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new developments in AI

sgs | academic,AI,review | Saturday, July 3rd, 2010

Thanks to popular culture, we have a good idea of what to expect when “strong” AI arrives. Machines attain consciousness? Prepare to be harvested as food. Detroit introduces talking cars? “Hello, Kit“.

What to expect in the near-term is less clear. While strong AI still lies safely beyond the Maes-Garreau horizon1 (a vanishing point, perpetually fifty years ahead) a host of important new developments in weak AI are poised to be commercialized in the next few years. But because these developments are a paradoxical mix of intelligence and stupidity, they defy simple forecasts, they resist hype. They are not unambiguously better, cheaper, or faster. They are something new.

What are the implications of a car that adjusts its speed to avoid collisions … but occasionally mistakes the guardrail along a sharp curve as an oncoming obstacle and slams on the brakes? What will it mean when our computers know everything — every single fact, the entirety of human knowledge — but can only reason at the level of a cockroach?

I mention these specific examples — smart cars and massive knowledge-bases — because they came up repeatedly in my recent conversations with AI researchers. These experts expressed little doubt that both technologies will reach the market far sooner, and penetrate it more pervasively, than most people realize.

But confidence to the point of arrogance is practically a degree requirement for computer scientists. Which, actually, is another reason why these particular developments caught my interest: for all their confidence about the technologies per se, every researcher I spoke to admitted they had no clue – but were intensely curious – how these developments will affect society.

Taking that as a signal these technologies are worth understanding I started to do some digging. While I am still a long way from any answers, I think I’ve honed in on some of the critical questions.

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group think

sgs | academic | Friday, April 4th, 2008

Spring is here, and with spring comes:  sunshine, fresh flowers, … and a slew of navel-gazing, big-idea technology conferences. I recently returned from two such trend-spotting confabs: CI Foo Camp and ETech.

In format, the events were completely different. CI Foo Camp, organized by Google’s Chief Economist Hal Varian and held on the Google campus, brought together 60 or so researchers all loosely connected to the idea of “collective intelligence” for a wide-ranging discussion with no set schedule. For ETech, O’Reilly’s flagship annual conference, several hundred hackers, academics, and online gadflies converged on San Diego for four days of presentations about anything deemed an emerging technology.

But what I distilled from the two conferences was very similar—the same topic kept coming up, over and over.  This emerging area doesn’t have a catchy moniker yet, but you can think of it as an amalgamation of crowd theory, human terrain mapping, and social simulation. It is the science of groups; it is a new kind of quantitative political science.

The tools and theories needed to analyze social interactions are just now reaching the level of sophistication — in accuracy, in robustness – necessary to leave the lab and enter commercial duty. We are in a period analogous to the early 1970s, when developments like the Capital Asset Pricing Model and the Black-Scholes equation transformed finance, changing it from an art to a science, and opening enormous new markets in the process. Now, new equations describing “crowd dynamics” are about to change our lives. And not always for the better. This is one of the most significant technology trends I have seen in years; it may also be one of the most pernicious.

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