Royal Holloway, University of London

Dr Rob Lachlan

Reverse-engineering learning from culture: from revolutionary whales to polluted birds

Variation in cultural traits, from dialects to values, can be seen as the outcome of interactions between individual processes of learning and cognition and population processes of cultural evolution. That means that if we can measure cultural variation, and if we understand population structure, and if we have a reasonable model of cognition, then it might be possible to work backwards and infer quantitative details of how animals or people learn, from culture. We have developed a toolkit for doing this (using Approximate Bayesian Computation with agent-based simulations) in the case of animal vocal culture, and I will summarise some of our recent results. Why do humpback whales undergo vocal revolutions, but only in the southern hemisphere? Why have island chaffinches lost the ability to learn precisely? And how might London air pollution affect great tits’ song learning? I would like to discuss how this approach may or may not be of use when applied to human culture.

Dr Michal Chmiel

Individual and collective differences in the predisposition to share fake news.

COVID 19 has, and will have, negative effects on people despite their geographical location. Worryingly, it has also exacerbated existing inequalities among certain groups – for example, among those identified as more vulnerable were those individuals suffering from worse mental health, in poverty, ethnic minorities, and LGBTQ+ communities. All of them are said to be at greater risk of loneliness (Jones et al. 2021). Also, early research shows that narcissism and machiavellism increase the perception of threat during COVOD-19 (Hardin et al. 2021). Even before the pandemic, digitisation, polarisation and atomisation of media has enabled a marketization of truth. However, PR – an academic discipline that deals with the communication-based relationships between organisations and their audiences - has not attended with due diligence to audiences’ characteristics that may explain the dissemination of untruthful content. My broad goal was to investigate shared/collective characteristics of those (audience members) who have a propensity to share false content on social media.