Sense and 'sensitivity': epistemic and instrumental approaches to statistical evidence.

AuthorEnoch, David
PositionIntroduction through II. The Theoretical Framework, p. 557-585

INTRODUCTION I. A Critical Review of Proposed Solutions to the Statistical EVIDENCE PUZZLE A. Exogenous-Factor Claims B. About-Relation Claims C. The Causal-Connection Argument D. Defendant-Specific Claims E. Justice-in-the-Particular-Case Claims F. Autonomy Considerations G. Social-Acceptability Considerations H. The Guaranteed-False-Conviction Argument II. THE THEORETICAL FRAMEWORK A. Justifying Beliefs or Actions?: We Require an Epistemic, Not a Practical, Framework B. Some Epistemology: Introducing "Sensitivity" C. From Epistemology to More Practical Concerns: Should the Law Care About Sensitivity (or Knowledge)? 1. The remaining puzzle: why care about knowledge? 2. Sanchirico on character evidence 3. Solution: the instrumental significance of being sensitive III. SOLVING SOME DOCTRINAL PUZZLES A. DNA Evidence B. Propensity-for-Crime Evidence at the Guilt Phase of Trial C. Incriminating Versus Exonerating Statistical Evidence D. Admissibility Versus Sufficiency of Statistical Evidence IV. PRESCRIPTIVE ANALYSIS CONCLUSION INTRODUCTION

"For nearly twenty years, law journals have been the forum for a bitter debate about the use at trial of overtly probabilistic evidence and methods," wrote Jonathan J. Koehler and Daniel N. Shaviro in 1990. (1) More than two decades have passed since then, but these words still hold true. Despite the voluminous body of literature dedicated to the issue of statistical evidence, it continues to generate great controversy in evidence law scholarship. Questions regarding the admissibility and sufficiency of statistical evidence arise in court with ever-growing frequency, with seemingly inconsistent treatment in the case law. (2) The aim of this Article is to dispel some of the confusion surrounding the use of statistical evidence in the legal arena by connecting the statistical evidence debate to broader epistemic discussions and by highlighting "Sensitivity"--that is, the requirement that a belief be counterfactually sensitive to the truth--as a way of epistemically explaining the suspicion toward statistical evidence. After exposing the epistemic distinctions between statistical and individualized evidence, the Article turns to examining their implications for the legal arena. We will use the epistemic discourse on Sensitivity as well as an instrumental analysis to address the descriptive and prescriptive challenges that statistical evidence poses.

One starting point for the statistical evidence debate is the classic Blue Bus hypothetical, (3) which is a variant of Smith v. Rapid Transit, Inc., (4) a seminal case in modern evidence law. The hypothetical consists of two cases. In both cases, a runaway bus injures the plaintiff, and the case goes to trial against the eponymous bus company. In the first case, the evidence includes eyewitness testimony that one of the Blue Bus Company's buses caused the injury. The witness, however, is imperfectly reliable. To illustrate, let us assume her to be 70% reliable in such circumstances. In the second case, however, there is no eyewitness to the accident. Instead, the plaintiff seeks to introduce evidence about the Blue Bus Company's market share in the area where the accident took place. The uncontested market share data show that the Blue Bus Company owns 70% of the buses in the relevant area. This, the plaintiff argues, shows that it is more likely that one of the Blue Bus Company's vehicles was involved in the accident, because Blue Bus is the largest bus company in the area with the greatest number of buses on the road.

Even though the evidence in both cases may be of equal probative value, our responses to the two cases are very different. Most people (lawyers and laypeople alike) find nothing problematic in basing a finding on the eyewitness evidence in the first case but are very reluctant to ground a finding on the market share evidence in the second case. (5) And many courts seem to agree. (6) Indeed, the second case closely resembles the Smith case mentioned above, in which the court rejected market share evidence as the basis for finding that the defendant's bus was responsible for the accident. (7)

But this now presents a problem. The Blue Bus hypothetical were carefully designed to keep all other things equal. This means, for instance, that relying on the two kinds of evidence will yield, over the long run, the same rate of mistaken decisions: in the words of the hypothetical, the percent chance that the witness mistook the color of the bus in the first case is equal to the market share of all other bus companies in the second case. And yet despite these similarities, almost everyone--judges and legal scholars, lawyers and laypeople alike--seems to draw a sharp distinction between eyewitness testimony and market share evidence, (8) even when all other things are held equal. How can such a discrepancy be explained? Why do we treat these kinds of evidence so differently? And can this intuitive distinction be vindicated? In other words, should we treat market share evidence and eyewitness testimony differently? If so, why? (9)

