backwardIn the course of this review of Carlo Rovelli’s Seven Brief Lessons on Physics, Alva Noë asks a fascinating question: does it make any sense to imagine that one might think backward?

In physics we are accustomed to thinking that entropy always increases; things run down, spread out, differences are evened out and available energy always decreases. Are cognitive processes like that, always going in one underlying direction? Are they like a river which flows to the sea, or are they more like a path we can take in either direction?

Well, we can’t talk backwards without careful preparation, and some kinds of conscious thought resemble talking to oneself. In fact, we can’t perform most tasks backwards without rehearsal. Unless one takes the trouble to learn zedabetical order, we cannot easily recite our letters in reverse. So it doesn’t seem we can do that kind of backward thinking, at least. We can, of course, read a written sentence in the reverse word order and I suppose that in that sense we can think the same sentence backwards, or ‘backwards sentence same the think’; but we might well doubt whether that truly reverses the thought.

On the other hand, on another level, there seems to be no inherent direction to a chain of thought. If I think of an egg, it makes me think of breakfast, and breakfast makes me think of getting up; but thinking about getting up might equally have prompted thoughts of breakfast, which in turn might have brought an egg to mind. The association of ideas goes both ways. Logical thought needs a little more care. ‘If p then q’ does not allow us to conclude that if q then p – but we can say that not-q gives us not-p. With due attention to the details there doesn’t seem to be a built-in direction to deduction.

The universal presence of memory in all our thoughts seems a deal-breaker on reversibility, though. We cannot forget things at will; memories constantly accumulate; and we cannot deliberately unthink a thought in such a way as to erase it from recollection. This one-way effect seems to be equally true of certain kinds of thought on another level. We have, let’s say, a problem in mind; all the clues we need are known. At some point they come together to point to the right conclusion – Aha! Unless we find a flaw in our reasoning, the meshing of the clues cannot be unpicked. We can’t ununderstand; the process of comprehension seems as irrevocable as the breaking of an eggshell or the cooking of a omelette.

There’s an odd thing about it though. The breaking of the egg is an example of the wider principle of entropy; the shell is destroyed, and later the protein is denatured by heat. The solving of the problem, by contrast, is constructive; we’re left with more than we had before and our mental contents are better structured, not worse. Learning and understanding seems like a process of growth. Like the growth of a plant it is of course just a local reversal of entropy, which has to be paid for through the use of a lot of irretrievable energy; still, it’s remarkable (as is the growth of a plant, after all).

Hang on, though. Isn’t it the case that we might have been entertaining a dozen different ideas about the possible solution to our problem?  Once we have the answer those other hypotheses are dropped and indeed may even be truly forgotten. More than that, the right answer may let us simplify our ideas, the way Copernicus let us do away with epicycles and all the rest of the Ptolemaic system nobody has to think about any more. Occam tells us to minimise the number of angels we require for our theory, so isn’t the growth of understanding sometimes a synthesis which actually has the character of a reductive simplification? That isn’t usually a reversal as such, but doesn’t it involve in some sense the unthinking of certain thoughts? David Lodge somewhere has a character feel a pang of pity for all the Marxist professors in the universities of no-longer-communist countries who must presumably unspool years of patient theoretical exegesis in order to start understanding the world again.

Well, yes, but I don’t think that is truly an unthinking or reverse cogitation. Is it perhaps more like a plant managing to grow downwards? So no, as Noë implied in the first place, it doesn’t really make sense to imagine we might think backward.

observationAre we being watched? Over at Aeon, George Musser asks whether some AI could quietly become conscious without our realising it. After all, it might not feel the need to stop whatever it was doing and announce itself. If it thought about the matter at all, it might think it was prudent to remain unobserved. It might have another form of consciousness, not readily recognisable to us. For that matter, we might not be readily recognisable to it, so that perhaps it would seem to itself to be alone in a solipsistic universe, with no need to try to communicate with anyone.

There have been various scenarios about this kind of thing in the past which I think we can dismiss without too much hesitation. I don’t think the internet is going to attain self-awareness because however complex it may become, its simply isn’t organised in the right kind of way. I don’t think any conventional digital computer is going to become conscious either, for similar reasons.

I think consciousness is basically an expanded development of the faculty of recognition. Animals have gradually evolved the ability to recognises very complex extended stimuli; in the case of human beings things have gone a massive leap further so that we can recognise abstractions and generalities. This makes a qualitative change because we are no longer reliant on what is coming in through our sense from the immediate environment; we can think about anything, even imaginary or nonsensical things.

I think this kind of recognition has an open-ended quality which means it can’t be directly written into a functional system; you can’t just code it up or design the mechanism. So no machines have been really good candidates; until recently. These days I think some AI systems are moving into a space where they learn for themselves in a way which may be supported by their form and the algorithms that back them up, but which does have some of the open-ended qualities of real cognition. My perception is that we’re still a long way from any artificial entity growing into consciousness; but it’s no longer a possibility which can be dismissed without consideration; so a good time for George to be asking the question.

