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Dark Pattern: A Serious Game for Learning About the Dangers of Sharing Data

Dark patterns refer to tricks built into websites and apps to manipulate users into acting unintentionally and detrimentally. An important issue is how such patterns might affect behaviour when actors are manoeuvred towards the sharing of their personal data, as exemplified in choices we face when downloading Apps or signing up for services provided on the internet. This paper presents our exploratory research into understanding the intention and subsequent actions of older teenagers responding to issues of personal data collection and (mis)use. The research is based on the competitive board-game Dark Pattern, in which players install apps, draw dark pattern cards, and make choices about the sharing of personal data. To win the game, a player must share as little data as possible and play cards that punish other players. We were interested to find out the extent to which the game was able to convey types of dark patterns to the players. Additionally, we wanted to explore how players’ perceptions of risks in data-sharing associated with their intention to protect their personal data. Finally, we were interested to explore potential gender difference, and whether this might be associated with intention to protect personal data. 56 of the students who played the game answered a subsequent survey with questions about their experiences and the data was analysed using Partial Least Squares – Structural Equation modelling (PLS-SEM). Despite the findings showing that playing the game had only limited impact on knowledge about dark patterns matters, the analysis of the relationship with the factors in our model shows that knowledge has a significant contribution on behavioural intention, demonstrating that students with high dark pattern knowledge also report higher intention to take steps to protect their data.