Consider the analogous gatecrasher hypothetical, (10) in which it is uncontested that of 1000 people attending a stadium event, only 10 purchased tickets. If any individual attending the event is sued for crashing the gate or, even more clearly, is prosecuted for such gatecrashing, a finding against him or her merely on the strength of the statistical evidence seems inappropriate. On the other hand, conviction based on a probabilistically similar piece of direct, individualized evidence, such as a videotape, seems perfectly fine.

The puzzle concerning the differential treatment of probabilistically equivalent statistical and individualized evidence, exemplified by these hypotheticals, surfaces in many different scenarios. This puzzle can appear in civil or criminal trials, arise with different levels of probability, relate to past or future events, and so on. (11)

Legal doctrine has failed to systematically resolve questions regarding the use of statistical evidence in court. In the first half of the twentieth century, when statistical evidence first began to appear in court, many judges responded antagonistically, deeming it inadmissible and devoid of any probative value. (12) To this day, courts continue to exhibit a general preference for individualized evidence and to reject base-rate evidence despite its potential to promote accuracy in legal factfinding. (13)

The doctrinal picture, however, is not clear-cut. First, the legal doctrine regarding the use of statistical evidence for imposing liability is incoherent, and there is conflicting case law on the matter. (14) Although statistical evidence is often considered irrelevant and thus inadmissible in court, (15) at other times, when presented as supplementary evidence, courts sometimes treat it as admissible. (16) In yet other instances, statistical evidence has even been treated as sufficient for a finding of liability. (17) For example, in contrast to the ruling in Smith, the appellate court in Kaminsky v. Hertz Corp. (18) ruled that the plaintiff had established a rebuttable presumption of ownership when the primary evidence brought forth against the defendant, Hertz, was unchallenged testimony that the yellow truck that had caused the accident at issue in the case bore a Hertz logo and that Hertz owned ninety percent of such trucks. (19)

Second, not only are there seemingly random inconsistencies in the court rulings on statistical evidence in the general class of cases, there are also exceptions to the general approach of inadmissibility in certain categories of cases. Such is the case, for example, with DNA profiling, which is explicitly statistical in nature. The standard DNA profile is extracted from only a small portion of the donor's entire DNA. So even under the assumption that a unique set of DNA characterizes each and every individual, two or more people can still share an identical DNA profile. (20) Despite its statistical nature, DNA evidence is increasingly relied on by the courts. (21) To date, most American courts admit DNA evidence despite its apparent similarities to other, inadmissible types of statistical evidence. (22) In light of the considerable inconsistency in the case law regarding the admissibility or sufficiency of statistical evidence, the extrapolation of the legal doctrine on this matter has been deemed "part science and part art." (23)

In addition to the inconsistencies in the legal doctrine, the legal scholarship is also fraught with discrepancies on this topic. The decision in Smith triggered a heated, ongoing debate in legal academia (24) around (1) whether judicial fact-finding ought to be grounded on standard probability logic and (2) whether statistical evidence regarding the base rate for liability is sufficient ground for a ruling in criminal or civil trials. (25) Koehler and Shaviro, for instance, question courts' refusal to ground verdicts in favor of plaintiffs or prosecutors on statistical evidence. (26) Shaviro claims that the objective of verdict accuracy requires that courts hold in favor of the party whose case seems more likely, (27) and that the only relevant misgivings about imposing liability are doubts related to risk of error, not those related to overtness. (28) But the evidence law scholars who advocate the use of statistical evidence are outnumbered by other legal academics who tend to strongly oppose statistical evidence and object to its submission in trial for reasons of probative deficiency, reasons of moral deficiency, or other policy reasons. (29)

The inconsistent treatment of statistical evidence in both legal doctrine and the evidence law literature has created a need for an overarching theory. The objective of this Article is to provide such a theoretical framework and to dispel some of the incoherence associated with the treatment of statistical evidence in trial.

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