How would it happen? I think we have to imagine that a very advanced AI system has been set to deal with a very complex problem. The system begins to evolve approaches which yield results and it turns out that conscious thought – the kind of detachment from immediate inputs I referred to above – is essential. Bit by bit (ha) the system moves towards it.

I would not absolutely rule out something like that; but I think it is extremely unlikely that the researchers would fail to notice what was happening.

First, I doubt whether there can be forms of consciousness which are unrecognisable to us. If I’m right consciousness is a kind of function which yields purposeful output behaviour, and purposefulness implies intelligibility. We would just be able to see what it was up to. Some qualifications to this conclusion are necessary. We’ve already had chess AIs that play certain end-games in ways that don’t make much sense to human observers, even chess masters, and look like random flailing. We might get some patterns of behaviour like that. But the chess ‘flailing’ leads reliably to mate, which ultimately is surely noticeable. Another point to bear in mind is that our consciousness was shaped by evolution, and by the competition for food, safety, and reproduction. The supposed AI would have evolved in consciousness in response to completely different imperatives, which might well make some qualitative difference. The thoughts of the AI might not look quite like human cognition.  Nevertheless I still think the intentionality of the AI’s outputs could not help but be recognisable. In fact the researchers who set the thing up would presumably have the advantage of knowing the goals which had been set.

Second, we are really strongly predisposed to recognising minds. Meaningless whistling of the wind sounds like voices to us; random marks look like faces; anything that is vaguely humanoid in form or moves around like a sentient creature is quickly anthropomorphised by us and awarded an imaginary personality. We are far more likely to attribute personhood to a dumb robot than dumbness to one with true consciousness. So I don’t think it is particularly likely that a conscious entity could evolve without our knowing it and keep a covert, wary eye on us. It’s much more likely to be the other way around: that the new consciousness doesn’t notice us at first.

I still think in practice that that’s a long way off; but perhaps the time to think seriously about robot rights and morality has come.

bokkenThe latest JCS features a piece by Christopher Curtis Sensei about the experience of achieving mastery in Aikido. It seems he spent fifteen years cutting bokken (an exercise with wooden swords, don’t ask me), becoming very proficient technically but never satisfying the old Sensei. Finally he despaired and stopped trying; at which point, of course, he made the required breakthrough. He needed to stop thinking about it. You do feel that his teacher could perhaps have saved him a few years if he had just said so explicitly – but of course you cannot achieve the state of not thinking about something directly and deliberately. Intending to stop thinking about a pink hippo involves thinking about a pink hippo; you have to do something else altogether.

This unreflective state of mind crops up in many places; it has something to do with the desirable state of ‘flow’ in which people are said to give their best sporting or artistic performances; it seems to me to be related to the popular notion of mindfulness, and it recalls Taoist and other mystical ideas about cleared minds and going with the stream. To me it evokes Julian Jaynes, who believed that in earlier times human consciousness manifested itself to people as divine voices; what we’re after here is getting the gods to shut up at last.

Clearly this special state of mind is a form of consciousness (we don’t pass out when we achieve it) and in fact on one level I think it is very simple. It’s just the absence of second-order consciousness, of thoughts about thoughts, in other words. Some have suggested that second-order thought is the distinctive or even the constitutive feature of human consciousness; but it seems clear to me that we can in fact do without it for extended periods.

All pretty simple then. In fact we might even be able to define it physiologically – it could be the state in which the cortex stops interfering and let’s the cerebellum and other older bits of the brain do their stuff uninterrupted – we might develop a way of temporarily zapping or inhibiting cortical activity so we can all become masters of whatever we’re doing at the flick of a switch. What’s all the fuss about?

Except that arguably none of the foregoing is actually about this special state of mind at all. What we’re talking about is unconsidered thought, and I cannot report it or even refer to it without considering it; so what have I really been discussing? Some strange ghostly proxy? Nothing? Or are these worries just obfuscatory playing with words?
There’s another mental thing we shouldn’t, logically, be able to talk about – qualia. Qualia, the ineffable subjective aspect of things, are additional to the scientific account and so have no causal powers; they cannot therefore ever have caused any of the words uttered or written about them. Is there a link here? I think so. I think qualia are pure first-order experiences; we cannot talk about them because to talk about them is to move on to second-order cognition and so to slide away from the very thing we meant to address. We could say that qualia are the experiential equivalent of the pure activity which Curtis Sensei achieved when he finally cut bokken the right way. Fifteen years and I’ll understand qualia; I just won’t be able to tell anyone about it…

red lampWas Libet wrong? The question has often been asked since the famous experiments which found that a detectable “Readiness Potential” (RP) showed that our decisions were made half a second before they entered our consciousness. There are plenty of counter arguments but the findings themselves have been reproduced and seem unassailable.

However, Christian Jarrett reports two new pieces of research which shed fresh light on the issue (Jarrett’s book Great Myths of the Brain is very sensible, btw, and should be read by all science journalists).

