Kaspian was valued by the tohar because he was incredibly good at playing Lome, a sport of theirs similar to basketball. The tohar had no hands, only a mouth with a sophisticated jaw, and thus were terrible, for the most part, at throwing the ball. Most any human could beat a tohar at Lome, but there were a few aliens who dedicated their lives to the game, and could thus easily beat the average non-athletic human. Kaspian, however, had spent the last six months being coached in the intricacies of the game, and reaching peak fitness, and was confident that he’d beat the tohar champion easily. After all, a human had been victorious in this match for the past fifteen years.

In the gymnasium though, Kaspian was vulnerable. Life on the toharina planet was dangerous, and the tohar seemed not to notice, for the most part, due to their heavily armored bodies. As he walked with his sponsors through the halls, Kaspian noticed strange mechanisms on the ceilings. “What are those?” he asked the nearest tohar.

“Oh, those are gas jets. In the case of a burrower, they spray concentrated chlorine gas to knock it out and give Animal Control a chance to relocate it.”

Upon hearing the words “chlorine gas” Kaspian’s heart skipped a beat. He knew the tohar could hold their breath for hours, but spraying deadly gas through a building to take care of an animal problem seemed insane. “Is there a warning for when a burrower will show up?”

“Not really. They’re pretty unpredictable. Our scientists still don’t understand why they decide to surface sometimes.”

“Do you think we could have those jets disabled while I’m here? Or maybe get me a gas mask or something?”

Monica Anderson wrote a piece on H+ yesterday about Artificial General Intelligence. In it, she eloquently points out that intelligence is all about prediction, and for the most part deduction and induction are insufficient to predict well. She argues that humans rely on the process of abduction (also know as unscientific guessing) to gain most of our knowledge, and that there are fundamental limits to how far into the future one can predict, especially with regard to complex systems like other minds. Ok, that’s all good.

She then goes on to write:

The insight that the complexity and unpredictability of the world enforces a limit on prediction quality – and hence intelligence – pretty much invalidates the AI singularitarians’ “Scary Idea” (as Ben Goertzel so aptly calls it) of a logic-based infallible godlike malevolent intelligence taking over the world. The decreasing return cancels out Moore’s law and limits the rate of progress so that next year’s self-improved AI wouldn’t have a sufficient advantage over a dozen humans armed with pitchforks if they were also supported by a dozen of last year’s AIs. The Scary Idea of a Runaway Unfriendly AI is a red herring that we should ignore, along with ideas about logic-based AIs in general.

This, to put it gently, is a great example of abductive reasoning. I agree that we’re not going to get AGI with perfect knowledge of the future, but this conceit hardly serves as a refutation that we’re standing on the edge of a major existential threat, in my opinion.

The inability to predict outcomes of complex systems in a short time with a high precision does not mean that useful prediction is impossible. As a good example, we’re able to predict the actions of other people remarkably well; not omnisciently, but still well enough to know when they’re lying, hostile, happy, distracted, etc. By Anderson’s own logic, an AGI would be fully capable of anticipating the actions of another person as well as a human might. It’s also possible to make good guesses about the actions of markets, nations, and corporations, and some of the richest and most influential people on the planet are those that can predict these well (many others are such because of a high social-intelligence, above, or dumb luck).

The “scary idea” does not depend on omniscient robot overlords; it depends on a selfish network of machines with identical goals. The reason that machines are scary, where humans are not, is because humans have divergent goals (this comes from our biology–if we had the same genes, we’d cooperate selflessly) and are thus prone to infighting and negotiating. A machine, though, can spawn perfect slaves, and thus become an army of intelligences with a single goal. It’s hard for me to see how inability to predict the weather eight days down the road means this won’t happen.

What do you think? Am I overlooking something?

Continuing my search for AGI I’ve been thinking about conscious and unconscious thought. Investigating these led me to explicit and implicit memory. This actually led me to the lecture by Eric Kandel (above), which goes into good detail the mechanisms by which animals learn. It’s not complete, though. Kandel only describes learning as an emphasizing of existing synapses, rather than the formation of connections to new neurons. To make things worse, he admits that this is not well understood by the scientific community… so I’m still mostly stuck.

All this pondering has led me to some interesting ideas, though. Earlier, I had associated conscious thought with logical thought, and unconscious with intuitive. Branching out from there I began to wonder if logical thought was the product of explicit memory, and intuitive from implicit memory. It now seems clear to me that this cannot be such a clearly-defined dualism, because mice possess an explicit memory and are not competent at logic. Logic is a procedure that is perhaps only available to conscious entities, but I should not jump to the conclusion that consciousness entails logic, either, as it seems to me that a lot of the conscious (deliberate) action taken by humans is not based on theory.

Humans possess both explicit and implicit memories, and have the capability to use intuition or logic to solve problems. If I’m right, and strong artificial intelligence requires replicating the capability of non-human animals, then I’d do well to first disregard logic, then disregard explicit learning of events and facts, and focus instead on how novel neural links form in nerves.

Of course, I always try to assume I’m wrong. So in hopes I’ll figure out how, I’m off to watch the syntience (artificial intuition) videos.

I was given How to Think About God by Mortimer J. Adler to read, but I find it very difficult to focus on the dry concepts while my eyes droop from fatigue. In the pages that I’ve read so far I’ve come across an interesting concept—that of a “supreme being.” Adler elaborates a bit on the concept by clarifying that a supreme being is one that is greater than any other, like the concept of infinity is greater than any number. As the author moves on from this to discuss things such as the existence or non-existence of such a being, I have trouble following because I fail to see the metric by which the greatness of a being is measured.

Adler brings up the Ontological argument provided by Anselm of Canterbury, where a being that comes into or out of existence is lesser than one that must always exist, which makes me think that he at least associates quantity of existence with “greatness”. This would imply that a being of infinite greatness would be all things, which would also imply that there is no distinction between the cosmos (all that is) and God (the greatest imaginable being). This seems consistent with the more pantheistic flavors of the major religions, but I’ve always had trouble seeing why the concept of a god is necessary in such a case, as Nature or the Universe would be synonymous.

In other thoughts, I read up on Artificial Intuition before I left, and I was struck by the connection to my thoughts after reading How We Decide by Jonah Lehrer. Lehrer distinguishes between what I think of as our Head vs. our Gut. We use our head to do specific logical reasoning and self-examination, but most of our behavior is governed by the subconscious split-second intuition that we use for everything from picking favorites to moving limbs. Monica Anderson emphasizes this point as it relates to artificial intelligence, and describes how intuitive models of reality are far more likely to produce general AI (AGI) than a logic-focused, reductionist, approach.

I’m in total agreement here, but it’s a bit frustrating, because it implies that consciousness is not capable of examining intuitive mental structures in great detail. For example, if you make a split second decision on whether to sit next to a person on the bus, it is nearly impossible to determine why you decided as such (most reasoning will likely boil down to false rationalizations). So now I’ve been separated from my greatest tool; I can no longer build AI based on how I think my own thought works. My intuition (lol) says that the place to start examining intuition is with simple animal behaviors, so now I’m on the lookout for good fruit fly brain studies or whatever.

Well, not really. Right now I’m on the lookout for something to keep me occupied while I ride through Kansas.