274: How "relevance realization" distinguishes human from artificial intelligence

Remember that fun video where the kids are throwing a basketball, and the viewer is asked to count how many times the ball has been passed? About half the people who watch this video miss the gorilla that walked into the middle of the scene and thumped its chest. 

That’s a negative illustration of “relevance realization,” which is a very important topic in the world of AI. 

I like AI, and I hope I’ve learned how to use it well. 

At the same time, I’m aware of the vast library of fiction warning us about the dangers of AI, and I take that very seriously. Or at least as seriously as I can take something that I can’t influence. If Bill Gates creates Skynet, there’s not much I can do about it except die in a hopeless battle and hope for a foamy mug of mead in Valhalla. 

There is a strong reason to believe that AI is nowhere near general intelligence, and that has to do with something called “relevance realization.” 

Here’s the problem. There’s an almost infinite number of ways to process the sensory data we’re flooded with every day. Somehow our brains are able to find what’s relevant and focus on those things. 

The significance of data is a different thing than raw data collection, but for now I’m going to focus on the data itself. 

To get a sense of the scale of the problem, each of our eyes has about 120 million photoreceptors. Only about 1-2 million nerve fibers transmit that information to the brain. That means we’ve already lost about 99 percent of the data. 

Now let’s look at this in terms of bits of information. The optic nerves transmit about 10 million bits of visual information per second to the brain, but the brain can only consciously process 40-50 bits per second. That’s a teeny tiny fraction of the one percent of the data we’re getting from our eyes. The ratio of data input to conscious processing is about 200,000 to one. 

There are three other things to keep in mind here. 

First, the 40-50 bits of processing I mentioned above is conscious processing. Our unconscious minds process a lot more than that, and we have some weird filter that mediates between the conscious and the unconscious mind. 

Second, a lot of this processing has to do with our bodies – with the fact that we have hands, for example. If we had claws, or fins, or wings, we’d process the information very differently. 

Third, we don’t just react to pre-curated information, the way AI does. We react to dynamic and new situations, and quickly determine what’s relevant and what’s not. 

All these things show why “relevance realization” is such an important concept. To some extent, our brains choose which tiny bits of information to focus on, based on whether something stands out, what goal we’re trying to achieve, our understanding of the situation and environment, and our past experiences and current expectations. All of that is filtered through our conscious and unconscious minds, it’s biased by the nature of our bodies, and it’s raw, uncurated stuff that can change on a dime. 

Computers don’t do that. They don’t know how to pick what’s relevant, they don’t have unconscious minds, they don’t see the world from an embodied point of view, and so on. 

The current crop of AI, like ChatGPT, is only able to pick relevant information by piggybacking on what humans have already determined is relevant. The data that’s going into ChatGPT isn’t random, raw data. It’s stuff that we’ve already picked, curated, and processed. 

In order for AI to attain general intelligence, it’s going to have to be able to determine relevance on its own. 

Think back to the gorilla video. People like to point out such things to make fun of the way humans process information. The thing is, that blindness to irrelevant information is what allows us to walk across a busy street, ignoring all the irrelevant sights and sounds and focusing on what’s going to keep us alive.