Competence without comprehension March 4, 2011Posted by Ezra Resnick in Computer science, Evolution.
Tags: Daniel Dennett
On the left, we have Gaudi’s cathedral in Barcelona; on the right, a termite mound. Both structures serve a purpose (or several purposes); and both exist, with their particular characteristics, for a reason. They are not the result of materials being thrown together randomly; it makes sense for us to ask why their features were built one way and not another. And yet, there is a crucial difference between the two.
In a recent lecture at UCLA, Daniel Dennett describes the difference this way: There is a reason why termites build mounds — but it’s not true that termites have a reason for building mounds. Human beings have reasons for the things they do, and they can represent those reasons explicitly. But no termite needs to understand the reasons behind its actions — no one needs to understand them. Complex reasons can emerge from the mindless, purposeless, automatic process of natural selection.
This idea, of course, is extremely counter-intuitive. Dennett quotes one early attack on Darwin, published anonymously in 1868:
In the theory with which we have to deal, Absolute Ignorance is the artificer; so that we may enunciate as the fundamental principle of the whole system, that, in order to make a perfect and beautiful machine, it is not requisite to know how to make it. This proposition will be found, on careful examination, to express, in condensed form, the essential purport of the Theory, and to express in a few words all Mr. Darwin’s meaning; who, by a strange inversion of reasoning, seems to think Absolute Ignorance fully qualified to take the place of Absolute Wisdom in all the achievements of creative skill.
Exactly! This “strange inversion of reasoning” was Darwin’s great insight: a new way of thinking, with profound consequences and explanatory power.
Dennett attributes a comparable “inversion of reasoning” to Alan Turing. Before modern computers, “computers” were humans who performed mathematical calculations manually. To do this, they had to understand arithmetic. But Turing realized that it’s not necessary for a computing machine to know what arithmetic is. And so we now have CPUs, spreadsheets, search engines, all performing complex tasks without understanding what they are doing: competence without comprehension.
This is the opposite of our own personal experience: our competences flow from our comprehension. But evolution shows us that comprehension can emerge as the result, not the cause, of competence. Just as life is ultimately constructed out of non-living parts, understanding can be constructed out of non-understanding parts. The individual neurons in our brain don’t understand anything — but we do.
There must be a continuum, therefore, ranging from a complete lack of understanding to the kind of understanding humans have. Do apes have reasons? Apes fall somewhere in the middle between termites and Gaudi. They have proto-reasons. The same might be said of our more complex computing machines. One day, we will reach the point when computers have full-fledged reasons of their own.
For billions of years on this planet, there was competence but no comprehension. There were reasons, but no one understood them. We have now evolved the ability to look back and see the reasons everywhere in the tree of life — reasons discovered by the same mindless process that produced us.