Release Date: February 18, 2009
BUFFALO, N.Y. -- In 2007, University at Buffalo computer scientist Sargur Srihari, Ph.D., one of the world's experts on pattern recognition and its application to fingerprints and handwriting, was selected by the National Academy of Sciences to serve with other national experts on its Committee on Identifying the Needs of the Forensic Science Community.
The committee's charge was to explore the current status of the forensic sciences and to guide future research that would best serve the U.S. justice system and its citizens.
Today, the NAS released the panel's findings in a report called "Strengthening Forensic Science in the United States: A Path Forward" that can be found at http://www.national-academies.org.
In the conversation below, Srihari, a SUNY Distinguished Professor in the UB Department of Computer Science and Engineering, discusses how his work in the field of pattern recognition has influenced and guided his interest in forensic science and how the NAS report's findings reflect the powerful potential that the field holds given proper scientific support.
In addition to founding and directing UB's Center of Excellence in Document Analysis and Recognition (CEDAR), Srihari is a fellow of the Institute for Electrical and Electronics Engineers (IEEE) and the International Association of Pattern Recognition. He organized the first-ever international workshop on computational forensics in the U.S. held last August at the National Academy of Sciences. The author of more than 300 peer-reviewed publications and the subject of numerous stories by such well-known media as ABC News and The New York Times, he also has served on the Board of Scientific Counselors of the National Library of Medicine.
How has serving on the NAS committee changed or influenced your perception of how much science can be applied to forensics?
I am a believer in strong artificial intelligence. Given sufficient time and resources, specific intelligent tasks that humans perform can be automated. Forensic tasks are much more challenging than reading postal addresses, for example, and, of course, much more is at stake.
What does this report mean to you as a researcher?
The NAS report puts the focus on the need to develop more objective methods. One of the areas that I hope we will be able to develop is something I call "computational forensics." It is about developing algorithms and software to perform forensic analysis. The results of such analysis will be less prone to criticism that forensic testimony is tainted by bias.
Hopefully, financial support of research in the forensic sciences, which at present only the National Institute of Justice is able to provide, will improve. Present support of National Institute of Justice research is miniscule in comparison to support for agencies like the National Institutes of Health and the National Science Foundation. Currently, there are only a handful of scientists in this field in the U.S.; so hopefully, additional funding will attract more researchers.
Dr. Srihari, when you began your career in the 1970s, you were researching how to get machines to read handwriting for the U.S. Postal Service. Today, you study how to rigorously apply science to forensics. Please describe how that evolution occurred.
My research for the past 30 years has been in the field of computer science known as "pattern recognition." It is an area of artificial intelligence that is about developing algorithms to get computers to perform cognitive tasks normally performed by skilled humans. An example of such a skill is that of recognizing handwriting. That interest resulted in my work being funded by the U.S. Postal Service, since they were interested in automatic reading of handwritten addresses. At the time, it was considered a difficult, if not impossible, task. Today, more than 95 percent of all handwritten addresses in the U.S. are processed by computer.
But the techniques of pattern recognition are far more general, and forensics is a natural application for them: one where humans perform specialized cognitive tasks and where algorithms could be devised to provide an objective basis for their work. The Supreme Court ruling in Daubert v. Merrell Dow, 1993, stated that "pattern evidence" had to have a proven scientific basis if it was going to be allowed in court. The first task we considered was developing algorithms to compare handwriting samples. Computers allowed us to perform large-scale tests to show that indeed this kind of comparison can be done with a high degree of accuracy (Journal of Forensic Sciences, July 2002). We were also able to develop computational tools to assist the handwriting examiners.
Then my colleagues and I at CEDAR decided to look at fingerprints, specifically friction ridge patterns, the swirling lines that make up the print. With high-speed computers, we found we were able to conduct large-scale tests to determine the degree of individuality and uniqueness in a given fingerprint (Journal of Forensic Identification, January 2008 and CEDAR Technical Report, TR-2009).
What surprised you most about working in the field of forensics?
The forensic examiners welcomed my participation in their community, which was under attack. Here was a fairly small community of underpaid and overworked individuals, whose work was being challenged. They were eager to engage with, and learn from, us. As an academic, it also is satisfying work because it is not a highly lucrative commercial field, so my contributions can make a difference even when profit-making is not the main priority.
How has the use of DNA evidence changed the whole field of forensics?
The accuracy of DNA has raised expectations for other forensic modalities, but DNA is available only in about 10 percent of cases. As with DNA, it would be useful for other types of evidence to provide exact probabilities of having a random match. Such probability calculations are to a large extent lacking.
You have been involved as an expert witness in several cases. Can you discuss that experience?
I spoke about the degree of accuracy obtainable with handwriting evidence using computational techniques. This has allowed handwriting evidence to be allowed in several cases. Expert human capability is still higher than today's computational capabilities.
What are some of the biggest challenges in trying to bring science into the courtroom?
Judges are open to hearing scientific testimony. However, they have to make sure in a preliminary hearing that it will be presented in a form that is understandable to a lay jury. For example, the strength of the evidence cannot be expressed as raw numbers or probabilities. Still, these ideas can only be simplified so much.
Can you talk about the backlash where some defense attorneys use the term "junk science" to discredit scientific methods in the courtroom? Will this attitude intensify with the release of this report?
This report will galvanize defense attorneys' position that the scientific basis for introducing evidence is lacking. But justice has to be carried out. With this report, judges and juries can become more aware that there is always an inherent error rate, and therefore multiple types of evidence should be considered in arriving at a final decision. Also, it has to be kept in mind that science is always a work in progress. Newton's laws were a reasonable explanation until they could not explain the behavior of small particles; thus, quantum theory was introduced, which may, one day be replaced by another theory, such as string theory.
Do you think the time is ripe for making forensics more scientific?
Yes, indeed. And applied science will have many economic spinoffs. We saw that with U.S. Postal Service funding of our research. Prior to those research successes, there was no funding for such work at U.S. universities, and the field of postal automation was left to Japanese and German companies. After the USPS-backed research proved fruitful, American companies, such as Northrup-Grumman -- which applied some of our technology to reading IRS forms -- and Lockheed-Martin -- which became the prime USPS contractor -- created many new technology jobs in the U.S. It also allowed the USPS to remain competitive and to keep its costs low.
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