our learning algorithms has yet to achieve even an insect's level of intelligence (which would be normally considered zero or close to it). How do you know we're even on the right path? I mean, I have no real reason to doubt that we'll get AI sometime in the future, but the belief -- certainty even -- that AI is imminent has been with us for about sixty years now.
Also, if intelligence means "achieving goals in a wide range of environments", then I think some computer viruses are far more intelligent -- by this definition -- than even the most advanced machine-learning software to date.