The role of the working memory storage component in the random-likes series generation

Abstract

People do not possess an internal random series generator. Instead, they try to reproduce outputs of a known random process. However, this process is restricted by their working memory. Here, we investigate the model of random-like series generation proposed by Biesaga, Talaga, and Nowak (2021) that accounts for the involvement of storage and processing components of working memory. In two studies, we used a modern, robust measure of randomness to assess human-generated series. In Study 1, in an experimental design with the visibility of the last generated elements as a between-subjects variable, we tested whether decreasing cognitive load on working memory would mitigate the decay in the level of randomness of the generated series. Moreover, we investigated the relationship between randomness judgment and algorithmic complexity of human-generated series. In Study 2, in a correlational design, we examined the relationship between working memory capacity and the ability to produce random-like series. The results of Study 1 show that when people did not have to solemnly rely on their working memory storage component to maintain active past choices they were able to prolongate their high-quality performance. Moreover, people who were able to better distinguish more complex patterns at the same time generated more random series. The results of Study 2 showed that individuals with longer working memory capacity length also were able to produce more complex series. These results indicate that although people do not have an inner randomness generator their limitations cannot be solemnly ascribed to the limits of their cognitive resources