Is “Is the brain a computer?” even a good question?

It’s too late to change the answer, and it distracts from the really useful questions about the relations between computers and brains. Nevertheless, a deeper look finds that brains stretch the definition of computing, perhaps beyond the breaking point.

This is part 1 of a series of brief essays (sometimes very brief) on aspects of this question.

Preface

Since the question seems to be taken seriously most often by neuroscientists who are trying to talk to a broader audience, these essays assume some knowledge of neurons and brains, and less knowledge about computers and computer science. But they challenge many assumptions about computers that are held by neuroscientists and philosophers. Because we’re trying to find a common language for talking about both brains and computers, we will get into areas that are unfamiliar to many computer scientists and challenge their assumptions as well, and we will cast our net of supporting evidence well beyond the traditional academic literature. I hope that the analyses and analogies here will stimulate researchers to fill in the many gaps that become visible when we achieve the high perspective needed needed to see how brains and computers relate to each other.

This series started out as a quick response to a couple of essays published in The Spike, but I wanted to explain how my answer to “Is the brain a computer?” is a reasoned conclusion from a view of computation and neuroscience that may be larger than the common perspective, rather than an unsupported opinion about seemingly unrelated concepts. As Blaise Pascal, or Mark Twain, and many others since then might have said, I regret that I could not make it shorter.

Series sections

1. Preface, Contents, and Introduction [this section]
2. What is a computer? Something that computes? Or Someone?
3. What does it mean for a computer to be “Universal”?
4. Computers vary across many dimensions
5. How is a brain like a PC? Neither one is the computer you think it is
6. Why did brains evolve, anyway?
7. Five better questions
8. A better answer: the brain is the organism’s master controller

Introduction

Writers have made a metaphorical equivalence between artificial computers and brains ever since the electronic computer emerged from wartime secrecy in the 1940s. This equivalence has become embedded in the languages we use to talk about them, so it’s no surprise that capturing the distinction with scientific precision has turned out to be no easy task. Once a concept has become embedded in languages used by hundreds of millions or billions of people, a comparatively small number of scientists attempting to control a technical term has little chance of wresting ownership of it back from them.

You can see the depth of that embedding by noticing that the Chinese characters for “computer” are composed of characters for “electric” and “brain”. If you want to write“the brain is a computer” in Chinese you end up writing something like “the brain is an electric brain”. Writing about this metaphor must be very difficult for our Chinese colleagues.

Control over the relationship between the terms is made even more difficult by the way that the capability of artificial computers has expanded over the years since they were first invented. Although “computing” originally meant performing arithmetic operations on numbers, most of the tasks that we use computers for are not explicitly numerical. Few people are aware that the process of rendering a video stream from YouTube or NetFlix fundamentally involves a vast number of discrete cosine computations, or that the cyclic redundancy checks that assure the integrity of the data streams between Google’s or Amazon’s servers and their personal device are based on computation of polynomials over finite fields, nor should they. For them, the computer is not calculating, it is providing a webpage or a motion picture.

From the perspectives of both the ordinary user and the theorist, what makes the computer such an important advance over any other device is not its numerical capability, or even its ability to follow a specified program, since some kinds of computers don’t use programs, but its universality — its ability to do anything with symbols or to be any kind of symbol processor that it’s possible to do or to be. Although the idea of computation started out with numbers, the equivalences between numerical operations, logical operations, and operations on arbitrary strings of symbols were recognized soon after the idea of universality itself was formally characterized.

The scope of the equivalences between different kinds of universal symbol-processing systems, and the variety of devices and systems that can implement them turned out to be wider than anyone could have imagined. But it was the human brain that was the first kind of universal symbol-processing system. As soon as artificial computers were invented, the equivalence between them and the symbol and numerical capabilities of human brains was recognized, and statements announcing that equivalence have been unavoidable ever since.

Go on to Part 2