By Brian Christian of Atlantic Magazine:

In the race to build computers that can think like humans, the proving ground is the Turing Test—an annual battle between the world’s most advanced artificial-intelligence programs and ordinary people. The objective? To find out whether a computer can act “more human” than a person. In his own quest to beat the machines, the author discovers that the march of technology isn’t just changing how we live, it’s raising new questions about what it means to be human.

BRIGHTON, ENGLAND, SEPTEMBER 2009. I wake up in a hotel room 5,000 miles from my home in Seattle. After breakfast, I step out into the salty air and walk the coastline of the country that invented my language, though I find I can’t understand a good portion of the signs I pass on my way—LET AGREED, one says, prominently, in large print, and it means nothing to me.

I pause, and stare dumbly at the sea for a moment, parsing and reparsing the sign. Normally these kinds of linguistic curiosities and cultural gaps intrigue me; today, though, they are mostly a cause for concern. In two hours, I will sit down at a computer and have a series of five-minute instant-message chats with several strangers. At the other end of these chats will be a psychologist, a linguist, a computer scientist, and the host of a popular British technology show. Together they form a judging panel, evaluating my ability to do one of the strangest things I’ve ever been asked to do.

I must convince them that I’m human.

Fortunately, I am human; unfortunately, it’s not clear how much that will help.

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To see if you can outwit a computer at Paper-Scissors-Rock, check out this interactive feature in the New York Times. The feature demonstrates basic artificial intelligence, and allows you to play against the computer at two different levels: novice, where the computer learns from scratch; and veteran, where the computer uses over 200,000 rounds of experience against you.

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From the Globe and Mail:

Geoffrey Hinton, a pioneer in artificial intelligence, was awarded the country’s top science prize last week, the prestigious Gerhard Herzberg Canada Gold Medal. The prize by the Natural Sciences and Engineering Research Council comes with a guarantee of $1-million in funding over five years. The University of Toronto researcher spoke with Anne McIlroy on his efforts to get computers to learn the way humans do.

Last week, an IBM computer named Watson bested humans on the television program Jeopardy!. Who were you rooting for?

Watson.

Why?

Well, it is an example of artificial intelligence. That’s the field I’m in, so it is nice to see progress.

How is Watson different than the kind of artificial intelligence you are working on?

There are two main ways. The first is, we want to do a lot more by learning and a lot less by less by hand programming. Watson was a mixture.

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From The Dana Foundation:

Editor’s note: The goal of computational neuroscience is to understand the brain and its mechanisms well enough to artificially simulate their functions. In some areas, like hearing, vision, and prosthetics, there have been great advances in the field. Yet there is still much about the brain that is unknown and therefore cannot be artificially replicated: How does the brain use language, make complex associations, or organize learned experiences? Once the neural pathways responsible for these and many other functions are fully understood and reconstructed, researchers will have the ability to build systems that can match—and maybe even exceed—the brain’s capabilities.

“If I cannot build it, I do not understand it.” So said Nobel laureate Richard Feynman, and by his metric, we understand a bit about physics, less about chemistry, and almost nothing about biology.¹

When we fully understand a phenomenon, we can specify its entire sequence of events, causes, and effects so completely that it is possible to fully simulate it, with all its internal mechanisms intact. Achieving that level of understanding is rare. It is commensurate with constructing a full design for a machine that could serve as a stand-in for the thing being studied.  To understand a phenomenon sufficiently to fully simulate it is to understand it computationally.

“Computation” does not refer to computers per se; rather it refers to the underlying principles and methods that make them work. As Turing Award recipient Edsger Dijkstra said, computational science “is no more about computers than astronomy is about telescopes.”² Computational science is the study of the hidden rules underlying complex phenomena from physics to psychology.

Computational neuroscience, then, has the aim of understanding brains sufficiently well to be able to simulate their functions, thereby subsuming the twin goals of science and engineering: deeply understanding the inner workings of our brains, and being able to construct simulacra of them. As simple robots today substitute for human physical abilities, in settings from factories to hospitals, so brain engineering will construct stand-ins for our mental abilities—and possibly even enable us to fix our brains when they break.

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Victim of the Brain is a 1988 docudrama by Dutch director Piet Hoenderdos about “the ideas of Douglas Hofstadter”. It features interviews with Douglas Hofstadter and Daniel Dennett. It has never been online before, but is now available on Google Video.

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Recently Crick and Koch offered a “Framework for Consciousness” (2003). Pradeep Mutalik’s review of that article in SCR (Mutalik 2003) asserts that “Crick and Koch describe ten aspects of a framework that they believe offers a coherent scheme for explaining the neural correlates of consciousness.”Crick and Koch explain that a framework must not be confused with a set of hypotheses. Rather a framework for A framework must not be confused with a set of hypotheses consciousness offers a point of view from which to address the problems of consciousness. It’s intended to guide research. A good framework should fit within current scientific knowledge reasonably well and should be roughly correct. It needn’t be correct in all its details, but rather should guide research to fill in and correct it details. Such frameworks have proved useful in Biology and Physics. This one can be expected to be useful in consciousness studies.

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