Internet users are constantly subjected to incessant demands for attention in a noisy digital world. Countless inputs compete for the chance to be clicked, to be seen, and to be interacted with, and they can deploy tactics that take advantage of behavioral psychology to 'nudge' users into doing what they want. Some nudges are benign; others deceive, steer, or manipulate users, as the U.S. FTC Commissioner says, "into behavior that is profitable for an online service, but often harmful to [us] or contrary to [our] intent". These tactics are dark patterns, which are manipulative and deceptive interface designs used at-scale in more than ten percent of global shopping websites and more than ninety-five percent of the most popular apps in online services. Literature discusses several types of harms caused by dark patterns that includes harms of a material nature, such as financial harms, or anticompetitive issues, as well as harms of a non-material nature, such as privacy invasion, time loss, addiction, cognitive burdens, loss of autonomy, and emotional or psychological distress. Through a comprehensive literature review of this scholarship and case law analysis conducted by our interdisciplinary team of HCI and legal scholars, this paper investigates whether harms caused by such dark patterns could give rise to redress for individuals subject to dark pattern practices using consent interactions and the GDPR consent requirements as a case study.
|Title of host publication||Proceedings of the 2022 Symposium on Computer Science and Law Association for Computing Machinery (ACM)|
|Place of Publication||Washington, US|
|Publisher||The ACM Digital Library|
|Number of pages||14|
|Publication status||Published - 1 Nov 2022|
|Event||Symposium on Computer Science and Law Association for Computing Machinery (ACM) - , United States|
Duration: 1 Nov 2022 → …
|Name||CSLAW 2022 - Proceedings of the 2022 Symposium on Computer Science and Law|
|Conference||Symposium on Computer Science and Law Association for Computing Machinery (ACM)|
|Period||1/11/22 → …|
Bibliographical noteFunding Information:
The research for this paper is partially funded by the Horizon Europe ENCRYPT project (Grant Agreement nr. 1010706), RENFORCE, Google ASPIRE award, and an NSF SaTC Frontiers grant (#1955227).
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- dark patterns
- data protection
- manipulative design