The Collective Learning Network is a network of researchers and practitioners from diverse disciplines and countries investigating the opportunities of new technologies for collective learning—the ability of human groups to adaptively organize and exchange information to overcome individual and collective challenges.
Our quarterly Virtual Seminars explore the potential benefits and risks of new technologies for collective learning. While artificial intelligence, social media, and communication platforms can augment collective learning through data-driven insights, they also present challenges around misinformation, polarization, and erosion of trust.
"Collective discourse norm change through counterspeech" - Cathy Buerger
This talk examines how counterspeech, direct responses to hatred that seek to undermine it, can contribute to positive norm change in online discourse. I present insights from my own qualitative research to illuminate how counterspeech—particularly when enacted collectively—can shift online discourse norms in a potentially sustainable fashion. By analyzing how individuals coordinate, frame, and do counterspeech in real-world contexts, I offer an explanatory account of how groups come together with the goal of transforming collective understandings of what constitutes civil communication.
"Studying Cooperation through Integrative Experiments" - Abdullah Almaatouq
The dominant paradigm of experimental social and behavioral science views an experiment as a test of a theory, where the theory is assumed to generalize beyond the experiment's specific conditions. But in reality, the process of integrating and reconciling findings from many different experiments conducted in different settings seems to happen either inefficiently or not at all. I will outline an approach that effectively inverts the usual sequence of social scientific reasoning, starting first with the question of generalization ("over what domain/situations do I want my theory to apply?"), then conducting the relevant experiments and analysis, and only then interpreting the results in terms of existing (or new) theory. I will go over how to apply the integrative experiment design approach with an example from my research on mapping the effect of punishment on social welfare in public good games.
"Hysteresis as an obstacle to collective learning" - Katarzyna Sznajd-Weron
Hysteresis is a collective phenomenon in which a system's response lags behind and depends on its past history. As a collective property, it emerges from the interactions among many elements -- in the case of social hysteresis, these elements are people. While the concept originated in physics, it has since found applications across a wide range of disciplines. In the social sciences, hysteresis has been used, among other things, to understand phenomena such as political polarization and vaccination-compliance problem. The aim of this talk is to show how agent-based models (ABMs) can be used to study hysteresis and the mechanisms underlying it. To build intuition, I will begin with an example from physics that illustrates how hysteresis arises as a form of collective memory. I will then present a simple ABM of binary opinions to demonstrate how hysteresis can emerge in social systems. Finally, I will briefly discuss the key factors that influence the strength and persistence of hysteresis. I believe that studying hysteresis through the lens of ABMs can help us better understand how it may hinder collective adaptation and pose a significant obstacle to effective collective learning.
This is an invite-only event series. To express interest in this or future events, please register on our website.
Speaker
Cathy Buerger