- Journal: Communications in Computer and Information Science (CCIS), vol. 1936, p. 332–343–12, 2024
- Utgiver: Springer
- Trykt: 1865-0929
- Elektronisk: 1865-0937
Tricks used in websites and apps to make you do things that you do not intend to do are often referred to as dark pattern. This paper presents the board-game Dark Pattern about installing apps. The players draw cards, make choice about data that the app would like to collect and use. To win the player must avoid sharing personal data. The game was played with 102 students. After playing the game the players answered a survey with questions about their knowledge about the dark patterns types featured in the game. In addition, 50 students answered the same survey without playing the game. In the paper we present key findings about the dark patterns knowledge generated by playing the game and present an exploratory analysis using Partial Least Square – Structural Equation modelling (PLS-SEM). We analysed whether dark patterns knowledge and risk perception, the likelihood of negative incidents due to data sharing, could predict the players behavioural intention to take proactive privacy steps. The PLS-SEM models have a variance explained (R2) of 0.17 indicating that 17% of the variance could be accounted for by the two variables included in the model. Taken together, the analyses indicated that playing the Dark Pattern game had weak positive effect on behavioural intention to proactive privacy steps.