AI: A Conceptual Problem

AI is really a conceptual problem.

What is "human intelligence"? I think for most people it's a fuzzy concept combining self-awareness, reasoning, information processing, problem solving, symbol manipulation, insight, etc. In other words, not clear enough to make good sense when thinking about machine intelligence.

What is "thinking"? ChatGPT seems to think, but all it does it string together words and phrases and sentences, based on some probabilities that were calculated during its training. I've tried it several times, and what I notice about it is that it uses vast amounts of cliche. Which is not at all surprising, since cliches by definition are more likely to occur in text than original tropes. Its output makes sense, but it's yawn-inducing boring.

On the other hand, I think all those processes, plus processes not yet understood or recognised, are necessary for sentience and self awareness. Will machines get there? Maybe. The real danger is that we will confuse their making sense with wisdom, and rely on them to do things only humans should do. Such a judge guilt and innocence.

Footnote: The most common imagery of robots shows them as humanoid. But all robots currently at work are machines that look nothing like human beings. They're basically arms.

Artificial Intelligence: a few musings

2005-06-20
“If it looks like a duck, and walks like a duck, and quacks like a duck, then it’s a duck” (Ancient wisdom)

Unless it’s a model of a duck.

Artificial Intelligence is model building – we want autonomous machines, but the best we can do is build models of autonomous machines.

Eg, an artificial ant – could be made to behave like an ant in many ways, but not as an ant in an anthill, or capable of making more ants.

2015-10-21
It’s probably possible to make an artificial ant that behaves like an ant in anthill. We may even be able to make an artificial ant that can reproduce in some way.

However, “behave like an ant” is not well defined. There are too many behaviours, and some are obviously easier to mimic than others. Nevertheless, it will soon be possible to make an ant-size robot that can navigate like an ant, climb vertical surfaces like an ant, etc.

But it will always be a model of ant, and therefore its behaviour will in some respect will not be antlike, and in other respects will be a bad imitation of ant behaviour. That’s simply the nature of models.

2016-05-15
Intelligence is even less well-defined than “ant behaviour”. We can mimic some intelligent behaviours, eg, sorting, learning correlations, recognising patterns, and so on, which are useful to augment human tasks such as diagnosis of a fault or illness, or finding the data we want. If a task is well enough defined, we can build a machine to do it.

But that’s the problem: “Intelligence” is simply not well enough defined. My notion of it is the ability to apply and adapt existing knowledge and insight to unanticipated problems. Every term in that definition is fuzzy and vague. Anyhow, some people (including me) would argue it’s more of a definition of creativity than intelligence.

Is consciousness part of  “intelligence”? Many people would say it is. A machine that merely solves problems isn’t intelligent, it’s just an algorithm. It’s not enough to know how to do long division, you have to be able to recognise when and why you should do it. And that you are doing it.

“Understanding” is another component of intelligence. Isn’t it? Well, it does have something to do with learning: an intelligent person is one who can make sense of new explanations. “I don’t get it” at one extreme means “I haven’t figured it out yet”, at the other it means “I can’t figure it out”. The latter is a measure of intelligence.

And that’s just three attempts to make sense of “intelligence”. We’re long way from knowing exactly what we mean by “artificial intelligence”. Far enough that we may not even recognise it when we see it.