Tag Archives: Stanford

Stanford Consciousness

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cakeThe Stanford Encyclopaedia of Philosophy is twenty years old. It gives me surprisingly warm feelings towards Stanford that this excellent free resource exists. It’s written by experts, continuously updated, and amazingly extensive. Long may it grow and flourish!

Writing an encyclopaedia is challenging, but an encyclopaedia of philosophy must take the biscuit. For a good encyclopaedia you need a robust analysis of the topics in the field so that they can be dealt with systematically, comprehensively, and proportionately. In philosophy there is never a consensus, even about how to frame the questions, never mind about what kind of answers might be useful. This must make it very difficult: do you try to cover the most popular schools of thought in an area? All the logically possible positions one might take up?  A purely historical survey? Or summarise what the landscape is really like, inevitably importing your own preconceptions?

I’ve seen people complain that the SEP is not very accessible to newcomers, and I think the problem is partly that the subject is so protean. If you read an article in the SEP, you’ll get a good view and some thought-provoking ideas; but what a noob looks for are a few pointers and landmarks. If I read a biography I want to know quickly about the subject’s  main works, their personal life, their situation in relation to other people in the field, the name of their theory or school, and so on.  Most SEP subject articles cannot give you this kind of standard information in relation to philosophical problems. There is a real chance that if you read up a SEP article and then go and talk to professionals, they won’t really get what you’re talking about. They’ll look at you blankly and then say something like:

“Oh, yes, I see where you’re coming from, but you know, I don’t really think of it that way…”

It’s not because the article you read was bad, it’s because everyone has a unique perspective on what the problem even is.

Let’s look at Consciousness. The content page has:

consciousness (Robert Van Gulick)

  • animal (Colin Allen and Michael Trestman)
  • higher-order theories (Peter Carruthers)
  • and intentionality (Charles Siewert)
  • representational theories of (William Lycan)
  • seventeenth-century theories of (Larry M. Jorgensen)
  • temporal (Barry Dainton)
  • unity of (Andrew Brook and Paul Raymont)

All interesting articles, but clearly not a systematic treatment based on a prior analysis. It looks more like the set of articles that just happened to get written with consciousness as part of the subject. Animal consciousness, but no robot consciousness? Temporal consciousness, but no qualia or phenomenal consciousness? But I’m probably looking in the wrong place.

In Robert Van Gulick’s main article we have something that looks much more like a decent shot at a comprehensive overview, but though he’s done a good job it won’t be a recognisable structure to anyone who hasn’t read this specific article. I really like the neat division into descriptive, explanatory, and functional questions; it’s quite helpful and illuminating: but you can’t rely on anyone recognising it (Next time you meet a professor of philosophy ask him: if we divide the problems of consciousness into three, and the first two are descriptive and explanatory, what would the third be? Maybe he’ll say  ‘Functional’, but maybe he’ll say ‘Reductive’ or something else – ‘Intentional’ or ‘Experiential’; I’m pretty sure he’ll need to think about it). Under ‘Concepts of Consciousness’ Van Gulick has ‘Creature Consciousness’: our noob would probably go away imagining that this is a well-known topic which can be mentioned in confident expectation of the implications being understood. Alas, no: I’ve read quite a few books about consciousness and can’t immediately call to mind any other substantial reference to ‘Creature Consciousness’: I’m pretty sure that unless you went on to explain that you were differentiating it from ‘State Consciousness’ and ‘Consciousness as an Entity’, you might be misunderstood.

None of this is meant as a criticism of the piece: Van Gulick has done a great job on most counts (the one thing I would really fault is that the influence of AI in reviving the topic and promoting functionalist views is, I think, seriously underplayed). If you read the piece you  will get about as good a view of the topic as that many words could give you, and if you’re new to it you will run across some stimulating ideas (and some that will strike you as ridiculous). But when you next read a paper on philosophy of mind, you’ll still have to work out from scratch how the problem is being interpreted. That’s just the way it is.

