Mind and Machine : Introduction



		In this course, we will describe some of the most recent attempts to build computers whose design and operation are modelled after the brain. In doing so, we shall attempt to address the question: Will it ever be possible to build a machine which possesses a mind? To answer this question we shall need to ask ourselves some further questions: Is the Mind a machine? What is intelligence? Can computers think? Is there any notion of personal responsibility for a computer? To start off, we shall go on a brief tour of the Biology of the Brain. We will describe the overall structure of the human brain and the elements of which it is made - nerve cells or neurons. We will see how neurons are connected up into complicated networks, whose function is to process electrical signals which constitute all brain activity. Motivated by this biological description, we will examine artificial Neural Networks, which have been proposed as an alternative route to achieving artificial intelligence. We will try to describe how two such popular networks work - the Hopfield and Perceptron models. These networks can perform tasks such as memory recall, pattern recognition, and simple decision making. Some of the features of these networks, particularly those associated to learning are very reminiscent of similar processes in the brain. Finally, we shall discuss some of the features we would expect to find in an intelligent machine. Are consciousness and the mind somehow distinct from the physical workings of the brain? How might we ascertain whether a machine was conscious? What must a neural network be capable of to stand a chance of being truly intelligent? A discussion of these issues in artificial intelligence will constitute the last part of this course.