Comments on AI Quotes: Can our brains understand our brains? / by Robert Smith

One more in my series of comments on AI quotes from a recent Forbes article by Rob Toews.

Today's quote is:

"If the human brain were so simple that we could understand it, we would be so simple that we couldn't."

This one has fascinating origins. It first appeared as an epigraph of a chapter in The Biological Origin Of Human Values, a 1977 book by George Edgin Pugh, attributed to the author's father, Emerson Pugh, who worked for decades at IBM and developed important computer memory technology.

I have not read George Edgin's book, but he has an interesting background relative to its titular topic. The younger Mr Pugh worked in modelling real-world phenomena with computers, in what mostly seem to be US government projects, including distributions of radioactive fallout and the efficiency of anti-segregation bussing. Several critical essays indicate that the book reflects a computer modeller's perspective on the complexity of the brain, evolution, and human values.

However, I think the interesting word in his father's quote is understand. The etymology of this simple English word is genuinely fascinating. Of course, it means "to stand under." However, the sense of under here isn't in the usual sense of beneath. Instead, it comes from either the Sanskrit antar for "among" or "between," or the Latin inter, which has similar connotations, or from the Greek entera for "intestines." Understand uses under in the sense of "under such circumstances." So, can our thinking "stand amongst and between" a conception of the brain? Can we get into its guts, as it were?

I think this indicates here is the difference between understanding, in the sense of an algorithmic computer model etched and executed in computer memory, and the sort of wholistic understanding that is a hallmark of what human thinking really does. I say human thinking, rather than the human brain because it is an error to see the brain as the seat of all human thinking, as has been discussed previously in this series of comments.

Quantitative understanding, as in the sense of computers, generally involves creating a model that behaves in a manner that is sufficiently similar to the thing being modelled that one can draw useful conclusions. Qualitative understanding is to stand amongst the nature of a thing. For truly complex things like human thinking, this may be the best we can hope for. But I think that's not a bad thing.

One of the most important messages of modern complexity science is that systems can generate emergent properties that cannot be described through a reduction of those systems. When we talk about qualitative understanding, or in fact qualities themselves, I believe what we are talking about is thoughts. And, if thoughts can't be reduced to quantitative models (quantitative understanding), then qualities are first-class objects that exist in the world.

For these reasons, I believe that qualitative understanding is in no way less than or "beneath" quantitative understanding. Thus even if our thinking is simpler than the brain (or, in fact, the whole human thinking system), that does not mean we can't stand amongst it, and understand.