Causal understanding is not necessary for the improvement of culturally evolving technology (paywalled)

I’ve been struggling a bit with writing a chapter on how we should research technologies, especially soft technologies, in the light of their innate complexity, the difficulties of identifying relevant boundaries, their situated nature, the impossibility of identifying all possible uses for any soft technology (and the immense importance of the role of the user in their enactment), and the fact that they are far from fixed, amongst other things. This (regretably paywalled) paper helps support the theoretical model I am developing. Using an experimental method, it shows that technologies can be developed, and can gain in sophistication and complexity over multiple generations, without any of its designers having an accurate or complete understanding of how they work. It is particularly interesting when viewed through a lens of distributed/situated/extended cognition because of the role the technology itself plays in its evolution, and it accords very well with Kauffman’s notion of the adjacent possible and Arthur’s theory of technological evolution.

From the abstract…

“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.”