Artificial Intelligence

    

Transparency and Granularity in the SP Theory of Intelligence and Its Realisation in the SP Computer Model

Authors: J. Gerard Wolff

This chapter describes how the SP System, meaning the SP Theory of Intelligence, and its realisation as the SP Computer Model, may promote transparency and granularity in AI, and some other areas of application. The chapter describes how transparency in the workings and output of the SP Computer Model may be achieved via three routes: 1) the program provides a very full audit trail for such processes as recognition, reasoning, analysis of language, and so on. There is also an explicit audit trail for the unsupervised learning of new knowledge; 2) knowledge from the system is likely to be granular and easy for people to understand; and 3) there are seven principles for the organisation of knowledge which are central in the workings of the SP System and also very familiar to people (eg chunking-with-codes, part-whole hierarchies, and class-inclusion hierarchies), and that kind of familiarity in the way knowledge is structured by the system, is likely to be important in the interpretability, explainability, and transparency of that knowledge. Examples from the SP Computer Model are shown throughout the chapter.

Comments: 37 Pages. As of 2020-09-02, this document has been accepted for publication as a chapter in the book Interpretable Articial Intelligence: A Perspective of Granular Computing, to be published by Springer-Verlag and edited by Witold Pedrycz and Shyi-Ming Chen.

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[v1] 2020-09-08 08:49:43

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