The first piece of research  shows that although an action may be prepared by the brain before we know we’ve decided to act, we can still change our minds. Subjects were asked to press a button at a moment of their choice after a green light came on. However, if a red light appeared before they pressed, they were asked to refrain. The experimenters then detected the RP which showed the subjects were about to press the button, and used the red light to try to cancel the intention. They found that although there was a ‘point of no return’, so long as the red light appeared in time the subjects were able to hold off and not press the button after all.

That means that a significant qualification has to be added to Libet’s initial findings – but it’s one Libet himself had already come up with. He was aware that the emergent action could be suppressed, and memorably said it showed that while we might not have free will, we could still have ‘free won’t’. I don’t know much use that is. In the experiment the subjects simply responded to a red light, but if the veto is to make consciousness effective again we seem to need the veto decision to happen instantly and overtake the action decision somehow. That seems problematic if not paradoxical. I also get quite confused trying to imagine what it would be like to veto mentally a decision you’re not yet aware of having made. Still, I suppose we must be grateful for whatever residual degree of freedom the experiments allow us.

The second piece of research  calls into question the nature of the RP itself. Libet’s research more or less took it for granted that the RP was a reliable sign that an action was on the way, but the new findings suggest that it is really just part of the background ebb and flow of neural noise. Actions do arise when the activity crosses a certain threshold, but the brain is much quicker about getting to that level when the background activity is already high.

That certainly adds some complexity to the picture, but I don’t think it really dispels the puzzle of Libet’s results. The RP may be fuzzier than we thought and it may not have as rigid a link to action as we thought – but it’s still possible to predict the act before we’re aware of the decision. What if we redesigned the first experiment? We tell the subject to click on a target at any time after it appears; but we detect the RP and whip the target away a moment before the click every time. The subject can never  succeed. The fact that that is perfectly possible surely remains more than a little unsettling.

Go boardThe recent victory scored by the AlphaGo computer system over a professional Go player might be more important than it seems.

At first sight it seems like another milestone on a pretty well-mapped road; significant but not unexpected. We’ve been watching games gradually yield to computers for many years; chess notoriously, was one they once said was permanently out of the reach of the machines. All right, Go is a little bit special. It’s an extremely elegant game; from some of the simplest equipment and rules imaginable it produces a strategic challenge of mind-bending complexity, and one whose combinatorial vastness seems to laugh scornfully at Moore’s Law – maybe you should come back when you’ve got quantum computing, dude! But we always knew that that kind of confidence rested on shaky foundations; maybe Go is in some sense the final challenge, but sensible people were always betting on its being cracked one day.

The thing is, Go has not been beaten in quite the same way as chess. At one time it seemed to be an interesting question as to whether chess would be beaten by intelligence – a really good algorithm that sort of embodied some real understanding of chess – or by brute force; computers that were so fast and so powerful they could analyse chess positions exhaustively. That was a bit of an oversimplification, but I think it’s fair to say that in the end brute force was the major factor. Computers can play chess well, but they do it by exploiting their own strengths, not by doing it through human-style understanding. In a way that is disappointing because it means the successful systems don’t really tell us anything new.

Go, by contrast, has apparently been cracked by deep learning, the technique that seems to be entering a kind of high summer of success. Oversimplifying again, we could say that the history of AI has seen a contest between two tribes; those who simply want to write programs that do what’s needed, and those that want the computer to work it out for itself, maybe using networks and reinforcement methods that broadly resemble the things the human brain seems to do. Neither side, frankly, has altogether delivered on its promises and what we might loosely call the machine learning people have faced accusations that even when their systems work, we don’t know how and so can’t consider them reliable.

What seems to have happened recently is that we have got better at deploying several different approaches effectively in concert. In the past people have sometimes tried to play golf with only one club, essentially using a single kind of algorithm which was good at one kind of task. The new Go system, by contrast, uses five different components carefully chosen for the task they were to perform; and instead of having good habits derived from the practice and insights of human Go masters built in, it learns for itself, playing through thousands of games.

This approach takes things up to a new level of sophistication and clearly it is yielding remarkable success; but it’s also doing it in a way which I think is vastly more interesting and promising than anything done by Deep Thought or Watson. Let’s not exaggerate here, but this kind of machine learning looks just a bit more like actual thought. Claims are being made that it could one day yield consciousness; usually, if we’re honest, claims like that on behalf of some new system or approach can be dismissed because on examination the approach is just palpably not the kind of thing that could ever deliver human-style cognition; I don’t say deep learning is the answer, but for once, I don’t think it can be dismissed.

Demis Hassabis, who led the successful Google DeepMind project, is happy to take an optimistic view; in fact he suggests that the best way to solve the deep problems of physics and life may be to build a deep-thinking machine clever enough to solve them for us (where have I heard that idea before?). The snag with that is that old objection; the computer may be able to solve the problems, but we won’t know how and may not be able to validate its findings. In the modern world science is ultimately validated in the agora; rival ideas argue it out and the ones with the best evidence wins the day. There are already some emergent problems, with proofs achieved by an exhaustive consideration of cases by computation that no human brain can ever properly validate.

