Acta Psychologica (Aug 2022)

Does attributing mental states to a robot influence accessibility of information represented during reading?

  • Abdulaziz Abubshait,
  • Giulia Siri,
  • Agnieszka Wykowska

Journal volume & issue
Vol. 228
p. 103660


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When we read fiction, we encounter characters that interact in the story. As such, we encode that information and comprehend the stories. Prior studies suggest that this comprehension process is facilitated by taking the perspective of characters during reading. Thus, two questions of interest are whether people take the perspective of characters that are not perceived as capable of experiencing perspectives (e.g., robots), and whether current models of language comprehension can explain these differences between human and nonhuman protagonists (or lack thereof) during reading. The study aims to (1) compare the situation model (i.e., a model that factors in a protagonist's perspective) and the RI-VAL model (which relies more on comparisons of newly acquired information with information stored in long term memory) and (2) investigate whether differences in accessibility of information differ based on adopting the intentional stance towards a robot. To address the aims of our study, we designed a preregistered experiment in which participants read stories about one of three protagonists (an intentional robot, a mechanistic robot and a human) and answered questions about objects that were either occluded or not occluded from the protagonist's view. Based on the situation model, we expected faster responses to items that were not occluded compared to those that were occluded (i.e., the occlusion effect). However, based on the RI-VAL model, we expected overall differences between the protagonists would arise due to inconsistency with general world knowledge. The results of the pre-registered analysis showed no differences between the protagonists, nor differences in occlusion. However, a post-hoc analysis showed that the occlusion effect was shown only for the intentional robot but not for the human, nor mechanistic robot. Results also showed that depending on the age of the readers, the RI-VAL or the situation model is able to explain the results such that older participants “simulated” the situation about which they read (situation model), while younger adults compared new information with information stored in long-term memory (RI-VAL model). This suggests that comparing to information in long term memory is cognitively more costly. Therefore, with older adults used less cognitively demanding strategy of simulation.