Faces Do Not Attract More Attention Than Non-Social Distractors in the Stroop Task

As robots begin to receive citizenship, are treated as beloved pets, and given a place at Japanese family tables, it is becoming clear that these machines taking on increasingly social roles. While human-robot interaction research relies heavily self-report measures for assessing people’s perception of robots, distinct lack robust cognitive behavioural gauge the scope limits motivation towards artificial agents exists. Here we adapted Conty colleagues’ (2010) version classic Stroop paradigm, in which showed four kinds distractor images above incongruent neutral words: human faces, robot object faces (for example, cloud with facial features) flowers (control). We predicted stimuli, like would be extremely salient draw attention away from to-be-processed words. A repeated-measures ANOVA indicated task worked (the effect was observed), distractor-dependent enhancement interference emerged. Planned contrasts specifically presented words significantly slowed participants’ reaction times. To investigate this small further, conducted second experiment (N=51) larger stimulus set. main condition slowing down time replicated, did not observe an distractors (human faces) drawing more than other types. question suitability measure discuss our findings light recent conflicting results attentional capture literature.