More nightmarish still the computer might go on to understand things we’re not capable of understanding. Or seem to: how could we be sure?

Alfred SmeeCharles Babbage was not the only Victorian to devise a thinking machine.

He is, of course, considered the father, or perhaps the grandfather, of digital computing. He devised two remarkable calculating machines; the Difference Engine was meant to produce error-free mathematical tables for navigation or other uses; the Analytical Engine, an extraordinary leap of the imagination, would have been the first true general-purpose computer. Although Babbage failed to complete the building of the first, and the second never got beyond the conceptual stage, his achievement is rightly regarded as a landmark, and the Analytical Engine routines published by Lady Lovelace in 1843 with a translation of Menabrea’s description of the Engine, have gained her recognition as the world’s first computer programmer.

The digital computer, alas, went no further until Turing a hundred years later; but in 1851 Alfred Smee published The Process of Thought adapted to Words and Language together with a description of the Relational and Differential Machines – two more designs for cognitive mechanisms.

Smee held the unusual post of Surgeon to the Bank of England – in practice he acted as a general scientific and technical adviser. His father had been Chief Accountant to the Bank and little Alfred had literally grown up in the Bank, living inside its City complex. Apparently, once the Bank’s doors had shut for the night, the family rarely went to the trouble of getting them unlocked again to venture out; it must have been a strangely cloistered life. Like Babbage and other Victorians involved in London’s lively intellectual life, Smee took an interest in a wide range of topics in science and engineering, with his work in electro-metallurgy leading to the invention of a successful battery; he was a leading ophthalmologist and among many other projects he also wrote a popular book about the garden he created in Wallington, south of London – perhaps compensating for his stonily citified childhood?

Smee was a Fellow of the Royal Society, as was Babbage, and the two men were certainly acquainted (Babbage, a sociable man, knew everyone anyway and was on friendly terms with all the leading scientists of the day; he even managed to get Darwin, who hated socialising and suffered persistent stomach problems, out to some of his parties). However, it doesn’t seem the two ever discussed computing, and Smee’s book never mentions Babbage.

That might be in part because Smee came at the idea of a robot mind from a different, biological angle. As a surgeon he was interested in the nervous system and was a proponent of ‘electro-biology’, advocating the modern view that the mind depends on the activity of the brain. At public lectures he exhibited his own ‘injections’ of the brain, revealing the complexity of its structure; but Golgi’s groundbreaking methods of staining neural tissue were still in the future, and Smee therefore knew nothing about neurons.

Smee nevertheless had a relatively modern conception of the nervous system. He conducted many experiments himself (he used so many stray cats that a local lady was moved to write him a letter warning him to keep clear of hers) and convinced himself that photovoltaic effects in the eye generated small currents which were transmitted bio-electrically along the nerves and processed in the brain. Activity in particular combinations of ‘nervous fibrils’ gave rise to awareness of particular objects. The gist is perhaps conveyed in the definition of consciousness he offered in an earlier work, Principles of the Human Mind Deuced from Physical Laws:

When an image is produced by an action upon the external senses, the actions on the organs of sense concur with the actions in the brain; and the image is then a Reality.
When an image occurs to the mind without a corresponding simultaneous action of the body, it is called a Thought.
The power to distinguish between a thought and a reality, is called Consciousness.

This is not very different in broad terms from a lot of current thinking.

In The Process of Thought Smee takes much of this for granted and moves on to consider how the brain deals with language. The key idea is that the brain encodes things into a pyramidal classification hierarchy. Smee begins with an analysis of grammar, faintly Chomskyan in spirit if not in content or level of innovation. He then moves on rapidly to the construction of words. If his pyramidal structure is symbolically populated with the alphabet different combinations of nervous activity will trigger different combinations of letters and so produce words and sentences. This seems to miss out some essential linguistic level, leaving the impression that all language is spelled out alphabetically, which can hardly be what Smee believed.

When not dealing specifically with language the letters in Smee’s system correspond to qualities and this pyramid stands for a universal categorisation of things in which any object can be represented as a combination of properties. (This rather recalls Bishop Wilkins’ proposed universal language, in which each successive letter of each noun identifies a position in an hierarchical classification, so that the name is an encoded description of the thing named.)

At least, I think that’s the way it works. The book goes on to give an account of induction, deduction, and the laws of thought; alas, Smee seems unaware of the problem described by Hume and does not address it. Instead, in essence, he just describes the processes; although he frames the discussion in terms of his pyramidal classification his account of induction (he suggests six different kinds) comes down to saying that if we observe two characteristics constantly together we assume a link. Why do we do that – and why is it we actually often don’t? Worse than that, he mentions simple arithmetic (one plus one equals two, two times two is four) and says:

These instances are so familiar we are apt to forget that they are inductions…

Alas, they’re not inductions. (You could arrive at them by induction, but no-one ever actually does and our belief in them does not rest on induction.)

