research-article

Fighting Malicious Designs: Towards Visual Countermeasures Against Dark Patterns

Authors:

René Schäfer,

Paul Miles Preuschoff,

Jan BorchersAuthors Info & Claims

CHI '24: Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems

Article No.: 296, Pages 1 - 13

https://doi.org/10.1145/3613904.3642661

Published: 11 May 2024 Publication History

Abstract

Dark patterns are malicious UI design strategies that nudge users towards decisions going against their best interests. To create technical countermeasures against them, dark patterns must be automatically detectable. While researchers have devised algorithms to detect some patterns automatically, there has only been little work to use obtained results to technically counter the effects of dark patterns when users face them on their devices.

To address this, we tested three visual countermeasures against 13 common dark patterns in an interactive lab study. The countermeasures we tested either (a) highlighted and explained the manipulation, (b) hid it from the user, or (c) let the user switch between the original view and the hidden version. From our data, we were able to extract multiple clusters of dark patterns where participants preferred specific countermeasures for similar reasons. To support creating effective countermeasures, we discuss our findings with a recent ontology of dark patterns.

Supplemental Material

MP4 File - Video Presentation

Video Presentation

Transcript for: Video Presentation

ZIP File - Prototype Screenshots

Screenshots of the Figma prototypes of the study are in the file "Dark Patterns in Scenarios". All countermeasures and their changes to both scenarios are in the file "Dark Pattern Countermeasures".

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Cited By

Löbel ASchäfer RPüschel HGüney EMeyer U(2024)Access Your Data... if You Can: An Analysis of Dark Patterns Against the Right of Access on Popular WebsitesPrivacy Technologies and Policy10.1007/978-3-031-68024-3_2(23-47)Online publication date: 4-Sep-2024
https://dl.acm.org/doi/10.1007/978-3-031-68024-3_2

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cover image ACM Conferences

CHI '24: Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems

May 2024

18961 pages

ISBN:9798400703300

DOI:10.1145/3613904

Editors:
Florian Floyd Mueller
Monash University
,
Penny Kyburz
The Australian National University
,
Julie R. Williamson
University of Glasgow
,
Corina Sas
Lancaster University
,
Max L. Wilson
University of Nottingham
,
Phoebe Toups Dugas
Monash University/New Mexico State University
,
Irina Shklovski
University of Copenhagen

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Published: 11 May 2024

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Cited By

Löbel ASchäfer RPüschel HGüney EMeyer U(2024)Access Your Data... if You Can: An Analysis of Dark Patterns Against the Right of Access on Popular WebsitesPrivacy Technologies and Policy10.1007/978-3-031-68024-3_2(23-47)Online publication date: 4-Sep-2024
https://dl.acm.org/doi/10.1007/978-3-031-68024-3_2

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