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22 A.I. & L. 1 (2014)

handle is hein.journals/artinl22 and id is 1 raw text is: Artif Intell Law (2014) 22:1-28 DOI 10.1007/s10506-013-9147-x Calculating and understanding the value of any type of match evidence when there are potential testing errors Norman Fenton - Martin Neil - Anne Hsu Published online: 11 October 2013 © Springer Science+Business Media Dordrecht 2013 Abstract It is well known that Bayes' theorem (with likelihood ratios) can be used to calculate the impact of evidence, such as a 'match' of some feature of a person. Typi- cally the feature of interest is the DNA profile, but the method applies in principle to any feature of a person or object, including not just DNA, fingerprints, or footprints, but also more basic features such as skin colour, height, hair colour or even name. Notwith- standing concerns about the extensiveness of databases of such features, a serious challenge to the use of Bayes in such legal contexts is that its standard formulaic representations are not readily understandable to non-statisticians. Attempts to get round this problem usually involve representations based around some variation of an event tree. While this approach works well in explaining the most trivial instance of Bayes' theorem (involving a single hypothesis and a single piece of evidence) it does not scale up to realistic situations. In particular, even with a single piece of match evidence, if we wish to incorporate the possibility that there are potential errors (both false positives and false negatives) introduced at any stage in the investigative process, matters become very complex. As a result we have observed expert witnesses (in different areas of speciality) routinely ignore the possibility of errors when presenting N. Fenton (E) Risk and Information Management Research Group, Queen Mary University of London, London, UK e-mail: norman@eecs.qmul.ac.uk N. Fenton - M. Neil Agena Ltd, Cambridge, UK e-mail: martin@eecs.qmul.ac.uk M. Neil Computer Science and Statistics, Queen Mary University of London, London, UK A. Hsu Queen Mary University of London, London, UK e-mail: anne.hsu@eecs.qmul.ac.uk I Springer

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