Invention as a combinatorial process: evidence from US patents

Youn, Hyejin; Strumsky, Deborah; Bettencourt, Luís M. A.; Lobo, José

doi:10.1098/rsif.2015.0272

Cited by 205 publications

(191 citation statements)

References 34 publications

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“…We take into account insights from recent theoretical and empirical work on cognitive processes that might underlie creativity (57,70), ideas from developmental psychology and cognitive science (68)(69)(70)(71), and a detailed view of how technological innovations develop (influenced by refs. [72][73][74]. Our model also is inspired by the long-standing debate regarding punctuation versus gradualism in related fields (6,8,(75)(76)(77)(78)(79).…”

Section: The Modelmentioning

confidence: 99%

Evolution in leaps: The punctuated accumulation and loss of cultural innovations

Kolodny

Creanza

Feldman

2015

Proc. Natl. Acad. Sci. U.S.A.

138

185

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Archaeological accounts of cultural change reveal a fundamental conflict: Some suggest that change is gradual, accelerating over time, whereas others indicate that it is punctuated, with long periods of stasis interspersed by sudden gains or losses of multiple traits. Existing models of cultural evolution, inspired by models of genetic evolution, lend support to the former and do not generate trajectories that include large-scale punctuated change. We propose a simple model that can give rise to both exponential and punctuated patterns of gain and loss of cultural traits. In it, cultural innovation comprises several realistic interdependent processes that occur at different rates. The model also takes into account two properties intrinsic to cultural evolution: the differential distribution of traits among social groups and the impact of environmental change. In our model, a population may be subdivided into groups with different cultural repertoires leading to increased susceptibility to cultural loss, whereas environmental change may lead to rapid loss of traits that are not useful in a new environment. Taken together, our results suggest the usefulness of a concept of an effective cultural population size.T he breadth and diversity of cultural traits and their rates of accumulation have received a great deal of scholarly attention. Scientific knowledge in many fields appears to accumulate exponentially (1, 2). However, although the number of tool types in the archaeological record also seems to fit this pattern of exponential increase broadly (3), the number of tools and other cultural traits does not increase steadily and monotonically over time. Depending on the timescale studied, change in tool repertoire may appear punctuated and stepwise. Long, seemingly static, periods are interspersed between "cultural explosions," periods of sudden cultural accumulation (3-13). Further, in some populations, there is evidence that whole suites of cultural traits, such as the ability to make tools, clothing, and fire (14-16), may be lost, defying the general trend of cultural accumulation over time (4,7,8).Reasons for the sudden changes in hominid material culture in the archaeological record continue to be debated; they could be related to demographic factors (17), rapid cognitive change (18-21), relatively sudden changes in hand morphology (22, 23), or dramatic climatic shifts (10,(24)(25)(26)(27)(28). Further, intermediate-scale environmental change or migration to a new environment also could affect the accumulation and loss of traits that are primarily useful in specific environments (29-33). In addition, the relationship between the number of cultural traits in a population and population size has been debated (4,14,29,(34)(35)(36)(37)(38)(39)(40)(41); this relationship also might depend on the social learning strategies of the population (42, 43). Further, there could be a feedback process between the number of tools in a population and the population size: A larger population might be able to invent and retain m...

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Section: The Modelmentioning

confidence: 99%

Evolution in leaps: The punctuated accumulation and loss of cultural innovations

Kolodny

Creanza

Feldman

2015

Proc. Natl. Acad. Sci. U.S.A.

138

185

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“…Technologies typically arise from a cumulative process that operates through incremental changes within path-dependent technological trajectories and by combining traits that have evolved along different trajectories (19)(20)(21). Screws, for example, are relatively simple artifacts that can be improved incrementally by using better materials, modifying head shape, or using a different kind of thread.…”

mentioning

confidence: 99%

Partial connectivity increases cultural accumulation within groups

Derex

Boyd

2016

Proc. Natl. Acad. Sci. U.S.A.

230

273

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Complex technologies used in most human societies are beyond the inventive capacities of individuals. Instead, they result from a cumulative process in which innovations are gradually added to existing cultural traits across many generations. Recent work suggests that a population's ability to develop complex technologies is positively affected by its size and connectedness. Here, we present a simple computer-based experiment that compares the accumulation of innovations by fully and partially connected groups of the same size in a complex fitness landscape. We find that the propensity to learn from successful individuals drastically reduces cultural diversity within fully connected groups. In comparison, partially connected groups produce more diverse solutions, and this diversity allows them to develop complex solutions that are never produced in fully connected groups. These results suggest that explanations of ancestral patterns of cultural complexity may need to consider levels of population fragmentation and interaction patterns between partially isolated groups. cultural evolution | innovation | population size | social network | technological trajectory P eople everywhere rely on technology for their survival (1). In even the simplest foraging societies, essential tools are beyond the inventive capacities of individuals; they result from a cumulative process by which innovations are gradually added to existing cultural traits across many generations (2). Recent work suggests that a population's ability to develop complex technologies is positively affected by its size and connectedness (3-5). Large interaction networks allow individuals to learn from many others, and theory predicts that increased opportunities to learn socially reduces the rate of cultural loss and increases the rate at which people improve existing cultural traits. This prediction is supported by evidence from both field and laboratory studies (5-10). However, some authors have been reluctant to embrace this idea, pointing out discrepancies between measures of population size and observed cultural complexity (11)(12)(13)(14). It seems likely that factors other than social network size affect the evolution of cultural complexity, and these factors may obscure the effect of the population size under some conditions.One possibility is that social network structure matters as well. Economists have recently investigated how levels of connectedness in networks affect a group's ability to solve problems of varying complexity (15,16). In agreement with previous work in cultural evolution, they found that high levels of connectivity help groups to solve simple tasks. However, they also suggest that wellconnected networks perform poorly at solving complex tasks (15,16). The complexity of a problem can be represented by mapping all possible solutions onto a measure of performance, which results in what has been called a fitness landscape (17). Simple problems are associated with smooth landscapes, each with a unique optimum that will be reached b...

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“…This phenomenon spans multiple scales, to include genes, cells, and individuals. Technological progress also arises by novel combinations of existing components, again on many different levels [7,8]. Heredity is paralleled by the combinatorial evolution of existing elements from simpler to more complex, while engineering and market mechanisms, expressed as utility and demand, parallel selection's filter [9].…”

Section: The Digital Organism?mentioning

confidence: 99%