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| Format: | Preprint |
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2023
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| Online Access: | https://arxiv.org/abs/2310.00340 |
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| _version_ | 1866911822400978944 |
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| author | Brenncke, Martin |
| author_facet | Brenncke, Martin |
| contents | Dark patterns have become increasingly pervasive in online choice architectures, encompassing practices like subscription traps, hiding information about fees, pre-selecting options by default, nagging, and drip pricing. Regulators around the world have started to express concerns that such practices are causing substantial consumer detriment. This Article focuses on the legal response to dark patterns in the European Union. It provides the first comprehensive mapping of European Union laws expressly addressing dark patterns. The Article argues that these laws protect biased consumers and adopt autonomy as a normative lens to assess dark patterns. Consequently, regulating dark patterns in European Union law means regulating for autonomy. This normative lens is under-researched.
This Article addresses this gap in research with two principle contributions. First, it works out a specific conception of autonomous decision-making, rooted in the paradigm that providing consumers with information enables consumers to make an informed decision. Second, the Article offers a novel normative classification for dark patterns in online choice architectures. It develops a taxonomy encompassing six categories of autonomy violations, specifically tailored for the assessment and regulation of dark patterns that exploit consumer behavioral biases. These categories serve multiple purposes. They uncover and make explicit the autonomy violations addressed by existing European Union laws. They delineate the contentious line between acceptable influences on consumer decision-making and autonomy violations that may warrant regulation in online choice architectures. They also provide policymakers in the EU and elsewhere with a framework when deliberating the regulation of other instances of dark patterns. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2310_00340 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Regulating Dark Patterns Brenncke, Martin Human-Computer Interaction Dark patterns have become increasingly pervasive in online choice architectures, encompassing practices like subscription traps, hiding information about fees, pre-selecting options by default, nagging, and drip pricing. Regulators around the world have started to express concerns that such practices are causing substantial consumer detriment. This Article focuses on the legal response to dark patterns in the European Union. It provides the first comprehensive mapping of European Union laws expressly addressing dark patterns. The Article argues that these laws protect biased consumers and adopt autonomy as a normative lens to assess dark patterns. Consequently, regulating dark patterns in European Union law means regulating for autonomy. This normative lens is under-researched. This Article addresses this gap in research with two principle contributions. First, it works out a specific conception of autonomous decision-making, rooted in the paradigm that providing consumers with information enables consumers to make an informed decision. Second, the Article offers a novel normative classification for dark patterns in online choice architectures. It develops a taxonomy encompassing six categories of autonomy violations, specifically tailored for the assessment and regulation of dark patterns that exploit consumer behavioral biases. These categories serve multiple purposes. They uncover and make explicit the autonomy violations addressed by existing European Union laws. They delineate the contentious line between acceptable influences on consumer decision-making and autonomy violations that may warrant regulation in online choice architectures. They also provide policymakers in the EU and elsewhere with a framework when deliberating the regulation of other instances of dark patterns. |
| title | Regulating Dark Patterns |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2310.00340 |