Igor Grossmann is an Associate Professor of Psychology at the University of Waterloo, Canada, where he leads the Wisdom and Culture Lab. As a cognitive/social scientist, Grossmann has been working on demystifying what makes up a “wise” judgment in the context of revolving societal and cultural changes. His chief work aims to uncover misconceptions about wisdom and societal change and identify cultural and psychological processes that enable people to think and act wisely. Grossmann’s work has been published in outlets such as Nature Human Behaviour, Science Advances, Proceedings of the Royal Academy: Biological Science, Proceedings of the National Academy of Sciences of the United States of America, Perspectives on Psychological Science, Psychological Science, Journal of Experimental Psychology, and Journal of Personality and Social Psychology.
His contributions have been recognized through numerous awards, such as the Joseph B. Gittler Award from the American Psychological Foundation, the SAGE Young Scholar Award from Society for Personality and Social Psychology, and the Rising Star Award from the Association for Psychological Science. In the past, Grossmann has served as an Associate Editor of Emotion, and Social Psychological and Personality Science, and currently he serves as the Editor-in-Chief of Psychological Inquiry. He co-hosts the “On Wisdom Podcast,” which aims to disseminate scientific insights from cognitive and social sciences to both academic and general audiences. Professor Grossmann holds a Ph.D. in psychology from the University of Michigan.
Where do you see the most exciting research/debates happening in your field?
There are many discussions happening in psychology these days. Many of them concern meta-scientific questions about the role of replication in the advancement of theory (e.g., how does one amend a theory or a phenomenon when it fails to replicate?). Or questions about the generalizability of lab-based experiments and surveys on specific subsamples -often North American college students- and whether they are applicable not only to the broader population but also to different cultures. Additionally, questions about how to reduce confusion about the concepts social scientists use; that is, when the same concept is meant to describe different phenomena or when different names are used to describe the same phenomenon. Beyond meta-theory, there are exciting questions about cultural evolution, (ongoing) societal changes, and misperception of such changes, often fuelled by misinformation and political polarization. The latter two topics of misinformation and polarization became central to much topical discussion in social psychology in the last few years.
How has the way you understand the world changed over time, and what (or who) prompted the most significant shifts in your thinking?
I am not sure which shifts have been most significant, and I am mindful of creating a post-hoc narrative here. Thus, the following pointers are presented chronologically, without any claim to a particular order of significance. I was born in the Soviet Union in early 1980s and adored history, so when the society collapsed and values in my home country of Ukraine started to shift in the early 1990s, changes in new history books my school received were both salient and surely influenced my world view about the fleeting and socially constructed nature of things societies value. Later on, my family ended up as refugees in Germany, where my worldview was further shaped by various forms of social stratification, hierarchy, and prejudice we experienced as immigrants from Eastern Europe. And when I started to study psychology, many of my mentors and colleagues in Germany, United States, and Canada greatly shaped how I understand psychological phenomena, including the cultural grounding and temporal dimensions underpinning these phenomena.
How have recent advancements in analytical methods (machine learning / NLP, big data etc.) enhanced our ability to understand how humans make sense of their world and societal change?
For some questions, relevant computational approaches enable scholars to analyse massive amounts of text-related, social media, or archival data. Consequently, the models may provide a more refined picture of how humans talk about certain phenomena, how they behave, and how relevant patterns of language and behavior change over time. A caveat here is that the computational approaches are still quite crude and may not be applicable for all research questions. Further, algorithms used in such computational approaches can be heavily biased—an expanding area of research.
In your publications ‘Expert predictions of societal change: insights from the world after COVID project’ and ‘Insights into the accuracy of social scientists’ forecasts of societal change’ you analysed interviews from some of the world’s top behaviour and social science experts. What were the most significant insights from this research?
There were three. First, opinions varied dramatically: there were more opinions than there were scientists interviewed! Second, scientists expressed a great deal of uncertainty when making predictions during the first year of the pandemic. Both in terms of mentioning the same topic as having a potential for improving and damaging society and in terms of affective sentiment: they often used mixed affect sentiment when talking about positive as well as negative consequences. Third, if there was any agreement on predictions of what the most important consequences of the pandemic may be (the time after the pandemic is over), those predictions appeared to mirror what was on people’s minds at a given moment. For instance, in the summer of 2020 most common themes concerned the issues of social justice and inequality, while in the fall of 2020 (right before the US election) such themes concerned political polarization. In short, events of the present appeared to bias scientists’ forecasts of the future.
What were the main challenges in forecasting psychological and societal changes during this period of Covid?
As outlined above, it is hard to ignore the “power of the situation” – if social injustice or political polarization are on your mind because that’s what most media write about, you may be tempted to project that these issues will continue to be the most important ones in the future. But there is also a bigger issue at stake: most social scientists, including many members of the scientific elite I interviewed, don’t have formal training in prediction-oriented science. As social scientists, we often rely on explaining the past. But we rarely think about the generalizability of our explanations when faced with the question of predicting the future. Also, our theoretical models are largely underspecified, merely stating that a certain event will be more or less likely to occur—this approach is hardly suitable for making specific predictions for the complex world we live in.
You also noted that you initially predicted greater convergence in predictions than observed. Why did so many experts had diverging opinions on the same matter? Would achieving a consensus ultimately be a positive thing?
I can only speculate about some of the reasons for the divergence in opinions. On the one hand, most scientists did not have a theoretical template or framework for the role of a once-in-a lifetime event such as the COVID-19 pandemic on human societies and behavior. Without a common framework, opinions may take an ad-hoc form. On the other hand, I deliberately sampled top scholars from diverse fields in social, environmental, and political sciences. So, the diversity in predictions may be a consequence of different disciplinary orientation.
Whether consensus would be desirable depends on the goal of an expert elicitation project. If you aim to figure out a likelihood for a specific event to occur (e.g., the likelihood of NATO getting actively involved in the Russian-Ukrainian conflict), consensus may reflect precision in experts’ estimates. But if the goal is to cast the net wide and consider all possible consequences of a major event, diversity may be more desirable.
In ‘Cultural Change: The How and the Why’ you delve into the mechanisms of cultural change. What are the most important factors in determining the how and why societies change?
There are several, including duration and potency of ecological events, socio-economic forces (including stratification, educational attainment, GDP), as well as factors influencing speed of cultural transmission. For instance, tightness or looseness of cultural norms may impact the speed of change or the observation that negative information tends to spread faster and reach more people than positive information on social media.
What role does cross-temporal research on culture and psychology play in the future of international relations and politics?
Cross-temporal research allows one to go beyond static cultural differences, to model cultural processes and how they change over time. Consequently, it captures the dynamic features of culture that have so far been neglected from some of the academic and international relations discourse. The key challenge for cultural change research concerns availability of reliable data with good temporal resolution over time. Without good data, estimates of cultural change in generosity, traditionalism, violence, or attitudes toward climate change remain speculative. The latter may be convenient for political pundits, as their claims about the direction our societies remain unchecked. To ensure greater accountability, reduce misperceptions, and provide clarity to the public, we need much greater investment into systematic measurement of cross-temporal trends about cardinal aspects of human welfare and societal change at scale.
What is the most important advice you could give to young scholars of international relations?
Don’t be afraid to ask challenging questions that make others uncomfortable. And try to find good (robust and reliable) data to address them.
Further Reading on E-International Relations