TechnEQ:Simulations

Dilemma Party

This simulation blends the idea of "Prisoner's Dilemma" from Game Theory with the idea of tokens from Tokenomics. It shows what happens when a group of individuals with different starting mindsets interact in a group to form tribes. In this model, software robots take the place of people and move about interactng with each other. Each robot is represented by a disk that shows its interaction preferences. The colors red, blue, and green represent the desires for different kinds of tokens. the color grey represents a tendency toward aggressive behavior that benefits one individual at the cost of another. In order to build groups, the robots remember interactions with others they meet. Mutually successful interactions are remembered and repeated. Also, robots that experience an aggressive interaction from another remember that interaction and retaliate the next time they meet.

As the robots interact with eachother, socially agresssive behavior is squeezed out, and the robots begin to congregate in groups defined by shared preferences, which are reinforced over time.

The simulation window that opens requires Java. If you see a button underneath, Java is already installed. If there is no button, you'll need to install Java to view the model. Furthermore, note that the window that opens to display the simulation may be behind your browser window when it appears. To learn more about the methodology behind this model, click here.

What the simulation above shows us is that modeling group interactions does not require that we model the full depth of human culture. We can see many elements of human behavior by simply selecting the right aspects of human behavior for our model. The Tokenomics approach lets us understand that acquiring social value by matching expectations will occur in every social setting, regardless of the details we pick. This helps us draw out truths in human interaction that otherwise would be much harder to see.

For a more concrete example of how such models can be applied, take a look at this second simulation. Here, we have added a 'leader/team-member' dynamic to the model. Large disks represent leaders. Small disks represent team members. The movement of leaders is affected by other leaders. The movement of team members is affected by other team members, and strongly by leaders.

In order to explore the effects of different organizational cultures, we have added two switches: 'Team Member Feedback' and 'Leader Listening'. When 'Team Member Feedback' is off, team members don't feel entitled to respond negatively to leaders when leaders act agressively toward them. When the feedback switch is on, team members hold leaders accountable, as they do each other. When 'Leader Listening' is off, leaders don't remember the specifics of positive interactions they have with team members, only the interactions with other leaders. When 'Leader Listening' is on, leaders remember the interactions with team members as clearly as they do with other leaders.

We've also added a 'view-style' button that will allow you to swap from the view that shows the interaction styles of the robots, to how they're feeling, as measured by whether their recent interactions have been positive or negative.

What this simulation shows us is that just removing these two simple features from an group (team feedback and leader listening) is enough to create the picture of a classic dysfunctional organization, in which leaders are uniformly aggressive and team members experiences are broadly negative. We didn't need to model any elements of human psychology beyond expectation matching, or any of the details of human interactions. The simple application of Tokenomics suffices. The simulation also shows the effects of turning either one of these traits on in isolation. Activating 'Leader Listening' is like sending all your managers on employee recognition training. Activating 'Team Member Feedback' is like implementing a shared accountability program of the sort used to improve safety in the airline industry. Both have quite different effects, as the simulation reveals. Simulations such as this are enabling us to unpack the years of wisdom that have been accumulated in leadership training into tools that can make useful predictions about workplace dynamics.