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.

We propose that the crucial difference between human cognition and that of other species is the ability to participate with others in collaborative activities with shared goals and intentions: shared intentionality. Participation in such activities requires not only especially powerful forms of intention reading and cultural learning, but also a unique motivation to share psychological states with others and unique forms of cognitive representation for doing so. The result of participating in these activities is species-unique forms of cultural cognition and (...) evolution, enabling everything from the creation and use of linguistic symbols to the construction of social norms and individual beliefs to the establishment of social institutions. In support of this proposal we argue and present evidence that great apes understand the basics of intentional action, but they still do not participate in activities involving joint intentions and attention. Human children's skills of shared intentionality develop gradually during the first 14 months of life as two ontogenetic pathways intertwine: the general ape line of understanding others as animate, goal-directed, and intentional agents; and a species-unique motivation to share emotions, experience, and activities with other persons. The developmental outcome is children's ability to construct dialogic cognitive representations, which enable them to participate in earnest in the collectivity that is human cognition. Key Words: collaboration; cooperation; cultural learning; culture; evolutionary psychology; intentions; shared intentionality; social cognition; social learning; theory of mind; joint attention. (shrink)

Contrary to Vaesen, we argue that a small number of key traits are sufficient to explain modern human tool use. Here we outline and defend the cultural intelligence (CI) hypothesis. In doing so, we critically re-examine the role of social transmission in explaining human tool use.

Until relatively recently, it was often supposed that changes in the material record of hominin life indexed advances in hominin cognitive sophistication in a relatively direct way. In particular, the “Upper Paleolithic Transition”—an apparently abrupt increase in the complexity and disparity of our material culture—was thought to signal the arrival of the fully human mind. While the idea of a direct relationship between material complexity and cognitive sophistication still has some defenders, this view has largely been abandoned. It is now (...) widely appreciated that aspects of ancient hominins’ demographic and social organization have a powerful influence both on the material culture they need and the material culture they can sustain. But if this more nuanced view is right, what does the deep material record tell us about the evolution of hominin cognition? I explore that question in this article. (shrink)

The complex systems approach to cognitive science invites a new understanding of extended cognitive systems. According to this understanding, extended cognitive systems are heterogenous, composed of brain, body, and niche, non-linearly coupled to one another. This view of cognitive systems, as non-linearly coupled brain–body–niche systems, promises conceptual and methodological advances. In this article we focus on two of these. First, the fundamental interdependence among brain, body, and niche makes it possible to explain extended cognition without invoking representations or computation. Second, (...) cognition and conscious experience can be understood as a single phenomenon, eliminating fruitless philosophical discussion of qualia and the so-called hard problem of consciousness. What we call “extended phenomenological-cognitive systems” are relational and dynamical entities, with interactions among heterogeneous parts at multiple spatial and temporal scales. (shrink)

In 2009, Tennie et al. proposed the theory of the Zone of Latent Solutions, defined as the range of behaviors an individual of a species can invent independently, i.e., which it can acquire without any form of social learning. By definition, species limited to their ZLS are unable to innovate and/or transmit behavioral traits outside their ZLS, i.e., they lack traits which go beyond the level of the individual—traits resulting from a gradual cultural evolution over successive transmission events [“cumulative culture”, (...) Boyd and Richerson ]. However, this does not exclude an influence of social learning on the population frequency of these behaviors: social learning can facilitate the acquisition of latent solutions and thus speed up and consolidate their spread within a population. Cultures—defined as behaviors at least influenced by social learning—are therefore still possible. Here, we elaborate on the ZLS account and relate it to the theories of Vygotsky who studied the role of social learning in human culture. We argue that the ZLS is a missing phylogenetic “baseline” of Vygotsky’s Zone of Actual Development. Vygotsky’s neglect of a need for a human “baseline ZAD” may have been due to his interpretation of Köhler’s work on great ape behaviors: Köhler used his observations on individual chimpanzees to draw conclusions about the chimpanzee species as a whole, stating that chimpanzees can only copy what they could have invented themselves, thus coming close to the ZLS concept. Vygotsky—studying the range of behaviors individuals could achieve independently—seemingly did not see that Köhler was suggesting a species “baseline”, upon which Vygotsky’s idea of an individual’s ZAD could develop. As a result, Vygotsky also did not see the need for a ZLS for his own study subjects: humans. Yet, there is no reason to assume that humans lack a ZLS, and in fact we present evidence for a human ZLS for tool-use behaviors. (shrink)

Since the cognitive revolution, it has become commonplace that cognition involves both computation and information processing. Is this one claim or two? Is computation the same as information processing? The two terms are often used interchangeably, but this usage masks important differences. In this paper, we distinguish information processing from computation and examine some of their mutual relations, shedding light on the role each can play in a theory of cognition. We recommend that theorists of cognition be explicit and careful (...) in choosing notions of computation and information and connecting them together.Keywords: Computation; Information processing; Computationalism; Computational theory of mind; Cognitivism. (shrink)

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 authors find East Asians to be holistic, attending to the entire field and assigning causality to it, making relatively little use of categories and formal logic, and relying on "dialectical" reasoning, whereas Westerners, are more analytic, paying attention primarily to the object and the categories to which it belongs and using rules, including formal logic, to understand its behavior. The 2 types of cognitive processes are embedded in different naive metaphysical systems and tacit epistemologies. The authors speculate that the (...) origin of these differences is traceable to markedly different social systems. The theory and the evidence presented call into question long-held assumptions about basic cognitive processes and even about the appropriateness of the process–content distinction. (shrink)

