The legal application of neuroimaging for lie-detection in courtrooms has been criticized by scientists on a number of grounds. Firstly, results of fMRI studies on experimental subjects such as undergraduate students cannot necessarily be applied to people offering evidence in a court. Secondly, lie-detection neuroimaging studies are designed such that lies are ‘instructed,’ meaning that a lie in the laboratory is not actually a real lie. Thirdly, much of the research on lie-detection with fMRI has been conducted by private companies, such as No Lie MRI, who do not publish their findings in peer-reviewed journals and who hire scientists with vested interests in study outcomes.
Despite these criticisms, an article by law professor Frederick Shauer recently appeared in Trends in Cognitive Sciences, arguing that the suitability of neuroimaging as a tool for the courtroom should be determined according to legal and not scientific standards. Principle among his arguments is the claim that current legal methods of lie-detection are not scientifically valid in any sense, and if neuroimaging provides even a slightly higher validity, it should be used in legal cases. Schauer points out that “[r]esearch shows that ordinary people’s ability to distinguish truth from lies rarely rises above random, and juries are unlikely to do better.” He follows this up by stating that “...the admissibility of neural lie-detection evidence must be based on an evaluation of the realistic alternatives within the legal system and not on a non-comparative assessment of whether neural lie-detection meets the standards that scientists use for scientific purposes.”
The argument is certainly interesting, and scientists should be able to appreciate it. Scientists are trained to be cautious and skeptical, only accepting of findings that have just a 5% or lower chance of being attributed to error. These standards are often even higher for fMRI studies. However, if a jury can correctly detect lies only 50% of the time, brain scans that are right 60% of the time are simply more reliable.
Yes, there may be differences between experimental subjects telling instructed lies and real-life defendants being put to the test. But Schauer argues that “...if the ease of telling an instructed lie in the laboratory correlates with the ease of telling a real lie outside the laboratory, research on instructed lies is no longer irrelevant to detecting real lies.”
This has not yet been demonstrated, and Schauer admits that the use of fMRI for lie-detection is probably unwarranted at this point. Several obstacles first need to be overcome, but fMRI in law seems to hold newfound promise in the face of scientific criticism when Schauer’s idea of comparing neuroimaging to current, perhaps less effective methods of lie-detection, are taken into consideration.
Still, scientists who understand the proper use of fMRI need to develop certain methods to ensure that the lie-detection application is practical and effective. Typically found in many neuroimaging studies are ‘outlier’ subjects whose results do not conform to what is found in other subjects. Sometimes the outlier did not perform the task correctly, resulting in brain activity reflecting attention to the wrong stimuli or a lack of attention to the task altogether. A smart liar might be able to play with his/her attention to the lie-detection task at hand, resulting in skewed data. Since fMRI studies typically require responses that involve button presses rather than speech, intentional distractive thoughts may be more readily enabled.
More fMRI studies on real-life-style lie-detection need to be conducted before a courtroom introduction is warranted. But over-skepticism is unwarranted when lie-detection systems of today’s courts are flawed and unreliable.
Schauer F (2010). Neuroscience, lie-detection, and the law: contrary to the prevailing view, the suitability of brain-based lie-detection for courtroom or forensic use should be determined according to legal and not scientific standards. Trends in cognitive sciences, 14 (3), 101-3 PMID: 20060772