The 11th International Conference on Forensic Inference and Statistics, or ICFIS 2023, is set for June 12-15 of this year. It will be held at the Faculty of Law (Juridicum) of Lund University, Lund, Sweden. While I am saddened that I cannot attend this particular meeting, several years ago I had the pleasure of going to the 2014 International Conference on Forensic Inference and Statistics, or ICFIS which was the 9th iteration of the conference. I wrote a blog post about that meeting some time ago.
I can say, based on past experience alone, that this meeting is well worth attending. That’s particularly true if you are interested in the logical approach to evidence evaluation, but it would benefit any forensic scientist. You will not find a better collection of brilliant people all focused on forensic inference, in the broadest sense.
Forensic scientists, lawyers, academics—they will all be there.
Years ago, in 2013 to be precise, I was invited to speak at the ICA conference held in Montréal, Québec. The conference had a special session on “distinguishing between science and pseudoscience in forensic acoustics”. Now, I am definitely not an expert in forensic acoustics. In fact, I know almost nothing about the field other than what I’ve read from time to time. So I wasn’t there to tell the audience anything about forensic acoustics, per se.
David H. Kaye (DHK) is one of my favourite writers. He is truly prolific and always manages to provide great insights for the reader. His grasp of statistics, logic, and the law is second-to-none, and his ability to communicate those very challenging topics to his audience is equally impressive.
As a mini introduction, David “…is Distinguished Professor, and Weiss Family Scholar in the School of Law, a graduate faculty member of Penn State’s Forensic Science Program, and a Regents’ Professor Emeritus, ASU.” If you would like to see a list of his publications check out http://personal.psu.edu/dhk3/cv/cv_pubs.html
Yes, DHK has written many things on many topics. But I would like to focus on his less formal writings from his blog Forensic Science, Statistics & the Law.
Forensic Document Examination is a complex area involving many different topics and abilities. I am always looking for useful resources that can help me do this work and some of that information can be found online.
In time I would like to provide a more fulsome list of online resources pertaining to the different facets of this work but that is going to take a while to compile and it will be an ongoing project. Still there are already a few websites I consider to be particularly interesting and useful. I’ve compiled them into a list to serve as a starting point for a more complete and general list.
Some of these relate to Forensic Document Examination, some to logic and reasoning, and some pertain to programming and statistics (i.e., my main areas of interest). They are not listed in any particular order. Other categories, and more sites, may be added from time to time. In the meantime, I hope that you find them as interesting and useful as I have. If you know of other sites that you think might be included here, please let me know via the contact page. Enjoy!!
The expression “better late than never” applies to this post. Over the span of two days in June 2013 the Measurement Science and Standards in Forensic Handwriting Analysis (MSSFHA) conference was held. It explored the (then) current state of forensic handwriting analysis, aka, forensic handwriting examination (FHE). Presentations varied in content but most discussed recent advancements in measurement science and quantitative analyses as it relates to FHE.
The conference was organized by NIST’s Law Enforcement Standards Office (OLES) in collaboration with the AAFS — Questioned Document Section, the ABFDE, the ASQDE, the FBI Laboratory, the NIJ and SWGDOC.
The concepts of ‘prior odds’, a.k.a., prior probabilities or simply priors, and ‘posterior odds’ come up in most discussions about the evaluation of evidence. The significance and meaning of both terms becomes clear when viewed in the context of a “Bayesian approach”, or the logical approach, to evidence evaluation. That approach has been discussed at length elsewhere and relates to the updating of one’s belief about events based upon new information. A key aspect is that some existing belief, encapsulated as the ‘prior odds’ of two competing possibilities or events, will be updated on the basis of new information, encapsulated in the ‘likelihood-ratio’ (another term you will undoubtedly have seen), to produce some new belief, encapsulated as ‘posterior odds’ about those same competing possibilities.
But what precisely do these terms, ‘prior odds’ and ‘posterior odds’, mean and how do they relate to the work of a forensic examiner?
This year the Annual General Meeting of the American Society of Questioned Document Examiners (ASQDE) is being held in Indianapolis, Indiana on August 24 through 29, 2013. In keeping with the theme, “Demonstrative Science: Illustrating Findings in Reports and Court Testimony”, I will be presenting a one-day workshop entitled “Conclusion Scales and Logical Inference” on Sunday, August 25.
Forensic scientists, individually and as a group, unquestionably want to be completely logical, open and transparent in their approach to the evaluation of evidence. Further, I am sure that most document examiners believe this is exactly what they are achieving when they apply the procedures outlined in various traditional textbooks or the SWGDOC/ ASTM standards; for example, the SWGDOC Standard for Examination of Handwritten Items. Given the very understandable desire to be logical, I find it strange that so many people have a negative attitude towards anything “Bayesian” in nature. After all, a logical approach to evidence evaluation that conforms to the overall Bayesian philosophy or approach is, quite literally, the embodiment of logic (more specifically, probabilistic logic).
The terms accuracy and precision are often confused or misunderstood. But every scientist, forensic or otherwise, should understand what they mean. In simple terms, ‘accuracy’ relates to how closely the value comes to the real score or true value (being ‘on target’). ‘Precision’, on the other hand, relates to the consistency of the value in repeated testing. Any given test, statistic or process may produce results that are one or the other, both or neither.