University of Michigan Journal of Law Reform, Vol. 44, p. 511, 2011
46 Pages Posted: 28 Jul 2011 Last revised: 29 Jul 2011
Date Written: July 28, 2011
Both case law and legal literature have recognized that all, and not just clearly statistical, evidence is probabilistic. Therefore, we have much to learn from the laws of probability with regard to the evaluation of evidence in a criminal trial. The present Article focuses on the confession. First, we review legal and psychological literature and show that the probability of a false confession and, consequently, a wrongful conviction, is far from insignificant. In light of this, we warn against the cognitive illusion, stemming from the fallacy of the transposed conditional, which is liable to mislead the trier of fact in evaluating the weight of a confession. This illusion in evaluating the weight of a confession occurs when the trier of fact believes that, if there is only a low probability that an innocent person would falsely confess, then there is also only a low probability of innocence in each and every case where a person does confess guilt. The surprising truth is that even if there is only little doubt regarding the credibility of confessions in general, in some cases, this raises considerable doubt regarding the certainty of a conviction. We demonstrate this through the case of George Allen, who was convicted in 1983 of the rape and murder of Mary Bell. This is an example of a case in which the fallacy reaches extreme proportions, since nothing connected the accused to the crime, apart from his confession.
Following this, we turn to a Bayesian calculation of probability for evaluating the weight of a confession. First, we discuss the standard of proof required for a criminal conviction. We show that the optimistic expectation of the U.S. Supreme Court in Kansas v. Marsh regarding the rate of false convictions (0.027%) is inconsistent with Blackstone’s famous approach, accepted by many judges, whereby it is better for ten criminals to be acquitted than for one innocent to be convicted (9.09% wrongful convictions). We then demonstrate the untenability of the optimistic estimate that it is possible to convict with a relatively low probability of guilt (approximately 91%) without paying a very heavy price in wrongful convictions. Considering this, we explain why we prefer the ratio proposed by Thomas Starkie, whereby it is better for a hundred criminals to be acquitted than for one innocent to be convicted. The probabilistic calculation that we perform based on this threshold of 1:100 dictates a new and surprising conclusion that calls for a significant * Prof. Boaz Sangero is Head of the Department of Criminal Law and Criminology at the Academic Center of Law and Business, Israel. ** Dr. Mordechai Halpert is a physicist involved, among other things, in the research and development of voice biometric systems. Furthermore, even if we suffice with Blackstone’s familiar threshold of 1:10, the strength of the other evidence against the suspect, apart from the confession, must still be at least a balance of probabilities (51%) in order to achieve proof of guilt beyond a reasonable doubt, the burden required for a conviction. Given the real danger of convicting innocents, we call on law enforcement officials to refrain from interrogating a person, with the aim of extracting a confession, when there is no well - established suspicion against this person, and even when the law allows for such an interrogation. Moreover, we call on legislatures to amend the law so that such an interrogation would not be possible, and to set forth that a confession is insufficient to constitute the sole, or key, evidence for a conviction, but it can be used only as corroboration for other key evidence - if it exists.
Suggested Citation: Suggested Citation
Sangero, Boaz and Halpert, Mordechai, Proposal to Reverse the View of a Confession: From Key Evidence Requiring Corroboration to Corroboration for Key Evidence (July 28, 2011). University of Michigan Journal of Law Reform, Vol. 44, p. 511, 2011. Available at SSRN: https://ssrn.com/abstract=1898097