Simplification without Falsification: The Problem of Relevance in Logic an AI

This chapter discusses the problem of how to simplify complex information without falsification, as it arises for AI, in light of Wittgenstein’s philosophy of logic. The capacity to simplify without falsifying seems crucial for AI systems that could be regarded as intelligent in that this seems to be what is required for picking out what is relevant from complex information. In short, what can be left out without falsification is that which is not relevant (essential, important or significant), and in general simplification without falsification requires that whatever is relevant (essential, important or significant) is taken into account. However, the notion of relevance in turn assumes or involves the perception of things being significant or that they matter, which is connected with the acting or thinking agent or entity having goals, purposes or interests. Thus, to get an AI system to simplify without falsifying, and to make it able to handle complex information in an intelligent way in this sense, seems to require that the behaviour of such a system is informed by goals, purposes or interests. I conclude with observations about what this involves.