AI, computers, minds, algorithms, evolution, Dennett

If even artificial intelligence advocates have largely abandoned the idea that AI is ultimately algorithmic, it’s time to question a lot of related assumptions, some of which I already have.

First, the human mind, then, is clearly not algorithmic. And, it’s likely even less algorithmic than a computer.

Second, being “kludged” together by evolution, it’s most surely not a black box, like a modern software program, routine, or subroutine.

Third, running off that point, contra Dan Dennett, evolution is most assuredly not algorithmic, either, as I’ve said before.

Fourth, the Turing test, as stipulated by Alan Turing himself, was NOT about whether a machine could think, but about whether a machine could simulate thinking. In other words, in modern philosophy terminology, Turing was a functionalist, as is Dennett (on this issue, at least), even as he continues to deny it.

Anyway, read the full story linked above.

The computer as baseball GM

Don’t laugh.

Right now, they’re being used more and more as either assistant general manager or assistant bench manager.

On the other hand, some of the actual numbers crunching indicates they’re not being used enough. And, some folks are fine with that, like Mr. Baseball Lawyer, Tony La Russa, manager of the St. Louis Cardinals:

“There’s way too much importance given to what you can produce from a machine,” he said. “These are human beings, and I don’t think any computer is going to model that close to what we deal with at this level.”

(Tony, the puter probably doesn’t care for pitchers batting in the eight spot. Or Khalil Greene batting cleanup.)

‘Emotional’ computers improve performance

Computers that show something like “regret” can improve their performance, Italian scientists say, and so help model human behavior for research:

Davide Marchiori of the University of Trento and Massimo Warglien of Ca’ Foscari University in Venice built mathematical models based on biological neural networks. These use simulated networks of “brain cells” to arrive at decisions and learn by trial and error.

Introducing an approximation of regret allowed the models to predict human behavior more precisely than conventional economic learning theories, the researchers said. Their findings appear in the Feb. 22 issue of the research journal Science.

Will we someday remove the scare quotes from “regret”?