“This is a story of how harmless choices can make a harmful world,” claims Parable of the Polygons, an online series of simulations that aim to show the cascading effect of collective bias on segregation. This style of simple, friendly sections of text that serve partially as instructions and partially as explanation continues throughout the post, and pairs nicely with simple mechanics and cute renderings of triangles and squares.
Parable of the Polygons reads less as one cohesive game, and more as a series of simulations connected by text, or a “playable post” (Hart). The game is a reworking of American economist Tom Schelling’s model of segregation, aiming to make it more dynamic and digestible to the average user. The model looks at how collective bias induces self-segregation, as “even when individuals (or ‘agents’) didn’t mind being surrounded or living by agents of a different race, they would still choose to segregate themselves from other agents over time” (McCown). The model claims that with a collective bias, no matter how small, agents will move within the community until they have self-segregated themselves, despite claims that they seek out or are at least okay with diversity in their area. Two types of agents are placed on a grid randomly, then have a set percentage of neighbors that must look like them to be “satisfied,” while unsatisfied agents move around the board randomly, stopping once they are satisfied, until all agents have settled.
As with any model, Schelling’s faces some issues with oversimplification, and so Parable of the Polygons must also take on these weaknesses. The same threshold of how many neighbors must be the same type of agent is the same for all agents, “even though in reality everyone might have a different threshold they are satisfied with” (McCown). The model also only stands for a single collective bias, being unable to deal with multiple, layered biases without completely collapsing into chaos. The model also segments the hypothetical society into only two segments, when in reality most societies deal with a far greater number of segments that are more nuanced than two different shapes. In these aspects, Parable of the Polygons also suffers, as while it makes the problem of segregation approachable and easily understood, it simplifies real-world factors, making the society it portrays in the game not quite equivocal to any real-world society or nation.
The personification of triangles and squares, the “agents” in the simulations, aims to represent, but also simplify, real-world attitudes on bias. While the polygons become unhappy if less than a set percentage of their neighbors look like them and become happy if their threshold is met, they also experience a third emotion. When there is not enough diversity for the polygon’s liking, they take on a “meh” emotion, signifying that they would rather have a diverse community around them, but also that they are not willing to move in order to satisfy that need. In this way, Parable of the Polygons exceeds the original model, portraying the complacency that often leads to stagnation in creating diversity in the modern world; people perceive there’s a problem in a homogenous society, but are also complacent, unwilling to risk being put in a group in which they are the minority.
Although much of the game consists of simulations that the player runs, the beginning portion allows the player to move the pieces themselves. The game encourages the player to not “think too much about it” as they move each polygon, perpetuating the idea that the moves to only be comfortably diverse but still a majority are truly instinctual for many peoples (Nicky Case and Vi Hart 2014).
The simulations that the player runs also show a graph with segregation on the y axis and time on the x axis, allowing the player to see the chaos of movement in the grid and quantify it. The game encourages the player to run the first simulation a couple times, and for good reason; the boards are set up randomly, and in some cases, segregation remains at under 40% and ends within a relatively short period of time, acting slightly against the point that the creators are making. The general curve of the graph always remains the same, however, in how steep it is, showing how even small biases lead to dramatic segregation in a short period of time.
In the next simulation, the player can control the percentage of bias for each polygon and then run the simulation, seeing that if they reset the board and lower the percentage, the graph shows far less segregation over time. However, the game points out that “the real world doesn’t start anew with a random shuffling of citizens every day” as it moves to the next simulation, showing that the world starts segregated, and lowering the bias does nothing to relieve that. The shapes are complacent with their position, and don’t move even with a lower bias, because they aren’t being urged to seek out diversity.
However, this simulation can run into a bit of a paradox, as if the player decides to raise the percentage, at a certain point – around 80% or higher – the chart actually shows segregation lowering as the model struggles to move shapes to an increasingly difficult spot, resulting in the graph showing that with a higher bias, segregation actually lowers over time, although it lasts far longer than times when the player may run the simulation with a lower bias.
The final two simulations play with differing percentages of bias with each polygon, and percentages of diversity that the polygons seek out. In this instance, the game shows the player just how actively looking to create a diverse community collectively can bring about true change and lower segregation within society. It is not enough to be complacent with simply not holding a bias, but rather the game urges the player to seek out people of different backgrounds to surround themselves with.
At the bottom of the game, the creators offer their summaries of the message, reminding players that if someone is pointing out systemic prejudice they are not attacking specific individuals, that diversity and equality take active work, and that the individual can be the change if they reach out and fight against segregation in their community. This last note is not resonated as strongly throughout the game, as the simulations themselves focus instead on collective bias, not allowing for the player to see the impact of individual change.
Further beyond, the creators list ways in which the player can take real-world action to help diversify fields, especially the tech industry. It’s a widely known fact that far fewer women go into STEM fields, and many face discrimination within the tech industry once they enter it. The game then directly ties to this issue as it points out that simply acknowledging that women are welcome in technology jobs is not enough, and that companies must actively seek out to abolish the continuing segregation that comes about form complacency.
Overall, Parable of the Polygons works well in dealing with “two subjects that get a really defensive and hateful reaction…mathematics and social justice” (Hart). In not targeting the player specifically, and quantifying the results of the simulation, Parable of the Polygons grounds itself in fact and remains a friendly reminder to players, rather than a hostile attack that may have only shut down conversation around the topic. However, it does simplify the problem, and the simulations lack as much player participation as the initial game, as well as running into a few glitches that yield confusing conclusions. If anything, Parable of the Polygons is a refreshingly logical take on a social issue that seeks not to demonize, but simply educate.
McCown, Frank. “Schelling’s Model of Segregation.” Schelling’s Model of Segregation.
Harding University, n.d. Web. 01 Apr. 2017
Hart, Vi. “Parable of the Polygons.” Blog post. Vi Hart. WordPress, 8 Dec. 2014. Web.
Parable of the Polygons. Nicky Case and Vi Hart. 2014. Video game.