RESUMO
Popular dual process models have characterized reasoning as an interplay between fast, intuitive (System 1) and slow, deliberate (System 2) processes, but the precise nature of the interaction between the two systems is much debated. Here we relied on the temporal resolution of electroencephalogram (EEG) recordings to decide between different models. We adopted base-rate problems in which an intuitively cued stereotypical response was either congruent or incongruent with the correct response that was cued by the base-rates. Results showed that solving problems in which the base-rates and stereotypical description cued conflicting responses resulted in an increased centro-parietal N2 and frontal P3. This early conflict sensitivity suggests that the critical base-rates can be processed fast without slow and deliberate System 2 reflection. Findings validate prior EEG work and support recent hybrid dual process models in which the fast System 1 is processing both heuristic belief-based responses (e.g., stereotypes) and elementary logico-mathematical principles (e.g., base-rates).
Assuntos
Conflito Psicológico , Tomada de Decisões/fisiologia , Potenciais Evocados/fisiologia , Resolução de Problemas/fisiologia , Pensamento/fisiologia , Adulto , Mapeamento Encefálico , Sinais (Psicologia) , Eletroencefalografia , Feminino , Humanos , Masculino , Tempo de Reação/fisiologia , Adulto JovemRESUMO
Decades of reasoning and decision-making research have established that human judgment is often biased by intuitive heuristics. Recent "error" or bias detection studies have focused on reasoners' abilities to detect whether their heuristic answer conflicts with logical or probabilistic principles. A key open question is whether there are individual differences in this bias detection efficiency. Here we present three studies in which co-registration of different error detection measures (confidence, response time and confidence response time) allowed us to assess bias detection sensitivity at the individual participant level in a range of reasoning tasks. The results indicate that although most individuals show robust bias detection, as indexed by increased latencies and decreased confidence, there is a subgroup of reasoners who consistently fail to do so. We discuss theoretical and practical implications for the field.