Stranded: a classroom game for implicit bias elicitation and recognition

Implicit biases towards groups of people is acquiring an increasingly stronger focus in many areas of our society. Recognizing these biases is a difficult task, as biases are subconscious and socially unacceptable. We propose Stranded, a game in which players are led to reveal and recognize possible racial and gender biases. Players face challenges, inspired by real-world examples of bias-inducing situations, where they must assign the type of person they think fits a particular task, in a group survival context, and with limited time and knowledge. After each round, the ideal character for each task is given away through small hints; ultimately, players will not survive the challenge if they ignore them and rely on prior biases. This spurs players to think more deeply about characters in terms of inner strengths rather than prior biases. Stranded is an effective tool for raising interesting classroom discussions, by anonymously collecting the decisions made by all players, and showing their aggregate outcomes per task, which easily leads to a conversation on the motivation for certain decisions. An evaluation of Stranded shows that it is effective at provoking players to make biased judgements and that a considerable percentage of players felt more aware of their biases after playing the game.

@InProceedings { HFLWSSB22,
  author       = "Huang, Andrew and Fu, Yuan and Leeuwen, Dexter van and Wu, Lian and Sebus, Siert and Song, Yingkai and
                  Bidarra, Rafael",
  title        = "Stranded: a classroom game for implicit bias elicitation and recognition",
  booktitle    = "Proceedings of ISAGA 2022 - 53rd conference of the International Simulation and Gaming Association",
  volume       = "LNCS XXX",
  year         = "2022",
  url          = "http://graphics.tudelft.nl/Publications-new/2022/HFLWSSB22"
}