Mancosu - Philosophy of Mathematical Practice (Oxford, 2008).pdf

understanding proofs 335that to explain why certain procedures for long multiplication are effective.Computer scientists have developed a clever method called ‘carry save addition’that makes it possible for a microprocessor to perform operations on binaryrepresentations in parallel, and therefore multiply numbers more efficiently.Each theory is fruitfully applied in its domain of application; no overarchingphilosophy is needed.But this objection misses the point. Both the experimental psychologist andthe computer scientist presuppose a normative account of what it means tomultiply correctly, and our foundational accounts of arithmetic apply equallywell to humans and machines. In a similar way, a theory of mathematicalunderstanding should clarify the structural aspects of mathematics that characterizesuccessful performance for agents of both sorts. To be sure, when itcomes to verifying an inference, different sorts of agents will have differentstrengths and weaknesses. We humans use diagrams because we are goodat recognizing symmetries and relationships in information so represented.Machines, in contrast, can keep track of gigabytes of information and carry outexhaustive computation where we are forced to rely on little tricks. If we areinterested in differentiating good teaching practice from good programmingpractice, we have no choice but to relativize our theories of understanding tothe particularities of the relevant class of agents. But this does not precludethe possibility that there is a substantial theory of mathematical understandingthat can address issues that are common to both types of agent. Lightning fastcalculation provides relatively little help when it comes to verifying commonmathematical inferences; blind search does not work much better for computersthan for humans. Nothing, apriori, rules out that a general philosophicaltheory can help explain what makes it possible for either type of agent tounderstand a mathematical proof.In the next four sections, I will consider four types of inference that arecommonly carried out in mathematical proofs, and which, on closer inspection,are not as straightforward as they seem. In each case, I will indicate some ofthe methods that have been developed to verify such inferences automatically,and explore what these methods tell us about the mechanisms by which suchproofs are understood.12.6 Understanding inequalitiesI will start by considering inferences that are used to establish inequalities inordered number domains, like the integers or the real numbers. For centuries,