faith in AI

June 22, 2009

Namit Arora at 3quarksdaily has a very interesting and thoughtful post about the future (or lack thereof) of true artificial intelligence.

He does a good job at tracing the major phases of AI design, from essentially large databases to the more modern neural networks. He points out that while AIs have become more and more capable of solving well-defined problems (although one could argue we’ve been able to expend the set of solvable well-defined problems a great deal over the years), ultimately they will fail to reach the truly human je ne sais quoi because they are unable to become completely immersed in the human experience of emotions, relationships, and even simple relationships between objects and things in our world. (Arora borrows much of these ideas, which I am only briefly paraphrasing, from Hubert L. Dreyfus who borrows from Heidegger.)

While I agree that we are no where near the singularity, as Ray Kurzweil would have you believe, I disagree that we are no where nearer than when we started in the early days of artificial intelligence (that is, the 60s and 70s).

A big shift in the development of AI, in my opinion, was moving away from the teleological view of intelligence, away from “This is how we think the mind works, so this is how we’re going to program our AI.” The transition from symbolic (brute force) AI to neural networks marks a large shift in that it’s basically an acknowledgement that we programmers don’t know how to solve every problem. Now, what we still know how to do (and must do for now at least) is to define our problems. Thus, if I make an AI to solve a certain problem, I may run it though millions of machine-learning iterations so that it can figure out the best way to solve that problem, but I’m still defining the parameters, the heuristics that make that program determine whether the current technique it’s testing is good or not.

I agree that this approach, while yielding many powerful problem-solving applications, is ultimately doomed. But in pursuing it, we have bootstrapped ourselves into a less well-defined area of AI. If you believe (as I do, although I don’t like the religiously aspects of the word “believe”), that the brain is simply a collection of interconnected cells and nothing else, then in theory we can recreate it in silicone. The problem arises in determining how the cells (nodes in comp sci language) are interconnected. How can we even know where to start?

And here’s where the faith aspect comes in. I’ll call it what it is. As our understanding of the functional aspects of the brain improves (thanks to all the tools of modern technology) as do our computational processing and storage capabilities, I find it hard to think that we will not ultimately get there.

Yes, we will probably need a more philosophical view of what it means to be human and sentient. Yes, it will probably take us a long, long time from now, perhaps even after my lifetime, but remember, the field is incredibly new. I’m heartened by work done by Jeff Krichmar’s group at UC Irvine with neurobots in approaching the idea of intelligence from a non-bounded perspective.

As our technology and understanding of intelligence improves, I simply cannot believe (and here, perhaps, I am using a more religious flavor) that our quest to understand ourselves would allow us to abandon this project.

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