The Super-Recogniser Advantage Extends to the Detection of Digitally Manipulated Faces

Abstract

Face recognition by human officials remains the predominant method of identity verification in security-critical contexts. The integrity of this process can be compromised by sophisticated fraud attacks using manipulated face images. Therefore, in this study, we examine whether human observers can detect digitally manipulated passport photos, and whether super-recognisers (SRs) outperform typical recogniser controls. Using two face manipulation detection tasks (DFMD1, DFMD2), participants were asked to decide whether a ‘suspected’ passport photo had been digitally manipulated. SRs were found to significantly outperform controls; this effect was not the result of a ‘speed-accuracy trade-off’. Individual differences on tests of face identification aptitude, self-rated ability, and response times, accounted for over 20% of the variance in manipulated image detection sensitivity. Taken together, these findings show that, despite increasing sophistication in digital face manipulation techniques, there is still utility in employing human operators, particularly SRs, to detect them.