As soon as we get an AI doing something that was previously considered intelligent that task is retroactively relabeled as not really requiring intelligence, and consequently "Real AI" remains out of reach.

Personally, I believe there's a tipping point where our society will no longer be able to live in denial that we've built AI. We're not there yet since there are still a huge number of things people can do that computers can't. For example, no AI has really passed the Turing Test yet. So pretty obviously, we don't yet have "Real AI", and I understand the AI Effect, even though it's unfortunate.

But surely, there's a point where it'll be blindingly obvious that our machines are intelligent?

Name something that "humans can do that computers can't", and I bet I'll find you a human person that can't do it either.

For example, at a previous job we wanted to introduce cognitive captchas to avoid accessibility issues with visual ones. We were told we couldn't do that because some of our target audience had learning difficulties and would not be able to pass them. (Coincidentally, there was HN post the other day about how Wolfram Alpha can pass a good proportion of captchas similar to what we had planned to use)

Advances in natural language processing, metaheuristics and machine learning, as examples, are clearly steps toward the "holy grail" but to the average person it is nigh meaningless.

Lay people think AI means something like artificial intuition. Which is very hard and can only be done poorly within narrow domains.

This heralds the relatively-recent arrival of advanced statistics to the college basketball world - rebounding percentages, scoring percentages, runs -- these are pieces of information anyone could glean by simply looking at a box score, or, at worst, looking at a site with advanced metrics like www.kenpomeroy.com.

All of the game recaps read basically the same - a sure sign of a homogenous data set combined with some fairly crafty name-replacement.

Perhaps this could replace the AP game recaps, but anything beyond that is still far beyond our AI reach.

The next step is pretty obvious: Use voice recognition software to analyze the remarks made by the announcers over the course of the game and blend that into the reporting. If you can properly analyze inflection and special events from the speech of the live game you can add game highlights to the article.

EDIT: what i really mean is that I reject the strong/weak AI dichotomy. I really need to resist the urge to play pointless semantic games. Guess thats an occupational hazard of programming all day long.

Just a random thought, but even if all of our weak AI systems don't directly result in us being able to build a strong AI, maybe they will do so indirectly. We might be able to use all of these weak AI systems to train a more general-purpose strong AI system.