Doctoral Thesis: A Research Model of Cultural Evolution Helps Better Explain Patterns In Cultural History

Cultural evolution is a field of science that studies how and under what conditions information acquired during a lifetime can be passed on between generations or within a community. For example, it has been used to try to explain how technologies created by some ancient cultures have ceased to be used when the necessary knowledge has not been preserved and passed on. Cultural evolution also helps to explain how visual arts gets close to the boundaries of the human mind, or how the behaviour of other animals can be significantly shaped by members of the same species through skills that have been preserved over generations. Research methods based on the principles of cultural evolution can be used to create quantitative data sets and model cultural change, explains Peeter Tinits, who defended his doctoral thesis at Tallinn University.

In his doctoral thesis, Tinits used cultural evolution methods to address three topical issues in the field. Broadly speaking, these questions can be formulated as follows: how can the structure of a language be affected by the conditions of its use? How can the history of art reflect people's perceptual preferences? Can the collective learning processes familiar from the development of technology also be seen in art? To address these questions, Tinits, with the help of colleagues, carried out three small research projects, based on both public and self-collected data.

To answer the first research question, a language learning experiment was carried out in which participants learned to use a small artificial language. The experiment also created simplified "generations": the messages they created were passed on to the following participants to learn from. The results of the experiment showed that, in situations where it is more difficult to distinguish what needs to be done to successfully communicate information, the language used became more complex. Certain meanings were clarified even when it was not strictly necessary.

To address the second question – the developmental relationship between art and perceptual preferences – Tinits and colleagues collected data on narrative devices in films. More specifically, it focused on anachronisms. An anachronism is a narrative technique that interweaves scenes from the past and the future into a central story. Previous research shows that this technique is well suited to creating excitement in the viewer. An analysis of the distribution patterns of anachronisms in the best known action films of the last 40 years has shown how this technique has become an increasingly important narrative technique in them. In this development we can see one way in which art has gradually adapted to people's perceptual preferences.

The third research question – on the manifestation of collective learning processes in art – was solved by Tinits and a colleague using public big data. They looked at how the structure of film production teams has changed in popular films over the past 100 years. The analysis showed that new useful jobs were constantly being found in film production. This is analogous to technological progress, which is based on the accumulation of many small innovations. Audiences' expectations of popular films have grown over time, which has also increased the need for production teams with ever greater and more diverse skills.

Systematic observation of learning processes in results of experiments and in big data will help better explain patterns in cultural history. Peeter Tinits's doctoral thesis illustrated that it is possible to approach the story of culture as a kind of collective intellect in a quantitative and data-driven way. This is why the quality and accessibility of cultural history datasets allows evolutionary models to be applied more widely, Tinits stresses. These models help us understand both cultural diversity and universals, and how they have evolved through the interplay of human experience and history. The models developed are not only human-centred, but are also applicable to other living organisms that may similarly depend on the skills acquired from other members of their species to survive and thrive.

Peeter Tinits, a PhD student at Tallinn University's School of Humanities, defended his PhD thesis "Cultural Evolution in Language and Art" on 26 November. The thesis supervisors were Professor Emeritus Krista Kerge and Professor Reili Argus, both from Tallinn University. The opponents were Gareth Roberts, Associate Professor at the University of Pennsylvania, and Monica Tamariz, Associate Professor at Heriot-Watt University.