  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.
