University of Glasgow

Reid Room, Philosophy Building

67 Oakfield Avenue

University of Glasgow, G12 8LP

Michael Blome-Tillmann (Cambridge/Montreal)

Anna-Maria Eder (Duisburg-Essen)

Andrew Higgins (Oxford)

Federico Picinali (LSE)

Mike Redmayne (LSE)

Martin Smith (Glasgow)

Levi Spectre (Open University of Israel)

About the workshop

It is often observed that courts are unwilling to reach affirmative verdicts – verdicts of guilt or liability – on the basis of evidence that is purely statistical in nature. At least two things are puzzling about this. First, when compared to other sorts of evidence given considerable weight in court, such as eye witness testimony, statistical evidence can raise the probability of guilt or liability to a higher level. Second, statistical evidence seems capable of meeting the standards of proof codified in legal doctrine – such as the balance of probabilities standard that is officially applied in civil trials.

Statistical evidence also lies at the heart of a number of long standing puzzles in epistemology. According to a widespread view, beliefs based upon purely statistical evidence cannot constitute knowledge, though beliefs based on testimony, perceptual experience, memory etc. can – even though these latter kinds of evidence may be probabilistically weaker. And, while many epistemologists agree that beliefs based upon purely statistical evidence can at least be justified, even this claim leads us straight into the lottery and preface paradoxes.

The aim of this workshop is to bring together epistemologists, philosophers of law, legal theorists and legal practitioners for an event dedicated to this topic of common interest.

Registration is free, but places are limited. To register please contact Martin Smith:

9:30 - 10:00 Coffee and Registration

10:00 - 11:30 Federico Picinali (LSE) 'From Quantitative Variables to Categorical Verdicts: What is Gained and What is Lost in Translation'.

11:30 - 13:00 Michael Blome-Tillmann (Cambridge/McGill) 'Statistical Evidence and E=K'

13:00 - 14:00 Lunch

14:00 - 15:30 Anna-Maria Eder (Duisburg-Essen) 'Evidential support, beliefs and credences'

15:30 - 16:00 Coffee

16:00 - 17:30 Martin Smith (Glasgow) 'When Does Evidence Suffice for Conviction?'

18:30 - Dinner

9:30 - 10:00 Coffee

10:00 - 11:30 Levi Spectre (Open University of Israel) 'A Characterisation of Statistical Evidence and Its Implications'

11:30 - 12:30 Andrew Higgins (Oxford) 'Statistical Evidence in Mass Harm Cases'

12:30 - 13:30 Lunch

Postgraduate Bursaries

We have six travel & accommodation bursaries available for Graduate students wishing to attend the workshop (up to £80 per student). If you wish to be considered for a studentship please indicate this when registering.

The event is sponsored by the AHRC, Scots Philosophical Association, University of Glasgow, and the University of Stirling

Anna Maria Asunta Eder (Duisburg-Essen)

Internalists about (epistemic) rationality typically endorse the following evidentialist characterisation of rationality: (Evi) It is rational that an agent S with total evidence e believes a proposition p if and only if p is supported by e for S with e. The best-developed and most widely accepted account of evidential support is, then, spelled out in terms of probabilities: (ES) A proposition p is supported by an agent S's evidence e for S with e if and only if the probability of p on e for S with e is high. The probability of a proposition given some evidence is commonly interpreted in terms of credences and, thus, in internalist terms.

This whole internalist approach is threatened by Wiliamson, who argues that the probability in question cannot be adequately interpreted in terms of credences. According to him it can neither be interpreted in terms of credences of human agents nor in terms of credences of ideal agents (2002: 209--11). Based on this, Williamson suggests an interpretation in terms of objective probabilities. The respective conception of evidential support is externalist.

I defend the internalist approach against Williamson. The probability of a proposition given some evidence can be adequately interpreted in terms of credences, namely, in terms of rational credences. The rationality of credences is specified in deontic terms. The respective interpretation turns out to be as required by internalists who are committed to (Evi) and (ES).

STATISTICAL EVIDENCE AND E = K

Abstract TBA

STATISTICAL EVIDENCE IN MASS HARM CASES

The claim that statistical evidence can be sufficient to establish causation between a defendant’s wrong and a claimant’s injuries is arguably at its strongest in mass harm cases. In such cases, if the epidemiological evidence is robust it can establish not only that there is a possibility, or even a probability, that the defendant caused harm, but the fact of the defendant causing harm. Yet while the epidemiological evidence may establish that some members of the class have been injured by the defendant, it still cannot tell us which members of the class have been injured by the defendant.

This paper will examine some of the approaches taken by courts to causation in mass harm cases including: the material increase in risk liability theory; the doubling the risk liability theory, policy based decisions to bridge the evidentiary causation ‘gap’; liability only to the extent a defendant has increased risk to the claimant, and no liability based on a traditional ‘but for’ analysis.

It will argue that where reliable statistical evidence establishes that X is a cause of Y, it is legitimate to hold the defendant liable to all persons who can establish, by independent evidence, that they have Y, that they were exposed to X and that the defendant has materially contributed to X. Whether the defendant should be held liable in full or to the extent they increased the risk of harm raises difficult policy questions about the role of deterrence, corrective justice, and risk allocation in the law. There are strong arguments for both approaches but liability linked to extent of the increased risk has the advantage of at least partially furthering of all of these objectives.

FROM QUANTITATIVE VARIABLES TO CATEGORICAL VERDICTS: WHAT IS GAINED AND WHAT IS LOST IN TRANSLATION

In order to deliver the verdict fact finders in criminal trials must translate quantitative variables into a categorical variable. There is no room in the verdict for probabilities and degrees of belief on the hypothesis of guilt or concerning key items of evidence. Verdicts express a categorical variable: either the defendant is guilty or she isn’t. There are a few arguments in favour of categorical verdicts, the most well-known focusing on the public perception of justice. However, categorical verdicts have their costs too, especially in terms of the accuracy that is lost in the translation from quantitative to categorical and of the difficulty of the translation itself. These costs are likely to rise due to the ever-increasing use of numerical evidence. Thus, a careful survey and assessment of the pros and cons of categorical verdicts is called for. The paper undertakes such a task.

CONNECTING KNOWLEDGE AND PROOF

Abstract TBA

Levi Spectre (Open University of Israel)

A CHARACTERISATION OF STATISTICAL EVIDENCE AND ITS IMPLICATIONS

Abstract TBA

WHEN DOES EVIDENCE SUFFICE FOR CONVICTION?

There is something puzzling about statistical evidence. One place this manifests is in the law, where courts are reluctant to use evidence of this kind, in spite of the fact that it is quite capable of meeting the standards of proof enshrined in legal doctrine. After surveying some proposed solutions to this problem, I shall outline a somewhat different approach – one that makes use of a notion of normalcy that is distinct from the idea of statistical frequency. The problem is not, however, merely a legal one. Our unwillingness to base beliefs on statistical evidence is by no means limited to the courtroom, and is at odds with almost every general principle that epistemologists have ever proposed as to how we ought to manage our beliefs.