Code-Level Dark Patterns: Exploring Ad Networks' Misleading Code Samples with Negative Consequences for Users

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We introduce code-level dark patterns in ad networks. These are official code samples provided by ad networks that will result in user-facing dark patterns, if copy-pasted by developers. Developers who do not carefully read the code for all the nuanced consequences may endanger users privacy by using these code samples. We present three code samples from Google and Amazon ad networks where the code samples do not provide a "I do not consent" option for location data collection, the consent form keeps reappearing until the user consents, and the inclusion of unnecessary permissions when they are presented as "optional'' in the surrounding text.
Original languageEnglish
Title of host publication"What Can CHI Do About Dark Patterns?" Workshop at CHI Conference on Human Factors in Computing Systems (CHI'21)
Number of pages5
Publication statusPublished - 8 May 2021
Event"What Can CHI Do About Dark Patterns?" Workshop at CHI Conference on Human Factors in Computing Systems 2021 - Virtual workshop
Duration: 8 May 20218 May 2021
https://darkpatternsindesign.com/

Conference

Conference"What Can CHI Do About Dark Patterns?" Workshop at CHI Conference on Human Factors in Computing Systems 2021
Period8/05/218/05/21
Internet address

Keywords

  • software developers
  • usable privacy
  • ad networks

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