I’m afraid Smee’s laws of thought also stand on a false premise; he says that the number of ideas denoted by symbols is finite, though too large for a man to comprehend. This is false. He might have been prompted to avoid the error if he had used numbers instead of letters for his pyramid – because each integer represents an idea; the list of integers goes on forever, yet our numbering system provides a unique symbol for every one? So neither the list of ideas nor the list of symbols can be finite. Of course that barely scratches the surface of the infinitude of ideas and symbols, but it helps suggest just how unmanageable a categorisation of every possible idea really is.

But now we come to the machines designed to implement these processes. Smee believed that his pyramidal structure could be implemented in a hinged physical mechanism where opening would mean the presence or existence of the entity or quality and closing would mean its absence. One of these structures provides the Relational Machine. It can test membership of categories, or the possession of a particular attribute, and can encode an assertion, allowing us to test consistency of that assertion with a new datum. I have to confess to having only a vague understanding of how this would really work. He allows for partial closing and I think the idea is that something like predicate calculus could be worked out this way. He says at one point that arithmetic could be done with this mechanism and that anyone who understands logarithms will readily see how; I’m afraid I can only guess what he had in mind.

It isn’t necessary to have two Relational Machines to deal with multiple assertions because we can take them in sequence; however the Differential Machine provides the capacity to compare directly, so that we can load into one side all the laws and principles that should guide a case while uploading the facts into the other.

Smee had a number of different ideas about how the machines could be implemented, and says he had a number of part-completed prototypes of partial examples on his workbench. Unlike Babbage’s designs, his were never meant to be capable of full realisation, though; although he thinks it is finite he says the Relational Machine would cover London and the mechanical stresses would destroy it immediately if it were ever used; moreover, using it to crank out elementary deductions would be so slow and tedious people would soon revert to using their wonderfully compact and efficient brains instead. But partial examples will helpfully illustrate the process of thought and help eliminate mistakes and ‘quibbles’. Later chapters of the book explore things that can go wrong in legal cases, and describe a lot of the quibbles Smee presumably hopes his work might banish.

I think part of the reason Smee’s account isn’t clearer (to me, anyway) is that his ideas were never critiqued by colleagues and he never got near enough to a working prototype to experience the practical issues sufficiently. He must have been a somewhat lonely innovator in his lab in the Bank and in fairness the general modernity of his outlook makes us forget how far ahead of his time he was. When he published his description of his machines, Wundt, generally regarded as the founder of scientific psychology, was still an undergraduate. To a first approximation, nobody knew anything about psychology or neurology. Logic was still essentially in the long Aristotelian twilight – and of course we know where computing stood. It is genuinely remarkable that Smee managed, over a hundred and fifty years ago, to achieve a proto-modern, if flawed, understanding of the brain and how it thinks. Optimists will think that shows how clever he was; pessimists will think it shows how little our basic conceptual thinking has been updated by the progress of cognitive science.

minskyMarvin Minsky, who died on Sunday, was a legend.  Here’s a slightly edited version of my 2004 post about him.



Is it time to rehabilitate Marvin Minsky? As a matter of fact, I don’t think he was ever dishabilitated (so to speak) but it does seem to be generally felt that there are a couple of black marks against his name. The most widely-mentioned count against him and his views is a charge of flagrant over-optimism about the prospects for artificial intelligence. A story which gets quoted over and over again has it that he was so confident about duplicating human cognitive faculties, even way back in the 1970s when the available computing power was still relatively modest, that he gave the task of producing a working vision system to one of his graduate students as a project to sort out over the summer.

The story is apocryphal, but one can see why it gets repeated so much. The AI sceptics like it for obvious reasons, and the believers use it to say “I may seem like a gung-ho over-the-top enthusiast, but really my views are quite middle-of-the-road, compared to some people. Look at Marvin Minsky, for example, who once…”

Still, there is no doubt that Minsky did at one time predict much more rapid progress than has, in the event materialized: in 1977 he declared that the problem of creating artificial intelligence would be substantially solved within a generation.

The other and perhaps more serious charge against him is that in 1969, together with Seymour Papert, he gave an unduly negative evaluation of Frank Rosenblatt’s ‘Perceptron’ (an early kind of neural network device which was able to tackle simple tasks such as shape recognition). Their condemnation, based on the single-layer version of the perceptron rather than more complex models, is considered to have led to the effective collapse of Rosenblatt’s research project and a long period of eclipse for networks before a new wave of connectionist research came along and claimed Rosenblatt as an unfairly neglected forerunner.

There’s something in both these charges, but surely in fairness neither ought to be all that damaging? Optimism can be a virtue, without which many long and difficult enterprises could not get started, and Minsky’s was really no more starry-eyed than many others. The suggestion of AI within a generation does no more at most than echo Turing’s earlier forecast of human-style performance by the end of the century, and although it didn’t come true, you would have to be a dark pessimist to deny that there were (and perhaps still are) some encouraging signs.

It seems to be true that Minsky and Papert, by focusing on the single-layer perceptron alone, did give an unduly negative view of Rosenblatt’s ideas – but if researchers were jailed for giving dismissive accounts of their rivals’ work, there wouldn’t be many on the loose today. The question is why Minsky and Papert’s view had such a strong negative influence when a judicious audience would surely have taken a more balanced view.

