Alan Turing and the “hard” and “easy” problem of cognition: doing and feeling

The "easy" problem of cognitive science is explaining how and why we can do what we can do. The "hard" problem is explaining how and why we feel. Turing's methodology for cognitive science (the Turing Test) is based on doing: Design a model that can do anything a human can do, indistinguishably from a human, to a human, and you have explained cognition. Searle has shown that the successful model cannot be solely computational. Sensory-motor robotic capacities are necessary to ground some, at least, of the model's words, in what the robot can do with the things in the world that the words are about. But even grounding is not enough to guarantee that -- nor to explain how and why -- the model feels (if it does). That problem is much harder to solve (and perhaps insoluble)

Can we prove that there are computational correlates of consciousness in the brain?

Scientific research on consciousness is attempting to gather data about the relationship between consciousness and the physical world. The basic procedure is to measure consciousness through first-person reports, measure the physical world and look for correlations between these sets of measurements. While most of this work has focused on neural correlates of consciousness, it has also been proposed that consciousness is linked to the computations that are being executed by the brain. If this is the case, we would expect there to be a high level of correlation between some of the brain’s computations and consciousness. This could be scientifically tested if a plausible method for measuring computations could be found. This paper investigates whether Chalmers’ method for identifying computations could be used to measure computations during an experiment on the correlates of consciousness. A number of arguments are used to show that Chalmers’ account of implementation fails for a desktop computer, which makes it unlikely that it could be used to identify computational correlates of consciousness in the brain. While a different account of implementation might be able to rescue computational approaches to consciousness, the problems raised in this paper suggest that it is going to be difficult to develop a method for measuring computations that could be used to test whether there are computational correlates of consciousness in the brain

Can we prove that there are computational correlates of consciousness in the brain?

Scientific research on consciousness is attempting to gather data about the relationship between consciousness and the physical world. The basic procedure is to measure consciousness through first-person reports, measure the physical world and look for correlations between these sets of measurements. While most of this work has focused on neural correlates of consciousness, it has also been proposed that consciousness is linked to the computations that are being executed by the brain. If this is the case, we would expect there to be a high level of correlation between some of the brain’s computations and consciousness. This could be scientifically tested if a plausible method for measuring computations could be found. This paper investigates whether Chalmers’ method for identifying computations could be used to measure computations during an experiment on the correlates of consciousness. A number of arguments are used to show that Chalmers’ account of implementation fails for a desktop computer, which makes it unlikely that it could be used to identify computational correlates of consciousness in the brain. While a different account of implementation might be able to rescue computational approaches to consciousness, the problems raised in this paper suggest that it is going to be difficult to develop a method for measuring computations that could be used to test whether there are computational correlates of consciousness in the brain

The causal topography of cognition

The causal structure of cognition can be simulated but not implemented computationally, just as the causal structure of a furnace can be simulated but not implemented computationally. Heating is a dynamical property, not a computational one. A computational simulation of a furnace cannot heat a real house (only a simulated house). It lacks the essential causal property of a furnace. This is obvious with computational furnaces. The only thing that allows us even to imagine that it is otherwise in the case of computational cognition is the fact that cognizing, unlike heating, is invisible (to eveyrone except the cognizer). Chalmers’s “Dancing Qualia” Argument is hence invalid: Even if there could be a computational model of cognition that was behaviorally indistinguishable from a real, feeling cognizer, it would still be true that if, like heat, feeling is a dynamical property of the brain, a flip-flop from the presence to the absence of feeling would be undetectable anywhere along Chalmers’s hypothetical component-swapping continuum from a human cognizer to a computational cognizer -- undetectable to everyone except the cognizer. But that would only be because the cognizer was locked into being incapable of doing anything to settle the matter simply because of Chalmers’s premise of input/output indistinguishability. That is not a demonstration that cognition is computation; it is just the demonstration that you get out of a premise what you put into it. But even if the causal topography of feeling, hence of cognizing, is dynamic rather than just computational, the problem of explaining the causal role played by feeling itself – how and why we feel – in the generation of our behavioral capacity – how and why we can do what we can do – will remain a “hard” (and perhaps insoluble) problem