Abeba Birhane has written an excellent historical overview of the original Artificial Intelligence movement, including Weizenbaum’s aboutface, and the current continuation of technological determinism.
Writing, both code and prose, for me, is both an end product and an end in itself. I don’t want to automate away the things that give me joy.
And that is something that I’m more and more aware of as I get older – sources of joy. It’s good to diversify them, to keep track of them, because it’s way too easy to run out. Or to end up with just one, and then lose it.
The thing about luddites is that they make good punchlines, but they were all people.
AI becomes a stand-in term for whatever technologies and techniques are new, shiny, and just beyond the grasp of our understanding. We use it to gesture at a future we cannot fully comprehend or currently realise. As soon as we do, it will no longer be “AI.”
In this piece published a year ago, Ted Chiang pours cold water on the idea of a bootstrapping singularity.
How much can you optimize for generality? To what extent can you simultaneously optimize a system for every possible situation, including situations never encountered before? Presumably, some improvement is possible, but the idea of an intelligence explosion implies that there is essentially no limit to the extent of optimization that can be achieved. This is a very strong claim. If someone is asserting that infinite optimization for generality is possible, I’d like to see some arguments besides citing examples of optimization for specialized tasks.
Whatever the merit of the scientific aspirations originally encompassed by the term “artificial intelligence,” it’s a phrase that now functions in the vernacular primarily to obfuscate, alienate, and glamorize.
Do “cloud” next!
A terrific cautionary look at the history of machine learning and artificial intelligence from the new laugh-a-minute book by James.
Seminal technology.
Revisiting Spielberg’s films after a decade and a half.