The Mechanization of the Mind

"This is by Jean-Pierre Dupuy. It’s a French book that came out in English translation in 2000. I’ve chosen it because I think one of the main obstacles to developing a broadly materialist view of consciousness is that people get stuck in the metaphor of the brain as a computer. There is a tendency to equate the two, which in turn leads to the assumption that materialism is basically the same thing as having a functionalist perspective on the mind-brain relation: the brain is a computer, in which the wet stuff, the wetware, is the hardware, and the mindware is the software. Where does consciousness fit into this? Is it some specific kind of mindware running on the wetware of the brain? Can we therefore simulate consciousness? Thinking of the brain as a computer overly constrains the way we think about these questions about the scope of materialism in general, and about the way we interpret experimental data. The computer metaphor also leads to a neglect of the body and the environment, because computers work without a body and an environment. Unfortunately this metaphor, of the brain as a computer, has become very dominant, not just in consciousness research, but in cognitive science generally. Oh yes. It underlies all these tropes about the simulation hypothesis , of mind uploading. There’s no necessity to buy into this computational metaphor of mind in order to pursue a broadly materialist agenda. You just don’t have to do it. We have always had metaphors for the brain – its complexity and opacity has demanded it – but these metaphors have always changed over time, driven often by whatever technology is dominant. In fact, one of my favourite recent books on the history of neuroscience is The Idea of the Brain by Matthew Cobb , which lays out a beautiful account of metaphors about the brain, how they’ve changed over time, and how they’ve influenced thinking about brain and mind and consciousness. I really enjoyed that book. Going back to Dupuy, reading about the historical roots of the computational metaphor of mind and its alternatives was really enlightening for me when I first encountered it more than twenty years ago. I was doing my PhD at Sussex, the same place where I am now as faculty. We were learning all about dynamical systems theory and embodiment and autopoiesis and all these concepts which really didn’t have much to do with computation or representation, and which were considered rather fringe (some still are, of course). At Sussex we were like the vanguard of the anti-representationalist resistance in cognitive science in the 1990s—showing that you can, for instance, get simple robots to do complicated things without any need for use of representational language. Now, it’s possible to get carried away and say that there’s never any need for representational speak at all when discussing the mind and brain. I don’t agree with that. My preferred way of thinking about the brain now is as a ‘prediction machine’ and there are sensible ways in which to think of the generative models underlying predictions as instantiating representations of some sort. Avoiding falling into the assumption that the brain is a computer is, I think, powerfully enabling for how we understand mind-brain behavior, and also for thinking about how brain activity might underlie or shape consciousness. Dupuy’s wonderful book takes us back to the Macy conferences, a series of meetings that happened in the late 1940s and early 50s in the US and which were closely associated with the discipline of cybernetics. I don’t know what people think cybernetics means now, because it’s a word that’s been co-opted and corrupted in many different ways, but at the time it was a rich mixture of philosophy, mathematics, the beginnings of computer science and AI, biology, engineering, sociology, even anthropology. The meetings hosted incredibly lively discussions exploring the basic idea that the brain and living systems are machines, and that they exercise control. This conception of the brain as a control system, engaged in regulation, with tight coupling between inputs and outputs and lots of feedback loops and the like was, and is, a very different perspective on brain function to the classical cognitive perspective of input, then computation, then output. What’s fascinating historically is that, back in the 1950s, there was very little clear air between these ways of thinking. As well as cybernetic pioneers like Norbert Wiener, the Macy conferences attracted some of the big names that we now associate with the computational metaphor of mind—like John von Neumann, the developer of the serial architecture underlying modern computers. At the time, these people were discussing all these ideas, all together. Even now, reading Dupuy’s book broadens one’s perspective about what kinds of form mechanistic and materialistic explanations can take and reminds us that the brain isn’t just doing computation—if it’s doing computation at all. The brain is embodied, and the body is embedded. The function of the brain can only be understood in terms of a rich context of tightly coupled interactions with strong feedback and recurrency—a very different situation from how a disembodied chess-playing (or Go-playing) computer searches ahead through unfolding trees of possible moves without doing anything. What’s more, the first neural networks came out of cybernetic thinking, not out of the development of the computational metaphor of mind. The recent avalanche of deep learning traces directly to the perceptron, to the work of McCulloch and Pitts, who were central participants in the Macy conferences. Dupuy’s book relates all this and much more, and it does so in a beautifully written and admirably concise way. I confess, as with Consciousness Explained , I haven’t read this book all the way through since my first encounter, but it made a big impact on me at the time, providing me with a systematicity to my skepticism about the computational metaphor of the mind. “One of the main obstacles to developing a broadly materialist view of consciousness is that people get stuck in the metaphor of the brain as a computer” There are a couple of other books I’d have loved to have included here. My PhD supervisor, Phil Husbands, and Owen Holland, have a recent book called The Mechanical Mind in History , which is a history of a similar group of meetings that took place in the UK, a parallel cybernetics movement in the 1950s that was called the Ratio Club. A lot of this activity, both in the UK and the US, was spurred by the Second World War, of course, the need to design machines that were useful in particular ways, that controlled guided missiles and that provided radar. You’re not going to control a missile by building a chess computer (though you might end up breaking the Enigma code). The UK group of cyberneticians included people like Ross Ashby, who has turned out to be very fundamental to my own thinking, and also Alan Turing, Horace Barlow and William Grey Walter, who is one of the great interdisciplinary pioneers of modern neuroscience. Grey Walter built a famous family of tortoises or turtles—it’s never entirely clear which term he preferred—so-called Machina speculatrix that showed autonomous behavior navigating back to their hutches when they were running low on battery. This was an early demonstration of how you can get compelling behavior from very simple circuits when they are embedded in a sufficiently rich embodied environment. Looking back, it’s something of a tragedy that cybernetics lost its way—a message that is promiment in both Dupuy’s book and the treatment by Husbands and Holland. It certainly lost its influence at the time. There was a second wave of cybernetics, but it never really had the impact or integrative coverage that the first wave did. At the same time, of course, the computational metaphor of mind really took off because people were building actual computers. Suddenly it was, ‘Yes! We have a computer that really can play chess ’ and all the funding went that way. All the everything went that way. Meanwhile, Chile tried to run its government on cybernetic principles and failed badly. There were lots of mistakes or historical contingencies that led to the general supremacy of the computational metaphor of mind. Reading books like Dupuy’s helps remind you that history could have unfolded differently. And it’s not too late. In fact, I think it’s still essential to take on board some of the insights from that time. To some extent. I was never formally trained in philosophy, but it’s hard to imagine any discipline of natural science where having a philosophical literacy is not going to be an advantage. It’s always going to help. At a minimum, it helps you avoid making naive and wrong assumptions about what you’re doing. I suppose there will be some areas of neuroscience that can be moderately encapsulated, without needing a day-to-day interaction with philosophy. You will still need to have some basic, background philosophical knowledge of why you’re doing what you’re doing and what it means. But if, for instance, you’re trying to unpack how the stomatogastric ganglion of a sea snail works, sure, you can probably get on with that job and be a relatively pure neuroscientist, and that’s fine. But when it comes to thinking about something like consciousness, absolutely not. There is no way to make good progress without really taking it on the chin that it’s an interdisciplinary enterprise permeated by philosophy and following through with the consequences of that."