Early modern humans developed mental capabilities that were immeasurably greater than those of nonhuman primates. We see this in the rapid innovation in tool making, the development of complex language, and the creation of sophisticated art forms, none of which we find in our closest relatives. While we can readily observe the results of this high-order cognitive capacity, it is difficult to see how it could have developed. We take up the topic of cave art and archeoacoustics, particularly the discovery (...) that cave art is often closely connected to the acoustic properties of the cave chambers in which it is found. Apparently, early modern humans were able to detect the way sound reverberated in these chambers, and they painted artwork on surfaces that were acoustic “hot spots,” i.e., suitable for generating echoes. We argue that cave art is a form of cross-modality information transfer, in which acoustic signals are transformed into symbolic visual representations. This form of information transfer across modalities is an instance of how the symbolic mind of early modern humans was taking shape into concrete, externalized language. We also suggest that the earliest rock art found in Africa may constitute one of the first fossilized proxies for the expression of full-fledged human linguistic behavior. (shrink)

The 'developmental systems' perspective in biology is intended to replace the idea of a genetic program. This new perspective is strongly convergent with recent work in psychology on situated/embodied cognition and on the role of external 'scaffolding' in cognitive development. Cognitive processes, including those which can be explained in evolutionary terms, are not 'inherited' or produced in accordance with an inherited program. Instead, they are constructed in each generation through the interaction of a range of developmental resources. The attractors which (...) emerge during development and explain robust and/or widespread outcomes are themselves constructed during the process. At no stage is there an explanatory stopping point where some resources control or program the rest of the developmental cascade. 'Human nature' is a description of how things generally turn out, not an explanation of why they turn out that way. Finally, we suggest that what is distinctive about human development is its degree of reliance on external scaffolding. (shrink)

Cognitive innovation has shaped and transformed our cognitive capacities throughout history. Until recently, cognitive innovation has not received much attention by empirical and conceptual research in the cognitive sciences. This paper is a first attempt to help close this gap. It will be argued that cognitive innovation is best understood in connection with cumulative cultural evolution and enculturation. Cumulative cultural evolution plays a vital role for the inter-generational transmission of the products of cognitive innovation. Furthermore, there are at least two (...) important functions of enculturation for cognitive innovation. First, enculturation is responsible for the ontogenetic acquisition of cognitive practices governing the interaction with innovative products. Second, successful processes of enculturation provide opportunities for subsequent innovative processes. The trans-generational trajectory of calculation from mathematical symbol systems to the first digital computers will serve as a paradigm example of the delicate interplay of cognitive innovation, cumulative cultural evolution, and enculturation. (shrink)

An overview on archaeological evidence, provided by Colagè and d’Errico, reveals that the timing, location, and pace of cultural innovations are more consistent with scenarios that take culture, rather than genetic evolutionary processes, as the key driving force for human cognition. The authors elaborate on those mechanisms by which cultural evolution operates, with a specific focus on cultural exaptation and cultural neural reuse.

While endorsing Gopnik's proposal that studies of the emergence and modification of scientific theories and studies of cognitive development in children are mutually illuminating, we offer a different picture of the beginning points of cognitive development from Gopnik's picture of "theories all the way down." Human infants are endowed with several distinct core systems of knowledge which are theory-like in some, but not all, important ways. The existence of these core systems of knowledge has implications for the joint research program (...) between philosophers and psychologists that Gopnik advocates and we endorse. A few lessons already gained from this program of research are sketched. (shrink)

Artificial intelligence research has foundered on the issue of representation. When intelligence is approached in an incremental manner, with strict reliance on interfacing to the real world through perception and action, reliance on representation disappears. In this paper we outline our approach to incrementally building complete intelligent Creatures. The fundamental decomposition of the intelligent system is not into independent information processing units which must interface with each other via representations. Instead, the intelligent system is decomposed into independent and parallel activity (...) producers which all interface directly to the world through perception and action, rather than interface to each other particularly much. The notions of central and peripheral systems evaporateeverything is both central and peripheral. Based on these principles we have built a very successful series of mobile robots which operate without supervision as Creatures in standard office environments. (shrink)

Second, this collection of cognitive programs evolved in the Pleistocene to solve the adaptive problems regularly faced by our hunter-gatherer ancestors-...

In the last 60,000 years humans have expanded across the globe and now occupy a wider range than any other terrestrial species. Our ability to successfully adapt to such a diverse range of habitats is often explained in terms of our cognitive ability. Humans have relatively bigger brains and more computing power than other animals and this allows us to figure out how to live in a wide range of environments. Here we argue that humans may be smarter than other (...) creatures, but none of us is nearly smart enough to acquire all of the information necessary to survive in any single habitat. In even the simplest foraging societies, people depend on a vast array of tools, detailed bodies of local knowledge, and complex social arrangements, and often do not understand why these tools, beliefs, and behaviors are adaptive. We owe our success to our uniquely-developed ability to learn from others. This capacity enables humans to gradually accumulate information across generations, and develop well-adapted tools, beliefs, and practices that are too complex for any single individual to invent during their lifetime. (shrink)