Nature: Causal understanding is not necessary for the improvement of culturally evolving technology

A contrived experiment used to support a sweeping conclusion, but still cool. Explicit causal or theoretical understanding is of course hugely important for technological progress, but it’s not the only way technological progress happens.

As Yann LeCun has pointed out (and personally experienced with deep learning and neural networks), sometimes our wrong explicit theories get in the way of us psychologically accepting empirical results that contradict them. Hence they get in the way of the pre-theoretical tinkering or experimentalism that is the source of a lot of technological progress.

For a contrasting perspective, look to David Deustch’s emphasis of explicit explanatory theories.

Abstract

Bows and arrows, houses and kayaks are just a few examples of the highly optimized tools that humans have produced and used to colonize new environments. Because there is much evidence that humans’ cognitive abilities are unparalleled, many believe that such technologies resulted from our superior causal reasoning abilities. However, others have stressed that the high dimensionality of human technologies makes them very difficult to understand causally. Instead, they argue that optimized technologies emerge through the retention of small improvements across generations without requiring understanding of how these technologies work. Here we show that a physical artefact becomes progressively optimized across generations of social learners in the absence of explicit causal understanding. Moreover, we find that the transmission of causal models across generations has no noticeable effect on the pace of cultural evolution. The reason is that participants do not spontaneously create multidimensional causal theories but, instead, mainly produce simplistic models related to a salient dimension. Finally, we show that the transmission of these inaccurate theories constrains learners’ exploration and has downstream effects on their understanding. These results indicate that complex technologies need not result from enhanced causal reasoning but, instead, can emerge from the accumulation of improvements made across generations.

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