Philosophy of Cognition: Topic5
A Brief Intro
As discussed in Topic 4, the major limitation of the CTM is that it completely dismisses any role play by the environment (including other people as part of it). In this Topic we will try to see an alternative way to look at cognition, the extended mind hypothesis. The main argument goes like this: the environment plays a specific role not only in enhancing pre-existing cognitive tasks (like for instance storing or remembering information), but also in shaping our cognition. Consider, for instance, writing. Writing is not just a way of storing ideas, but also a powerful means for transforming them. More specifically, by writing, people can externally reproduce something that they have only within the isolated brain and make it more visible. Once they have externalized their thoughts in external objects, people can work on them and develop new concepts and new ways of thinking.
The extended mind hypothesis (or distributed cognition) questions many assumptions of the CTM. For instance, why should there be a magic boundary separating the “skull” from the rest of the universe? Is there something magic in it? Why should we pinpoint the cognizer? Is there any advantage in doing so? The distributed or extended approach to cognition clearly states that there is no magic boundary, as almost any cognitive activity is distributed across the environment, which acquires a cognitive meaning in the interaction with the human brain. In this sense, the distributed cognition approach looks at a broader class of cognitive events and does not expect cognitive capabilities to be encompassed by the skin or skull of an individual. So, why do we assign a kind of magical role to our isolated brain? The reason is that our brain is just more “portable” than any other cognitive resource, say, it is always with us. But in a way our brain and the environment work together for "making us smart".
Another major difference with the CTM is about the role assigned to action and its relation with perception. The CTM claims that the information can guide behavior only if it is represented - encoded in the organism. Motor activity - that is, action - is only initiated at the endpoint of a very complex process in which a detailed representation is created. The distributed cognition approach calls that into doubt by providing another account. That is, action - what we do - is part of our cognition, as action guides perception and vice versa. They engage each other in a specific activity in which perceptual controlled explorations take place. For instance, our eye movements are directed to obtain more information and in turn they are influenced by the information we can get. In the case haptic perception, action is an intrinsic part. Think of for instance the amount of information we constantly get from various manipulations like hefting, rubbing, running fingers, squeezing, etc.
That being said, the image of cognition is profoundly altered. Cognition is not something that only happens within our skull. But it is a distributed or extended phenomenon, which should be investigated by pulling down the boundaries between our head and all other external resources around us.
Analyze a case that fairly represents the idea of distributed cognition.
What are the main principles of the distributed approach to cognition?
What is the role assigned to the environment by the distributed approach to cognition?
Edwin Hutchins, Distributed Cognition. Available at: http://files.meetup.com/410989/DistributedCognition.pdf
Yvonne Rogers, A Brief Introduction to Distributed Cognition. Available at: http://mcs.open.ac.uk/yr258/papers/dcog/dcog-brief-intro.pdf
E. Bardone, Moving the Bonds: Distributing Cognition through Cognitive Niche Construction. In E. Bardone, Seeking Chances. From Biased Rationality to Distributed Cognition, Springer, Heidelberg, 2011.
R.D. Rupert, Part I: The Thinking Organism. In R.D: Rupert, Cognitive Systems and the Extended Mind, Oxford University Press, Oxford, 2009.
L. Magnani, Beyond Mind: How Brains Make up Artificial Cognitive Systems, Minds and Machines 19(4), 2009.