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The Belief-filter Component

One of the goals of AI is to design and build an android who can pass undetected as he lives and interacts with human beings. Although this aim cannot be realised, it makes sense to design androids initially who have skills and abilities similar to those possessed by humans. Among such abilities is that of learning from other people. It is this that I consider in this paper. I propose a two-phase model of belief-acquisition. The first stage consists of a collection of easily applicable rules that are used to decide what to do with the many statements that a person hears and reads every day. The second stage comprises a critical methodology for the thorough investigation of a small number of selected theories. I argue that this methodology should be an anti-justificationist one. An android’s belief-filter component should reflect this two-stage model if he is to interact effectively with human beings.