Internal Seminar: Harriet Rowthorn, "Advancing the cognitive approach to lie detection"
Advancing the cognitive approach to lie detection
The cognitive approach to lie detection posits that interviewers should impose cognitive load on interviewees to elicit cues to deception. The success of the cognitive approach, however, relies on the interviewee having a strong memory for the target event (i.e., the crime committed). When interviewees have strong memories, they must dedicate more cognitive resources to suppressing the truthful details and monitoring the information they are communicating. This means that they have fewer cognitive resources available to monitor their behaviour and consequently, they are more likely to leak cues to deception. When interviewees have poor memories, the cognitive demand of retrieving the truth may surpass that of lying, which may lead truth tellers to seem suspicious and liars to leak fewer cues to deception. It is therefore important to interview people in a way that preserves their memory for the target event to assist accurate veracity judgements throughout a criminal investigation.
Using a novel mock crime procedure, we explored the implications of imposing cognitive load on interviewees’ memories for a simulated crime. Adult participants (n = 150) watched a mock crime and were then instructed to tell the truth or lie about the details they had witnessed. Participants lied about the mock crime by solving and reporting deceptive anagrams that were easy (low cognitive load), difficult (high intrinsic cognitive load) or while completing a secondary task (high extraneous cognitive load). Three weeks later, we tested participants’ memories for the mock crime. The results showed that imposing cognitive load on interviewees does impair memory, but the type of the cognitive load instruction matters. Our findings help to refine a new model—the memory and deception framework—that aims to account for the effects of lying on memory, and have important practical implications for the cognitive approach to lie detection.
Event co-ordinator: Jesse Preston