Brain = Abstraction Machine: A Fascinating Anecdote

 

I was struck by the implications of this event at the time, and it have remained so ever since.

I believe it is an extraordinary example of how the brain works, and shows why artificial intelligence is so difficult. In fact, it illustrates one critical and very fundamental function of the brain.

Many years ago I worked in the forests of the Northwest as a tree planter, reforesting clear cuts. The idea is that a contract would specify the spacing of trees on the ground (8’ x 8’, 10’ x 10’, for example) to achieve the number of tress per acre that the forester desired.

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Now, one aspect of this work is that there sometimes existed young trees on the site that had been naturally seeded. We called these natural reproductions, or reprods. Some of these are of a species considered commercially valuable trees, and others not. So, when we plant, we are instructed to treat the former as if it had been planted by us, and to ignore the latter and plant right next to them.

Typically, there was just one variety of reprod on a given unit, so it is easy to deal with. You just either skip over any reprod if it is valued, or plant right next to it if it is not.

We had one contract outside of Tiller, Oregon, however, on which there were two species, one in each category. To my recollection, one was the Western White Pine (Pinus monticola) and the other was the Jeffrey Pine (Pinus jeffreyi). The problem was, as they were both species of pine, they were very difficult to tell apart (at least as young seedlings).

On my first day of work, the Forest Service inspector took me and showed me the two. He explained the differences, which were two. The White Pine had 5 needles in a cluster, and each had a white streak underneath. The Jeffery Pine had only 3 needles per cluster and no streak. In order to tell the difference, one needed to walk up to the seedling on his or her line, and check. This was time consuming. One typically planted from 500 to 900 trees in a day, so stopping to check was a real problem. BUT, there was no other way to tell. The inspectors had no alternative methodology. We just had to live with this.

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So off I went – a bit grumpy with the delays – checking carefully each time I came across a reprod. Sometimes you would have to walk three to six feet to check tree, then look meticulously at the needles.

Each time, before I checked, I would form an opinion as to the species. As a couple of days passed, I noticed that I was getting quite accurate with my guesses. I soon was guessing correctly virtually every time. I began to gain confidence and quit checking closely, except a few time each day to be sure I was still in tune. It turned out that everybody on the crew had the same experience. They could tell immediately which tree species it was at a glance.

The interesting thing was this:

  1. While everyone could do it, not a single person could explain how!

That is, every planter could now tell immediately and accurately, from a dozen feet away, which of the two species  a particular seedling was. Yet not a single person could explain what qualities of the tree they were using to distinguish one from the other. There was no way for anyone to see the white streaks or count the needles from a distance. So this has remained an enigma.

To me, there is just one explanation.

There must be a collection of fine attributes about the trees, such as very subtle differences in:

  •  Color of bark
  •  Texture of bark
  •  Color of the needles
  •  Length of needles relative to the height of the seedling
  •  General form of the tree

Every one of these was minor and might occur in either one or the other of the species, but perhaps was more typical of one. So, while few seedling of species A would have all the attributes that might help identify it, they would have some of them which together throw the decision in the right direction.

These micro characteristics and the range of distribution of them were all too subtle for the conscious, analytical mind to register, but still the incredible networks of the neurons picked them out and formed a decision, a decision while correct could never be explained nor rationalized. We just knew which species it was.

This type of decision making is called Intuition. Intuition is frequently denigrated by analytic types, but that does not mean it is not real. [double negative intended.]

This is, in fact, a crucial part of intelligence. This story illustrates the fundamental function of the brain Abstraction.

  • Abstraction is what the brain does.

That is, from an extraordinarily complex deluge of data (i.e. sensory information), the brain abstracts sufficient portions to create an orderly picture – particularly one that is appropriate to a given task. It is like when we are listening to a favorite piece of music – sometimes we just close our eyes so we can focus completely on just the sound. So the mind discards a plethora of unwanted sensory data.

Imagine, for example, an early human hunter in the jungle, focused on tracking prey. Suddenly, in the corner of the eye a brief and tiny flash of yellow passes. All of a sudden, the tracking is forgotten as the hunter turns to face a potential attack from a tiger. This, of course, is a change of attention, but the brain is doing this all the time, even when attention is fixed. That is, it is filtering out a lot of details, and highlighting others, in order to achieve the current task.

Particularly in learning this is so. The newborn receives a flood of confusing input and only with time does the brain learn to organize into a sensible flow. It does this in part by abstracting that which is deemed important and forming collections of related impressions.

So in the case of the two trees, the brain began to make some correlations of subconscious visual data that led to recognition of various patterns. It abstracted from a plethora of data patterns that could be used for recognition.

Artificial Intelligence

This is one of the things that AI is trying to do, particularly AI in business analytics, such as IBM’s Watson. It sifts through volumes of data trying to find new correlations.

— Comments Appreciated —

 

Notes:

 

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One thought on “Brain = Abstraction Machine: A Fascinating Anecdote

  1. Pingback: Artificial Intelligence: Apple’s Second Revolutionary Offering – Apple Inc. (NASDAQ:AAPL) – Tech Box

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