Prof Catriona Havard

Super-recognisers (SR) are defined as individuals with superior facial recognition skills (Russel, Duchaine, Nakayama, 2009), and have been found to outperform control individuals (i.e., non-super-recognisers) when matching faces to simultaneously presented line-ups and at recognising faces from videos (Bobak, Hancock, & Bate, 2016). These ‘super’ skills in facial recognition suggest that SR may be the ideal candidates to work as immigration officers and CCTV analysts (Bobak et al., 2016). However, as well as performance in experimental conditions, utilising SR in the field would require additional capabilities, including avoiding bias, which may be introduced through context (i.e., knowledge of the decisions made by other SRs when investigating the same face), that might influence a decision. Previous research has shown that forensic scientists, who have expertise in analysing forensic evidence (e.g. DNA), are influenced by contextual information (Dror, Charlton, & Peron, 2006), so it is critical to determine whether SR are similarly affected. The proposed study will, therefore, aim to investigate if contextual information biases face-experts (i.e., SR). To achieve this aim, SR will be identified by using valid and reliable measures (e.g., the Cambridge Face Memory Test+; Duchaine & Nakayama, 2006). A 2 (context vs. no context) x 2 (target face present vs. absent from CCTV) x 2 (high resolution image vs. low resolution image) x 2 (SR vs. control) experimental design will be utilised to investigate if context influences the recognition judgments of SR when compared to controls. In 50% of trials, participants will be introduced to context by informing them of the decision made by a fictitious super-recogniser. The contextually biased trials will be counterbalanced over the course of the research. Image quality will be manipulated as context influences decisions more in ambiguous contexts (Dror et al., 2006).