Does that mean philosophy of mind never gets anywhere? No, I really don’t think so, though it’s outstandingly hard to provide proof of progress. In science we hope to boil down all the hypotheses to a single correct theory: in philosophy perhaps we have to be happy that we now have more answers (and more problems) than ever before.

And the SEP has got most of them! Happy Birthday!

Brain on a chip

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Following on from preceding discussion, Doru kindly provided this very interesting link to information about a new chip designed at MIT which is designed to mimic the function of real neurons.

I hadn’t realised how much was going on, but it seems MIT is by no means alone in wanting to create such a chip. In the previous post I mentioned Dharmendra Modha’s somewhat controversial simulations of mammal brains: under his project leadership IBM, with DARPA participation, is now also working on a chip that simulates neuronal interaction. But while MIT and IBM slug it out those pesky Europeans had already produced a neural chip as part of the FACETS project back in 2009. Or had they? FACETS is now closed and its work continues within the BrainScaleS project working closely with Henry Markram’s Blue Brain project at EPFL, in which IBM, unless I’m getting confused by now, is also involved. Stanford, and no doubt others I’ve missed, are involved in the same kind of research.

So it seems that a lot of people think a neuron-simulating chip is a promising line to follow; if I were cynical I would also glean from the publicity that producing one that actually does useful stuff is not as easy as producing a design or a prototype; nevertheless it seems clear that this is an idea with legs.

What are these chips actually meant to do? There is a spectrum here from the pure simulation of what real brains really do to a loose importation of a functional idea which might be useful in computation regardless of biological realism. One obstacle for chip designers is that not all neurons are the same. If you are at the realist end of the spectrum, this is a serious issue but not necessarily an insoluble one. If we had to simulate the specific details of every single neuron in a brain the task would become insanely large: but it is probable that neurons are to some degree standardised. Categorising them is, so far as I know, a task which has not been completed for any complex brain: for Caenorhabditis elegans, the only organism whose connectome is fully known, it turned out that the number of categories was only slightly lower than the number of neurons, once allowance was made for bilateral symmetry; but that probably just reflects the very small number of neurons possessed by Caenorhabditis (about 300) and it is highly likely that in a human brain the ratio  would be much more favourable. We might not have to simulate more than a few hundred different kinds of standard neuron to get a pretty good working approximation of the real thing.

But of course we don’t necessarily care that much about biological realism. Simulating all the different types of neurons might be a task like simulating real feathers, with the minute intricate barbicel latching structures – still unreplicated by human technology so far as I know – which make them such sophisticated air controllers, whereas to achieve flight it turns out we don’t need to consider any structure below the level of wing. It may well be that one kind of simulated neuron will be more than enough for many revolutionary projects, and perhaps even for some form of consciousness.

It’s very interesting to see that the MIT chip is described as working in a non-digital, analog way (Does anyone now remember the era when no-one knew whether digital or analog computers were going to be the wave of the future?). Stanford’s Neurogrid project is also said to use analog methods, while BrainScaleS speaks of non-Von Neumann approaches, which could refer to localised data storage or to parallelism but often just means ‘unconventional’. This all sounds like a tacit concession to those who have argued that the human mind was in some important respects non-computational: Penrose for mathematical insight, Searle for subjective experience, to name but two. My guess is that Penrose would be open-minded about the capacities of a non-computational neuron chip, but that Searle would probably say it was still the wrong kind of stuff to support consciousness.

In one respect the emergence of chips that mimic neurons is highly encouraging: it represents a nearly-complete bridge between neurology at one end and AI at the other. In both fields people have spoken of ‘connectionism’ in slightly different senses, but now there is a real prospect of the two converging. This is remarkable – I can’t think of another case where two different fields have tunnelled towards each other and met so neatly – and in its way seems to be a significant step towards the reunification of the physical and the mental. But let’s wait and see if the chips live up to the promise.