Assessing 'beyond a reasonable doubt' without probability: an info-gap perspective. (3rd January 2019)

• Record Type: Journal Article
• Authors: Ben-Haim, Yakov
• Is Part Of: Law, probability & risk. Volume 18:Number 1(2019)
• Page Start: 77
• Page End: 95
• Publication Date: 2019-01-03
• Subjects: beyond a reasonable doubt -- judicial evidence -- Knightian uncertainty -- indeterminism -- info-gap -- robustness; Proximate cause (Law) -- Periodicals; Risk -- Periodicals; Law -- Mathematical models -- Periodicals; Law -- Methodology -- Periodicals; Probabilities -- Periodicals; Risk assessment -- Periodicals; Law -- Mathematical models; Law -- Methodology; Probabilities; Proximate cause (Law); Risk; Risk assessment; Periodicals; 340.1
• DOI: 10.1093/lpr/mgy021
• Languages: English
• ISSNs: 1470-8396

Abstract

Abstract: The concept 'beyond a reasonable doubt' is fundamental, procedurally and normatively, in legal proceedings. It generates operational criteria for triers' decisions, and reflects the high social value of protecting innocent individuals. Uncertainty in judicial evidence is prevalent, motivating the concept of 'beyond a reasonable doubt'. 'Beyond a reasonable doubt' is traditionally operationalized with ethical definitions. Recently, qualitative and quantitative probabilistic concepts have been advocated and disputed for defining 'beyond a reasonable doubt'. Our first claim is that much judicial uncertainty is consistent with Knight's concept of 'true uncertainty', and inconsistent with the normalization and additivity axioms of probability. The prevalence of Knightian uncertainty in judicial evidence results from indeterminism in human affairs as developed by Shackle and Popper. Our second claim is that 'beyond a reasonable doubt' can be operationalized with the concept of robustness as developed qualitatively in info-gap decision theory. A trier's decision is highly robust to uncertainty in the evidence if only very great change in the evidence would undermine the decision. When facing Knightian uncertainty, a decision is acceptable beyond a reasonable doubt if it is highly robust to uncertainty in the evidence. We illustrate the qualitative implementation of this criterion with several examples.