Although we see much utility in Osiurak and Reynaud's in-depth discussion on the role of what they term technical reasoning in cumulative culture, we argue that they neglect the time and energy costs that individuals would have to face to acquire skills in the absence of specific socio-cognitive abilities.

In recent years, developmental psychologists have increasingly been interested in various forms of prosocial behavior observed in infants and young children—in particular comforting, sharing, pointing to provide information, and spontaneous instrumental helping. We briefly review several models that have been proposed to explain the psychological mechanisms underpinning these behaviors. Focusing on spontaneous instrumental helping, we home in on models based upon what Paulus :77–81, 2014) has dubbed ‘goal-alignment’, i.e. the idea that the identification of an agent’s goal leads infants to (...) take up that goal as their own. We identify a problem with the most well-known model based upon this idea, namely the ‘goal contagion’ model. The problem arises from the way in which the model specifies the content of the goal which is identified and taken up. We then propose an alternative way of specifying the content of the goal, and use this as a starting point for articulating an alternative model based upon the idea of alignment, namely the ‘goal slippage’ model. By elucidating the difference between goal contagion and goal slippage, we contribute to the articulation of experimental criteria for assessing whether and when the mechanisms specified by these two models are at work. (shrink)

Recent data show that human children (up to 8 years old) perform poorly when required to innovate tools. Our tool-rich culture may be more reliant on social learning and more limited by domain-general constraints such as ill-structured problem solving than otherwise thought.

Evidence from developmental psychology on children's imagination is currently too limited to support Dubourg and Baumard's proposal and, in several respects, it is inconsistent with their proposal. Although children have impressive imaginative powers, we highlight the complexity of the developmental trajectory as well as the close connections between children's imagination and reality.

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)

Artificial Intelligence is making rapid and remarkable progress in the development of more sophisticated and powerful systems. However, the acknowledgement of several problems with modern machine learning approaches has prompted a shift in AI benchmarking away from task-oriented testing towards ability-oriented testing, in which AI systems are tested on their capacity to solve certain kinds of novel problems. The Animal-AI Environment is one such benchmark which aims to apply the ability-oriented testing used in comparative psychology to AI systems. Here, we (...) present the first direct human-AI comparison in the Animal-AI Environment, using children aged 6–10. We found that children of all ages were significantly better than a sample of 30 AIs across most of the tests we examined, as well as performing significantly better than the two top-scoring AIs, “ironbar” and “Trrrrr,” from the Animal-AI Olympics Competition 2019. While children and AIs performed similarly on basic navigational tasks, AIs performed significantly worse in more complex cognitive tests, including detour tasks, spatial elimination tasks, and object permanence tasks, indicating that AIs lack several cognitive abilities that children aged 6–10 possess. Both children and AIs performed poorly on tool-use tasks, suggesting that these tests are challenging for both biological and non-biological machines. (shrink)

We consider the evolutionary plausibility of Osiurak and Reynaud's arguments. We argue that technical reasoning is not quite the magic bullet that O&R assume, and instead propose a co-evolutionary account of the interplay between technical reasoning and social learning, with language emerging as a vital issue neglected in O&R's account.

Cumulative technological culture (CTC) refers to the increase in the efficiency and complexity of tools and techniques in human populations over generations. A fascinating question is to understand the cognitive origins of this phenomenon. Because CTC is definitely a social phenomenon, most accounts have suggested a series of cognitive mechanisms oriented toward the social dimension (e.g., teaching, imitation, theory of mind, and metacognition), thereby minimizing the technical dimension and the potential influence of non-social, cognitive skills. What if we have failed (...) to see the elephant in the room? What if social cognitive mechanisms were only catalyzing factors and not thesufficient and necessaryconditions for the emergence of CTC? In this article, we offer an alternative, unified cognitive approach to this phenomenon by assuming that CTC originates in non-social cognitive skills, namely technical-reasoning skills which enable humans to develop the technical potential necessary to constantly acquire and improve technical information. This leads us to discuss how theory of mind and metacognition, in concert with technical reasoning, can help boost CTC. The cognitive approach developed here opens up promising new avenues for reinterpreting classical issues (e.g., innovation, emulation vs. imitation, social vs. asocial learning, cooperation, teaching, and overimitation) in a field that has so far been largely dominated by other disciplines, such as evolutionary biology, mathematics, anthropology, archeology, economics, and philosophy. (shrink)

The commentaries have both revealed the implications of and challenged our approach. In this response, we reply to these concerns, discuss why the technical-reasoning hypothesis does not minimize the role of social-learning mechanisms – nor assume that technical-reasoning skills make individuals omniscient technically – and make suggestions for overcoming the classical opposition between the cultural versus cognitive niche hypothesis of cumulative technological culture.

Human life history incorporates childhood, a lengthy post-weaning period of dependency. This species-specific period provides an opportunity for extensive learning and for sophisticated cultural behaviors to develop, including crucial tool use skills. Although I agree that no individual cognitive trait singularly differentiates humans from other animals, I suggest here that without childhood, the traits that are key to human tool use would not emerge.

Several theories, which attempt to give an account of cumulative culture, emphasize the importance of high‐fidelity transmission mechanisms as central to human learning. These high‐fidelity transmission mechanisms are thought to account for the ratchet effect, that is, the capacity to inherit modified or improved knowledge and skills rather than having to develop one's skills from the ground up via individual learning. In this capacity, imitation and teaching have been thought to occupy a special place in the explanation of cumulative culture (...) because they are both thought to function as high‐fidelity transmission mechanisms. In contrast to this standard view, I will argue that imitation and teaching are not both best construed as primarily high‐fidelity transmission mechanisms. Rather, I will argue that though both can contribute to the high‐fidelity transmission of information, imitation and teaching make two distinct contributions to cumulative culture. I will claim that imitation functions primarily as a high‐fidelity transmission mechanism while teaching is primarily responsible for the innovation and creativity characteristic of cumulative culture. (shrink)