For P3, I worked on CA$H OR CREDIT, a board game that models the US Credit Score System. The central values of this game are financial literacy, financial decision-making, risk-taking, and responsibility. As players move around the board, they can decide about purchasing assets, paying off bills/loans, getting college degrees, and going into debt. All decisions made affected one’s credit score, and one’s credit score affected the financial opportunities and decisions made after that. In the end, the game’s mechanics afforded a pretty accurate model of the credit system, emphasizing the importance of the credit score in the US financial system.
Before going into this project, I did not expect to gain as much insight into social dynamics as I did. In previous games, we aimed to teach something or make others feel something, but with this system game, I realized that we were aiming to not only “role-play” a real-world system through the game but also encourage the emergence of real-world dynamics that the system affords through its design, whether intentional or not. When seeing the natural behaviors that the players took on as participants in the system, I learned so much about why different scenarios that occur in real life happen as a result of this system. Given that we were able to model the system successfully through the mechanics of the game, natural by-products of the real-world system began to emerge in the game automatically, without our intention. For example, our players started budgeting to plan for bill pay and decided only to take on debt strategically if they knew they could make it to payday on time to afford to do so. Other players consciously decided to take out loans to improve their credit score, even if they could afford the asset. The game also sparked genuine curiosity about the credit score system from players who were formerly unfamiliar with it and stories from those who have had experiences with it. Because of these moments of insight, seeing others play the game was the most interesting part of the whole experience of building this game.
Modeling a complex system such as the US credit score system is complicated. Many intricacies make it difficult to fully model the system’s complexity in such a short amount of time. We quickly learned this and understood that reaching a good version would take many iterations. Even though we did successfully model our system with our game, we recognize that we could do an even better job with more time, getting every detail of the complexities correct. Therefore, I will take this game on for P4, and continue polishing it to get it just right.
