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We are the European branch of the oldest and largest forensic association in the world. This professional forensic association represents a large network of interested academics, professionals, companies and institution who are active in the world of forensic and biometrics.
4th Conference of the European Division of the International Association for Identification
June 13-14, 2019 at SOUND GARDEN HOTEL, Warsaw, Poland
KEYNOTE SPEAKER
CEDRIC NEUMANN
A new perspective on the analysis of data collected during error rates experiments in forensic science
Several groups, in particular in the U.S. (e.g., PCAST, NRC, NIST-OSAC, NIJ), have called for the determination of the “error rates” of different forensic sub-disciplines. Estimating error rates in forensic science is not an easy task. Many discussions are taking place on how to administer error rates experiments in the most unbiasing way, to a sufficiently large number of scientists, with a sufficiently large number of test cases and that can account for important factors affecting the examination process.
Unfortunately, experiments in the forensic context cannot be run in the same sheltered way as they are in plant or animal science, or in industry. Due to budget and time constraints, experiments in the forensic context are necessarily relying on practicing scientists who gracefully donate personal time to support research. Consequently, data collected during these experiments is often messy, unbalanced and incomplete and its analysis is an often overlooked challenge; not to mention that interpreting the results of these analyses is far from being intuitive (e.g., what is a “confidence interval”, and why does the PCAST report only uses a “one-sided confidence interval”?).
During this talk, we will explore the difficulties associated with the analysis of data collected during error rates experiments. We will describe a method for analysing messy and incomplete data that actually answers the question at hand (i.e., assigning values to error rates under the uncertainty associated with the experiment). We will apply this method to two well-known experiments aimed at quantifying the error rates in fingerprint examination: the NIJ-funded experiment conducted by the Miami-Dade Police Department (MDPD), and the FBI-driven experiment conducted by Noblis (aka the “black-box study”). Our method allows us to look at this data under a new light, address some of the controversy surrounding these studies (principally the MDPD study) and draw some conclusions that have previously escaped the initial researchers. No statistical background is required to enjoy this talk.
Workshop (3 hours) – Decision-making in forensic science: what information is needed, which conclusions are supported.
The inference of the source of a given trace is the key question addressed by most forensic scientists (at least in the pattern and trace sub-disciplines). The inference process includes many different phases, which, in turn, require different types of information. Fortunately, the decision-making process used in forensic science is no different than the one used to make decisions at every instant of our lives; thus, this process is, at least unconsciously, very familiar to all of us. During this workshop, we will explore, using a series of examples and exercises rooted in our daily lives, the structure of the decision-making process that we use to reach conclusions in forensic science. We will explore how the different types of conclusions that are commonly encountered in forensic science relate to different phases of the decision-making process, and we will discuss how our (in)ability to use certain pieces of information during the process (e.g., because of the possibility of bias) affect the types of conclusions that can be logically supported. No statistical background is required to benefit from this workshop.
Bio
Cedric Neumann was awarded a PhD in Forensic Science from the University of Lausanne, Switzerland. From 2004 to 2010, Cedric worked at the Forensic Science Service (FSS) in the United Kingdom. As head of the R&D Statistics and Interpretation Research Group, he contributed to the development of the first validated fingerprint statistical model. This model was used to support the admissibility of fingerprint evidence in U.S. courts. Cedric is currently an Associate Professor of Statistics at the South Dakota State University. Cedric’s main area of research focuses on the statistical interpretation of forensic evidence, more specifically fingerprint, shoeprint and traces. Cedric has taught multiple workshops for forensic scientists and lawyers alike. Cedric served on the Scientific Working Group for Friction Ridge Analysis, Study and Technology (SWGFAST), was a member of the Board of Directors of the IAI and is the resident statistician of the Chemistry/Instrumental Analysis SAC committee in the NIST-OSAC.
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