I suspect that both Minsky’s optimism and his attack on the perceptron should properly be seen as crystallizing in a particularly articulate and trenchant form views which were actually widespread at the time: Minsky was not so much a lonely but influential voice as the most conspicuous and effective exponent of the emergent consensus.

What then, about his own work? I take the most complete expression of his views to be “The Society of Mind”. This is an unusual book in several ways – for one thing it is formatted like no other book I have ever seen, with each page having its own unique heading. It has an upbeat tone, compared to many books in the consciousness field, which tend to be written as much against a particular point of view as for one. It is full of thought-provoking points, and is hard to read quickly or to summarise adequately, not because it is badly or obscurely written (quite the contrary) but because it inspires interesting trains of thought which take time to mull over adequately.

The basic idea is that each simple task is controlled by an agent, a kind of sub-routine. A set of agents which happen to be active when a good result is achieved get linked together by a k-line. The multi-level hierarchical structures which gradually get built up allow complex and highly conditional forms of behaviour to be displayed. Building with blocks is used as an example, starting with simple actions such as picking up a block, and gradually ascending to the point where we debate whether to go on playing a complex block-building game or go off to have lunch instead. Ultimately all mental activity is conducted by structures of this kind.

This is recognizably the way well-designed computer programs work, and it also bears a plausible resemblance to the way we do many things without thinking (when we move our arm we don’t think about muscle groups, but somehow somewhere they do get dealt with); but it isn’t a very intuitively appealing general model of human thought from an inside point of view. It naturally raises some difficulties about how to ensure that appropriate patterns of behaviour can be developed in novel circumstances. There are many problems which arise if we just leave the agents to slug it out amongst themselves – and large parts of the book are taken up with the interesting solutions Minsky has to offer. The real problem (as always) arises when we want to move out of the toy block world and deal with the howling gale of complexity presented by the real world.

Minsky’s solution is frames (often compared with Roger Schank’s similar strategy of scripts). We deal with reality through common sense, and common sense is, in essence, a series of sets of default assumptions about given events and circumstances. When we go to a birthday party, we have expectations about presents, guests, hosts, cakes and so on which give us a repertoire of appropriate to deploy and a context in which to respond to unfolding events. Alas, we know that common sense has so far proved harder to systematize than expected – so much so that these days the word ‘frame’ in a paper on consciousness is highly likely to be part of the dread phrase ‘frame problem’.

The idea that mental activity is constituted by a society of agents who themselves are not especially intelligent is an influential one, and Minsky’s version of it is well-developed and characteristically trenchant. He has no truck at all with the idea of a central self, which in his eyes is pretty much the same thing as an homunculus, a little man inside your head. Free will, for him, is a delusion which we are unfortunately stuck with. This sceptical attitude certainly cuts out a lot of difficulties, though the net result is perhaps that the theory deals better with unconscious processes than conscious ones. I think the path set out by Minsky stops short of a real solution to the problem of consciousness and probably cannot be extended without some unimaginable new development. That doesn’t mean it isn’t a worthwhile exercise to stroll along it, however.

Newton in doubtConsciousness is not a problem, says Michael Graziano in an Atlantic piece that is short and combative. (Also, I’m afraid, pretty sketchy in places. Space constraints might be partly to blame for that, but can’t altogether excuse some sweeping assertions made with the broadest of brushes.)

Graziano begins by drawing an analogy with Newton and his theory of light. The earlier view, he says, was that white light was pure, and colour happened when it was ‘dirtied’ by contact with the surfaces of coloured objects. The detail of exactly how this happened was a metaphysical ‘hard problem’. Newton dismissed all that by showing first, that white light is in fact a mixture of all colours, and second, that our vision produces only an inaccurate and simplified model of the reality, with only three different colour receptors.

Consciousness itself, Graziano says, is also a misleading model in a somewhat similar way, generated when the brain represents its own activity to itself. In fact, to be clear, consciousness as represented doesn’t happen; it is a mistaken construct, the result of the good-enough but far from perfect apparatus bequeathed to us by evolution (this sounds sort of familiar).

We should be clear that it is really Hard Problem consciousness that is the target here, the consciousness of subjective experience and of qualia. Not that the other sort is OK: Graziano dismisses the Easy Problem kind of consciousness, more or less in passing, as being no problem at all…

These days it’s not hard to understand how the brain can process information about the world, how it can store and recall memories, how it can construct self knowledge including even very complex self knowledge about one’s personhood and mortality. That’s the content of consciousness, and it’s no longer a fundamental mystery. It’s information, and we know how to build computers that process information.

Amazingly, that’s it. Graziano writes in an impatient tone; I have to confess to a slight ruffling of my own patience here; memory is not hard to understand? I had the impression that there were quite a number of unimpeachably respectable scientists working on the neurology of memory, but maybe they’re just doing trivial detail, the equivalent of butterfly collecting, or who knows, philosophy? …we know how to build computers… You know it’s not the 1980s any more? Yet apparently there are still clever people who think you can just say that the brain is a computer and that’s not only straightforwardly true, but pretty much a full explanation? I mean, the brain is also meat, and we know how to build tools that process meat; shall we stop there and declare the rest to be useless metaphysics?

