Download Artificial Knowing: Gender and the Thinking Machine by Alison Adam PDF

By Alison Adam

Artificial Knowing demanding situations the masculine slant within the man made Intelligence (AI) view of the realm. Alison Adam admirably fills the massive hole in technology and know-how stories by means of displaying us that gender bias is inscribed in AI-based computers. Her therapy of feminist epistemology, targeting the information of the understanding topic, the character of data, rationality and language, are guaranteed to make an important and strong contribution to AI studies.
Drawing from theories via Donna Haraway and Sherry Turkle, and utilizing instruments of feminist epistemology, Adam presents a sustained critique of AI which curiously re-enforces some of the conventional criticisms of the AI venture. Artificial Knowing is an esential learn for these attracted to gender reviews, technology and expertise stories, and philosophical debates in AI.

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Additional info for Artificial Knowing: Gender and the Thinking Machine

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We gradually acquired the feeling for things such as when to brake coming to a junction, when to turn the wheel, change gear and so on. This points to a crucial aspect of connectionist systems. Networks can only ‘learn’ with an operator saying what is right and that particular aspect of learning only forms a part of human learning. Often we know without being told and often we can be told without ever being able to do it.

It can be contrasted with the symbolic approach in that it does not attempt to model cognition at the symbolic level, rather, it models the subsymbolic operations of the brain, focusing instead on the neurological level (Bechtel and Abrahamsen 1991). The domain of enquiry has been variously termed connectionism, parallel distributed processing (PDP) or neural networks and it is based on the idea that the human brain offers a natural model for the possibility of building intelligent machines. Connectionism offers the hope of simulating the brain directly on a computer through the use of ‘artificial neurons’ (Rich and Knight 1991: 487).

Behaviourism (Watson 1925; Skinner 1953) is inextricably linked to the earlier forms of computational connectionism and it is clearly this aspect which some AI researchers dislike. Behaviourist models are based on the idea that entities and associations are limited to what can be observed by the scientific investigator, namely stimuli, reinforcements and so on, and the observed behavioural responses of the organism. For instance, a laboratory rat could be conditioned into providing the response of pulling a lever by being given the stimulus of food.

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