Background

Dissent against authority is ubiquitous throughout human history and culture, as are authorities’ efforts to maintain power, stability, and social order. But communication and surveillance technologies change the risk landscape for dissidents and governments alike. Individuals must make careful choices about whether to express dissent or engage in self-censorship, voluntarily moderating their behavior to avoid punishment by the authority. On the other hand, authorities must weigh their competing goals of suppressing dissent and minimizing punishment costs. A recent paper from the BSS Center analyzes optimal decision making by either party when the other is static (i.e., how should an individual behave based on its own parameters and those of the authority? how should an authority set its policies based on the parameter distributions of its population?). However, many questions remain open about the system’s dynamics when both parties adapt simultaneously.

Research Goals

The scholar team will (1) read and understand the dissent model and existing results, (2) read and understand background literature on opinion dynamics, (3) propose adaptation rules for individuals existing in networks of social influence, (4) propose adaptation rules for the authority beyond random-mutation hill climbing covered in the original paper, (5) conduct simulation experiments of population/authority co-adaptation, and (6) develop insights about this co-evolution, possibly supported by mathematical analysis.

Skills Needed

Linux command line; Python; formal (mathematical) and pseudocode algorithm descriptions

Skills Gained

Learning theory; game theory; agent-based modeling; social complex systems