Behavioral scientists routinely publish broad claims about human psychology and behavior in the world's top journals based on samples drawn entirely from Western, Educated, Industrialized, Rich, and Democratic (WEIRD) societies. Researchers – often implicitly – assume that either there is little variation across human populations, or that these “standard subjects” are as representative of the species as any other population. Are these assumptions justified? Here, our review of the comparative database from across the behavioral sciences suggests both that there is (...) substantial variability in experimental results across populations and that WEIRD subjects are particularly unusual compared with the rest of the species – frequent outliers. The domains reviewed include visual perception, fairness, cooperation, spatial reasoning, categorization and inferential induction, moral reasoning, reasoning styles, self-concepts and related motivations, and the heritability of IQ. The findings suggest that members of WEIRD societies, including young children, are among the least representative populations one could find for generalizing about humans. Many of these findings involve domains that are associated with fundamental aspects of psychology, motivation, and behavior – hence, there are no obviousa priorigrounds for claiming that a particular behavioral phenomenon is universal based on sampling from a single subpopulation. Overall, these empirical patterns suggests that we need to be less cavalier in addressing questions ofhumannature on the basis of data drawn from this particularly thin, and rather unusual, slice of humanity. We close by proposing ways to structurally re-organize the behavioral sciences to best tackle these challenges. (shrink)

We tested an architect with a lesion to the right prefrontal cortex in a real-world architectural design/planning task that required him to develop a new design for our lab space and compared his performance to an age- and education-matched architect. The patient understood the task and even observed that “this is a very simple problem.” His sophisticated architectural knowledge base was still intact and he used it quite skilfully during the problem structuring phase. However, the patient's problem-solving behaviour differed from (...) the control's behaviour in the following ways: he was unable to make the transition from problem structuring to problem solving; as a result preliminary design did not start until two thirds of the way into the session; the preliminary design phase was minimal and erratic, consisting of three independently generated fragments; there was no progression or lateral development of these fragments; there was no carry-over of abstract information into the preliminary design or later phases, and the patient did not make it to the detailing phase. This suggests that the key to understanding our patient's deficit is to understand the cognitive processes and mechanisms involved in the preliminary design phase. We appeal to a theory of design problem solving that associates cognitive processes involved in preliminary design with “lateral” state transformations and argues that “ill-structured” representational and computational systems are necessary to support these transformations. We conclude that the neural basis of this system is selectively damaged in our patient. (shrink)

This article has two goals. First, it synthesizes and critically assesses current scientific knowledge about the cognitive bases of human tool use. Second, it shows how the cognitive traits reviewed help to explain why technological accumulation evolved so markedly in humans, and so modestly in apes.

In three studies, we explored the retention and transfer of tool-making knowledge, learnt from an adult demonstration, to other temporal and task contexts. All studies used a variation of a task in which children had to make a hook tool to retrieve a bucket from a tall transparent tube. Children who failed to innovate the hook tool independently saw a demonstration. In Study 1, we tested children aged 4 to 6 years (N = 53) who had seen the original demonstration (...) 3 months earlier. Performance was excellent at the second time, indicating that children’s knowledge was retained over the 3 month period. In Studies 2 and 3 we explored transfer of the new knowledge to other tasks. In Study 2, children were given two variants of the apparatus that differed in surface characteristics (e.g. shape and colour). Participants generalised their knowledge to these new apparatuses even though the new pipecleaner also differed in size and colour. Five- to 6-year-olds (n = 22) almost always transferred their knowledge to problems where the same tool had to be made. Younger, 3- to 5-year-olds’ (n = 46), performance was more variable. In Study 3, 4- to 7-year-olds (N = 146) saw a demonstration of hook making with a pipecleaner, but then had to make a tool by combining pieces of wooden dowel (or vice versa: original training on dowel, transfer to pipecleaner). Children did not transfer their tool-making knowledge to the new material. Children retained tool-making knowledge over time and transferred their knowledge to new situations in which they needed to make a similar tool from similar materials, but not different materials. We concluded that children’s ability to use tool-making knowledge in novel situations is likely to depend on memory and analogical reasoning, with the latter continuing to develop during middle childhood. (shrink)