‘Information’, as we’ve often noted before, is a treacherous, ambiguous word. If we mean something akin to data, then yes, computers can handle it; if we mean something akin to understanding, they’re no better than meat cleavers. Nothing means anything to a computer, while human consciousness reads and attributes meanings with prodigal generosity, arguably as its most essential, characteristic activity. No computer was ever morally responsible for anything, while our society is built around the idea that human beings have responsibilities, rights, and property. Perhaps Graziano has debunking arguments for all this that he hasn’t leisure to tell us about; the idea that they are all null issues with nothing worthwhile to be said about them just doesn’t fly.

Anyway, perhaps I should keep calm because that’s not even what Graziano is mainly talking about. He is really after qualia, and in that area I have some moderate sympathy with him; I think it’s true that the problem of subjective experience is most often misconceived, and it is quite plausible that the limitations of our sensory apparatus and our colour vision in particular contribute to the confusion. There is a sophisticated argument to be made along these lines: unfortunately Graziano’s isn’t it; he merely dismisses the issue: our brain plays us false and that’s it. You could perhaps get away with that if the problem were simply about our belief that we have qualia; it could be that the sensory system is just misinforming us, the way it does in the case of optical illusions. But the core problem is about people’s actual direct experience of qualia. A belief can be wrong, but an experience is still an experience even if it’s a misleading one, and the existence of any kind of subjective experience is the real core of the matter. Yes, we can still deny there is any such thing, and some people do so quite cogently, but to say that what I’m having now is not an experience but the mere belief that I’m having an experience is hard and, well, you know, actually rather metaphysical…

On examination I don’t think Graziano’s analogy with Newton works well. It’s not clear to me why the ‘older’ view is to be characterised as metaphysical (or why that would mean it was worthless). Shorn of the emotive words about dirt, the view that white light picks up colour from contact with coloured things, the way white paper picks up colour from contact with coloured crayons, seems a reasonable enough scientific hypothesis to have started with. It was wrong, but if anything it seems simpler and less abstract than the correct view. Newton himself would not have recognised any clear line between science and philosophy, and in some respects he left the true nature of light a more complicated matter, not fully resolved. His choice of particles over waves has proved to be an over-simplification and remains the subject of some cloudy ontology to this day.

Worse yet, if you think about it, it was Newton who first separated the two realms: colour as it is in the world and colour as we experience it. This is the crucial distinction that opened up the problem of qualia, first recognisably stated by Locke, a fervent admirer of Newton, some years after Newton’s work. You could argue therefore, that if the subject of qualia is a mess, it is a mess introduced by Newton himself – and scientists shouldn’t castigate philosophers for trying to clear it up.

intentional automatonJochen’s paper Von Neumann Minds: Intentional Automata has been published in Mind and Matter.

Intentionality is meaningfulness, the quality of being directed at something, aboutness. It is in my view one of the main problems of consciousness, up there with the Hard Problem but quite distinct from it; but it is often under-rated or misunderstood. I think this is largely because our mental life is so suffused with intentionality that we find it hard to see the wood for the trees; certainly I have read more than one discussion by very clever people who seemed to me to lose their way half-way through without noticing and end up talking about much simpler issues.

That is not a problem with Jochen’s paper which is admirably clear.  He focuses on the question of how to ground intentionality and in particular how to do so without falling foul of an infinite regress or the dreaded homunculus problem. There are many ways to approach intentionality and Jochen briefly mentions and rejects a few (basing it in phenomenal experience or in something like Gricean implicature, for example) before introducing his own preferred framework, which is to root meaning in action: the meaning of a symbol is, or is to be found in, the action it evokes. I think this is a good approach; it interprets intentionality as a matter of input/output relations, which is clarifying and also has the mixed blessing of exposing the problems in their worst and most intractable form. For me it recalls the approach taken by Quine to the translation problem – he of course ended up concluding that assigning certain meanings to unknown words was impossible because of radical under-determination; there are always more possible alternative meanings which cannot be eliminated by any logical procedure. Under-determination is a problem for many theories of intentionality and Jochen’s is not immune, but his aim is narrower.

The real target of the paper is the danger of infinite regress. Intentionality comes in two forms, derived on the one hand and original or intrinsic on the other. Books, words, pictures and so on have derived intentionality; they mean something because the author or the audience interprets them as having meaning. This kind of intentionality is relatively easy to deal with, but the problem is that it appears to defer the real mystery to the intrinsic intentionality in the mind of the person doing the interpreting. The clear danger is that we then go on to defer the intentionality to an homunculus, a ‘little man’ in the brain who again is the source of the intrinsic intentionality.

