Abstract
By now it is an old story: legal scholarship in the English-speaking world about the law of evidence began to change in the late 1960s and early 1970s. This shift in the direction of Evidence scholarship came to be known as the ‘New Evidence Scholarship’—‘NES’, for short. A characteristic (but not universal) feature of much of NES—particularly in the early days—was a preference for formal mathematical argument about evidence and inference and about decisions based on uncertain evidence and inference. NES aroused controversy from the moment of its birth (or rebirth). Laurence Tribe almost succeeded in turning NES into an example of sudden infant death syndrome; his powerful 1971 attack on ‘trial by mathematics’ almost succeeded in killing off the baby.1 Other observers, while not necessarily rejecting the need for a shift in the direction of Evidence scholarship, followed the anti-mathematicist trail that Tribe had blazed. (But scholars such as Richard Lempert, David Kaye and David Schum saved the mathematicist branch of the new scholarship from premature oblivion.2) Many of the attacks on mathematical analysis of evidential inference were misdirected; many of them—probably the vast majority of them—rested on basic misunderstandings about the nature and possible uses of mathematics. (Some critics seemed to assume that numbers are only good for counting. Other observers seemed to assume that all mathematical expressions amount to recipes for solving problems.) But some of the attacks on mathematical argument about evidence and inference harboured, even if not always distinctly, intuitions that seem to have considerable substance. One such intuition is that it makes little sense to ask people such as jurors to use a method of analysis or argument—such as Bayesianism—that is beyond their ‘common’, or ‘ordinary’, understanding.3 Another important intuition is that the nuances and complexities of real-world evidence and inference are too great to be captured by any type of formal analysis. Both of these intuitions involve assumptions about the cognitive capacities of human beings and the human brain. One reason I am interested in visualization of evidence and inference is that I suspect and hope that visualization of evidence and inference can make the logic of formal analytical
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