Junk Science Legal Challenge Explained
Computer forensics is a relatively new forensic science and it is different from most of the other forensic sciences, e.g., peer reviews are limited and very few universities offer courses or degrees in computer forensic science. Another aspect of computer forensics that makes it unique is that computer technology is continually changing with the times. These technology changes mandate that computer forensic software tools and processes must change frequently. For these reasons some criminal and civil defense lawyers have challenged the expertise of computer forensics practitioners in U. S. courts and have sought to exclude computer related evidence claiming that computer forensics is a "Junk Science" and therefore cannot be relied upon to produce accurate and reliable results. Sometimes the junk science argument is referred to as the Daubert - Frye argument.
Before the Federal Rules of Evidence were adopted, the Frye case (Frye v. United States, 293 f. 1013 - D.C. CIR 1923) was the governing rule to determine whether scientific testimony could be admitted in court. In the 1923 case of Frye v. United States, a federal judge refused to admit polygraph results against a criminal defendant because the principles of the polygraph had not yet been "generally accepted" by others in the relevant scientific community.
In 1975 the Federal Rules of Evidence were enacted by Congress. With regard to the admissibility of scientific evidence, Rule 702 states that:
If scientific, technical, or other specialized knowledge will assist the trier of fact to understand the evidence or to determine a fact in issue, a witness qualified as an expert by knowledge, skill, experience, training, or education, may testify thereto in the form of an opinion or otherwise.
In other words, if a jury would find the testimony of one with specialized knowledge to be helpful, a court may admit it. Following the enactment of Rule 702, many courts rejected the Frye standard of "general acceptance" in favor of the more liberal "helpfulness" standard of Rule 702.
The U. S. Supreme Court helped resolve the division in the lower courts in Daubert v. Merrel Dow Pharmaceuticals, Inc., 509 U. S. 579 (1993), by stating that Frye was no longer the standard governing the admissibility of sceintific evidence. Rather, the court interpreted Rule 702 to mean that scientific evidence may be admitted only if it is relevant to the issue at hand and rests on a reliable foundation.
In order to assist the lower courts in applying Daubert, the Court provided the following list of factors that courts should consider before ruling on the admissibility of scientific evidence:
- Whether the theory or technique has been reliably tested;
- Whether the theory or technique has been subject to peer review and publication;
- What is the known or potential rate of error of the method used; and
- Whether the theory or method has been generally accepted by the scientific community.
The law of scientific evidence presents unique challenges to the field of computer forensics. This is one of the reasons that NTI has aligned with academia in its training courses, e.g., NTI's 5 Day Computer Forensics Course qualifies for academic certification and university credit hours. NTI also makes it a point to teach cross validation methodologies using multiple tools from multiple vendors to validate the "error free" accuracy of relevant computer forensic findings. NTI also encourages its students to take many computer and computer forensic training courses from multiple training sources and to stay current with credible books and publications on the topic of computer forensics. In that regard, NTI's training students receive copies of some of the top computer evidence books in the field during the NTI training courses. NTI's list of recommended computer evidence books can be found at http://www.forensics-intl.com/ev-info.html.
Junk science issues, arguments and rebuttals are covered in detail in NTI's 5 Day Computer Forensics Course and NTI's 3 Day Expert Witness Course. With the proper training, experience, methodology and software tool cross validation, junk science challenges can easily be resolved.