Jochen quotes the arguments of Searle and others who suggest that computational theories of the mind fail because the meaning and even the existence of a computation is a matter of interpretation and hence without the magic input of intrinsic intentionality from the interpreter fails through radical under-determination. Jochen dramatises the point using an extension of Searle’s Chinese Room thought experiment in which it seems the man inside the room can really learn Chinese – but only because he has become in effect the required homunculus.

Now we come to the really clever and original part of the paper; Jochen draws an analogy with the problem of how things reproduce themselves. To do so it seems they must already have a complete model of themselves inside themselves… and so the problem of regress begins. It would be OK if the organism could scan itself, but a proof by Svozil seems to rule that out because of problems with self-reference.  Jochen turns to the solution proposed by the great John Von Neumann (a man who might be regarded as the inventor of the digital computer if Turing had never lived). Von Neumann’s solution is expressed in terms of a tw0-dimensional cellular automaton (very simplistically, a pattern on a grid that evolves over time according to certain rules – Conway’s Game of Life surely provides the best-known examples). By separating the functions of copying and interpretation, and distinguishing active and passive states Von Neumann managed to get round Svozil successfully.

Now by importing this distinction between active and passive into the question of intentionality, Jochen suggests we can escape the regress. If symbols play either an active or a passive role (in effect, as semantics or as syntax) we can have a kind of automaton which, in a clear sense, gives its own symbols their interpretation, and so escapes the regress.

This is an ingenious move. It is not a complete solution to the problem of intentionality (I think the under-determination monster is still roaming around out here), but it is a novel and very promising solution to the regress. More than that, it offers a new perspective which may well offer further insights when fully absorbed; I certainly haven’t managed to think through what the wider implications might be, but if a process so central to meaningful thought truly works in this unexpected dual way it seems there are bound to be some. For that reason, I hope the paper gets wide attention from people whose brains are better at this sort of thing than mine…

miceMale and female brains are pretty much the same, but male and female behaviour is different. It turns out that the same neural circuitry exists in both, but is differently used.

A word of caution. We are talking about mice, in the main: those obliging creatures who seem ready to provide evidence to back all sorts of fascinating theories that somehow don’t transfer to human beings. And we’re also talking specifically about parental behaviour patterns; it seems those are rather well conserved between species – up to a point – but we shouldn’t generalise recklessly.

Catherine Dulac of Harvard explains the gist in this short Scientific American piece. A particular network of neurons in the hypothalamus was observed to be active during nurturing parental behaviour by females; by genetic engineering (amazing what we can do these days) those neurons were edited out of some females who then showed no caring behaviour towards infants. Meanwhile a group of males in which those neurons were stimulated (having been made light-sensitive by even more remarkable genetic manipulation) did show nurturing behaviour.

For male mammals it seems the norm is to kill strange infants on sight (I did say we should be careful about extrapolating to human beings); another set of neurons in the hypothalamus proves to be associated with this behaviour in just the same kind of way as the ones associated with nurturing behaviour.

One of the interesting things here is that both networks exist in both sexes; no-one knows at the moment why one is normally active in females and the other in males. If we were talking about human beings we should be tempted to attribute the difference to cultural factors (I hope that by now nobody is going to be astonished by the idea that different cultural influences could lead to different patterns of physical activity in the brain); it doesn’t seem very plausible that that could be the case for mice. It goes without saying that to identify a new hidden factor which sets certain gender roles in mice would inevitably trigger a highly-charged discussion of the possible equivalent in human beings.

So much for the proper research. Could we dare to venture on the irresponsibly speculative hypothesis that men and women habitually think somewhat differently but that each is fully capable of thinking like the other? I shouldn’t care to advance that thesis and the whole topic of measuring the quality and style of thought processes is deeply fraught scientifically and beset with difficulty philosophically.

There is, though, one rather striking piece of evidence to suggest that men and women can enter fully into each others minds; novels. Human consciousness is often depicted in novels; indeed the depiction may be the central feature or even pretty much the whole of the enterprise. Jane Austen, who arguably played a major role in making consciousness the centre of narrative, never wrote a scene in which two men converse in the absence of women, allegedly because she considered she could have no direct experience of how men talked to one another in those circumstances. Moreover, while she was exceptionally skilful at discreetly incorporating a view from inside her heroines’ heads, she never did the same for Darcy or Mr Knightley.

But others have never been so restrained; male authors have depicted the inward world of females and vice versa with very few complaints; that rather suggests we can swap mental gender roles without difficulty.

But are we sure? I suppose it could be argued that as a man I have no more access to the minds of other men than to those of women, so to a degree I actually have to take it on trust that the male mind is accurately depicted in novels. In some cases, certain allegedly typical male thought patterns depicted in books (Nick Hornby choosing a routine football match over a good friend’s wedding) are actually rather hard for me to enter into sympathetically. For that matter I recall the indignant rebuttal I got from a female fan when I suggested that Robert Heinlein’s depiction of the female mind might be slightly off the mark. Perhaps, then, none of us knows anything about the matter for sure in the end. Still I think nil humanum me alienum puto (I think nothing human alien to me) is a good motto and, I’m slightly encouraged to think, an attainable aspiration.