David Chalmers

To make progress on the problem of consciousness, we have to confront it directly. In this paper, I first isolate the truly hard part of the problem, separating it from more tractable parts and giving an account of why it is so difficult to explain. I critique some recent work that uses reductive methods to address consciousness, and argue that such methods inevitably fail to come to grips with the hardest part of the problem. Once this failure is recognized, the door to further progress is opened. In the second half of the paper, I argue that if we move to a new kind of nonreductive explanation, a naturalistic account of consciousness can be given. I put forward my own candidate for such an account: a nonreductive theory based on principles of structural coherence and organizational invariance, and a double-aspect theory of information.

The project that Dan Lloyd has undertaken is admirable and audacious. He has tried to boil down the substrate of information-processing that underlies conscious experience to some very simple elements, in order to gain a better understanding of the phenomenon. Some people will suspect that by considering a model as simple as a connectionist network, Dan has thrown away everything that is interesting about consciousness. Perhaps there is something to that complaint, but I will take a different tack. It seems to me that if we apply his own reasoning, we can see that Dan has not taken things far _enough_. When we have boiled things down to a system as simple as a connectionist network, it seems faint-hearted to stop there, and perhaps a little arbitrary as well. So I will take things further, and ask what seems to be the really interesting question in the vicinity: what is it like to be a thermostat?

It's very interesting to see neurophysiological evidence brought to bear on the puzzling question of conscious experience. Many have observed that information-processing models of cognition seem to leave consciousness untouched; it is natural to hope that turning to neurophysiology might lead us to the Holy Grail. Still, I think there are reasons to be skeptical. There are good reasons to suppose that neurophysiological investigation contributes to cognitive explanation at best in virtue of constraining the information-processing structure of cognition. Of course this is a very large and significant role for it to play, but it may be over-optimistic to suppose that it can play some further explanatory role, taking us where information-processing theories cannot. If so, then neurophysiological accounts will be no more and no less successful at dealing with consciousness than information-processing accounts are.

What follows are compressed versions of three lectures on the subject of "Mind and Modality", given at Princeton University the week of October 12-16, 1998. The first two form a series; the third stands alone to some extent. All are philosophically technical, and probably of interest mainly to philosophers. I hope that they make sense, at least to those familiar with my book _The Conscious Mind_. Lecture 1 recapitulates some of the material in the book in a somewhat different form, and adds some further material on conditionals and on Kripke. Note that section has a more or less definitive formalization of the anti-materialist argument from the book. Lecture 2 pushes deeper into the heart of modality, further investigating the conceivability/possibility relationship and the epistemology of modality, and arguing for a sort of modal rationalism. Lecture 3 gives an analysis of the content of beliefs about experiences, and applies this to a number of epistemological issues, including incorrigibility and the dialectic on "The Myth of the Given".

A natural way to think about epistemic possibility is as follows. When it is epistemically possible (for a subject) that p, there is an epistemically possible scenario (for that subject) in which p. The epistemic scenarios together constitute epistemic space. It is surprisingly difficult to make the intuitive picture precise. What sort of possibilities are we dealing with here? In particular, what is a scenario? And what is the relationship between scenarios and items of knowledge and belief? This chapter tries to make sense of epistemic space. It explores different ways of making sense of scenarios and of their relationship to thought and language. It discusses some issues that arise and outlines some applications to the analysis of the content of thought and the meaning of language.

Computation is central to the foundations of modern cognitive science, but its role is controversial. Questions about computation abound: What is it for a physical system to implement a computation? Is computation sufficient for thought? What is the role of computation in a theory of cognition? What is the relation between different sorts of computational theory, such as connectionism and symbolic computation? In this paper I develop a systematic framework that addresses all of these questions. Justifying the role of computation requires analysis of implementation, the nexus between abstract computations and concrete physical systems. I give such an analysis, based on the idea that a system implements a computation if the causal structure of the system mirrors the formal structure of the computation. This account can be used to justify the central commitments of artificial intelligence and computational cognitive science: the thesis of computational sufficiency, which holds that the right kind of computational structure suffices for the possession of a mind, and the thesis of computational explanation, which holds that computation provides a general framework for the explanation of cognitive processes. The theses are consequences of the facts that (a) computation can specify general patterns of causal organization, and (b) mentality is an organizational invariant, rooted in such patterns. Along the way I answer various challenges to the computationalist position, such as those put forward by Searle. I close by advocating a kind of minimal computationalism, compatible with a very wide variety of empirical approaches to the mind. This allows computation to serve as a true foundation for cognitive science.

The book is an extended study of the problem of consciousness. After setting up the problem, I argue that reductive explanation of consciousness is impossible, and that if one takes consciousness seriously, one has to go beyond a strict materialist framework. In the second half of the book, I move toward a positive theory of consciousness with fundamental laws linking the physical and the experiential in a systematic way. Finally, I use the ideas and arguments developed earlier to defend a form of strong artificial intelligence and to analyze some problems in the foundations of quantum mechanics.