Innovation in the collective brain

Abstract

Innovation is often assumed to be the work of a talented few, whose products are passed on to the masses. Here, we argue that innovations are instead an emergent property of our species' cultural learning abilities, applied within our societies and social networks. Our societies and social networks act as collective brains. We outline how many human brains, which evolved primarily for the acquisition of culture, together beget a collective brain. Within these collective brains, the three main sources of innovation are serendipity, recombination and incremental improvement. We argue that rates of innovation are heavily influenced by (i) sociality, (ii) transmission fidelity, and (iii) cultural variance. We discuss some of the forces that affect these factors. These factors can also shape each other. For example, we provide preliminary evidence that transmission efficiency is affected by sociality--languages with more speakers are more efficient. We argue that collective brains can make each of their constituent cultural brains more innovative. This perspective sheds light on traits, such as IQ, that have been implicated in innovation. A collective brain perspective can help us understand otherwise puzzling findings in the IQ literature, including group differences, heritability differences and the dramatic increase in IQ test scores over time.

Keywords: cultural evolution; innovation; intelligence; language; social learning; technology.

Figure 1.

Causal relationships suggested by the cultural brain hypothesis and captured in our simulation. Oblique learning and learning biases refer to the ability to select non-genetic parents with more adaptive knowledge from whom to socially learn.

Figure 2.

Gumbel probability distribution of imperfect transmission, based on Henrich [69]. Analyses by Kobayashi & Aoki [88] confirm that this logic is not specific to Henrich's chosen distribution. For a given skill value z_i, the probability of acquiring a lower level skill (the portion of the distribution to the left of the dashed line) is less than the probability of acquiring an equal or greater skill level (the portion of the distribution to the right of the dashed line): learning is prone to error. As sociality and access to cultural models increases (e.g. through increased population size or density), there is a greater probability of at least one learner possessing skill level z_i or greater and becoming the most skilled cultural model from whom the next generation learns. These assumptions and logic predict a relationship between sociality and equilibrium cultural complexity.

Figure 3.

Relationship between the number of contemporary speakers of a language and the degree to which word lengths have been optimized for communication. The horizontal axis is a log scale. The vertical axis is the correlation between the information content of words and their written length made positive for easier interpretation. (Online version in colour.)