Generative Adversarial Collaborations: A practical guide for conference organizers and participating scientists

Abstract

Generative adversarial collaborations (GACs) are a form of formal teamwork between groups of scientists with diverging views. The goal of GACs is to identify and ultimately resolve the most important challenges, controversies, and exciting theoretical and empirical debates in a given research field. A GAC team would develop specific, agreed-upon avenues to resolve debates in order to move a field of research forward in a collaborative way. Such adversarial collaborations have many benefits and opportunities but also come with challenges. Here, we use our experience from (1) creating and running the GAC program for the Cognitive Computational Neuroscience (CCN) conference and (2) implementing and leading GACs on particular scientific problems to provide a practical guide for future GAC program organizers and leaders of individual GACs.