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)

Cumulative technological culture can be defined as the progressive diversification, complexification, and enhancement of technological traits through generations. An outstanding issue is to specify the cognitive bases of this phenomenon. Based on the literature, we identified four potential cognitive factors: namely, theory-of-mind, technical-reasoning, creativity, and fluid-cognitive skills. The goal of the present study was to test which of these factors—or a combination thereof—best predicted the cumulative performance in two experimental, micro-society conditions differing in the nature of the interaction allowed between (...) participants. The task was to build the highest possible tower. Participants were also assessed on the four aforementioned cognitive factors in order to predict cumulative performance and attractiveness. Our findings indicate that technical-reasoning skills are the best predictor of cumulative performance, even if their role may be restricted to the specific technological domain. Theory-of-mind skills may have a facilitator role, particularly in the Communication condition. Creativity can also help in the generation of novel ideas, but it is not sufficient to support innovation. Finally, fluid cognition is not involved in cumulative technological culture. Taken together, these findings suggest that domain-specific knowledge remains critical for explaining cumulative technological culture. (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.

Understanding the link between brain evolution and the evolution of distinctive features of modern human cognition is a fundamental challenge. A still unresolved question concerns the co-evolution of tool behavior (i.e., tool use or tool making) and language. The shared neurocognitive processes hypothesis suggests that the emergence of the combinatorial component of language skills within the frontal lobe/Broca's area made possible the complexification of tool-making skills. The importance of the frontal lobe/Broca's area in tool behavior is somewhat surprising with regard (...) to the literature on neuropsychology and cognitive neuroscience, which has instead stressed the critical role of the left inferior parietal lobe. Therefore, to be complete, any version of the shared neurocognitive processes hypothesis needs to integrate the potential interactions between the frontal lobe/Broca's area and the left inferior parietal lobe as well as their co-evolution at a phylogenetic level. Here, we sought to provide the first elements of answer through the use of the massive deployment framework, which posits that evolutionarily older brain areas are deployed in more cognitive functions (i.e., they are less specific). We focused on the left parietal cortex, and particularly the left areas PF, PGI, and anterior intraparietal (AIP), which are known to be involved in tool use, language, and motor control, respectively. The deployment of each brain area in different cognitive functions was measured by conducting a meta-analysis of neuroimaging studies. Our results confirmed the pattern of specificity for each brain area and also showed that the left area PGI was far less specific than the left areas PF and AIP. From these findings, we discuss the different evolutionary scenarios depicting the potential co-evolution of the combinatorial and generative components of language and tool behavior in our lineage. (shrink)

Understanding the link between brain evolution and the evolution of distinctive features of modern human cognition is a fundamental challenge. A still unresolved question concerns the co-evolution of tool behavior (i.e., tool use or tool making) and language. The shared neurocognitive processes hypothesis suggests that the emergence of the combinatorial component of language skills within the frontal lobe/Broca's area made possible the complexification of tool-making skills. The importance of the frontal lobe/Broca's area in tool behavior is somewhat surprising with regard (...) to the literature on neuropsychology and cognitive neuroscience, which has instead stressed the critical role of the left inferior parietal lobe. Therefore, to be complete, any version of the shared neurocognitive processes hypothesis needs to integrate the potential interactions between the frontal lobe/Broca's area and the left inferior parietal lobe as well as their co-evolution at a phylogenetic level. Here, we sought to provide the first elements of answer through the use of the massive deployment framework, which posits that evolutionarily older brain areas are deployed in more cognitive functions (i.e., they are less specific). We focused on the left parietal cortex, and particularly the left areas PF, PGI, and anterior intraparietal (AIP), which are known to be involved in tool use, language, and motor control, respectively. The deployment of each brain area in different cognitive functions was measured by conducting a meta-analysis of neuroimaging studies. Our results confirmed the pattern of specificity for each brain area and also showed that the left area PGI was far less specific than the left areas PF and AIP. From these findings, we discuss the different evolutionary scenarios depicting the potential co-evolution of the combinatorial and generative components of language and tool behavior in our lineage. (shrink)

Humans can follow different social learning strategies, sometimes oriented toward the models’ characteristics. The goal of the present study was to explore which who-strategy is preferentially followed in the technological context based on the models’ psychological characteristics. We identified three potential who-strategies: Copy the pedagogue, copy the engineer, and copy the friend. We developed a closed-group micro-society paradigm in which participants had to build the highest possible towers. Participants began with an individual building phase. Then, they were gathered to discuss (...) the best solutions to increase tower height. After this discussion phase, they had to make a new building attempt, followed by another discussion phase, and so forth for a total of six building phases and five discussion rounds. This methodology allowed us to create an attraction score for each participant. We also assessed participants’ theory-of-mind skills, technical-reasoning skills, and prosocialness to predict participants’ attraction scores based on these measures. Results show that we learn from engineers because they are the most successful. Their attraction power is not immediate, but after they have been identified as attractors, their technique is copied irrespective of their pedagogy or friendliness. These findings open avenues for the study of the cognitive bases of human technological culture. (shrink)