Emergent Dark Patterns in AI-Generated User Interfaces
Fuente:
arXiv
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| Formato: | Preprint |
| Publicado: |
2026
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| _version_ | 1866910028730990592 |
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| author | Pandey, Daksh |
| author_facet | Pandey, Daksh |
| contents | The advancement of artificial intelligence has transformed user interface design by enabling adaptive and personalized systems. Alongside these benefits, AI driven interfaces have also enabled the emergence of dark patterns, which are manipulative design strategies that influence user behavior for financial or business gain. As AI systems learn from data that already contains deceptive practices, they can replicate and optimize these patterns in increasingly subtle and personalized ways.
This paper examines AI generated dark patterns, their psychological foundations, technical mechanisms, and regulatory implications in India. We introduce DarkPatternDetector, an automated system that crawls and analyzes websites to detect dark patterns using a combination of UI heuristics, natural language processing, and temporal behavioral signals. The system is evaluated on a curated dataset of dark and benign webpages and achieves strong precision and recall.
By aligning detection results with India's Digital Personal Data Protection Act, 2023, this work provides a technical and regulatory framework for identifying and mitigating deceptive interface practices. The goal is to support ethical AI design, regulatory enforcement, and greater transparency in modern digital systems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_18445 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Emergent Dark Patterns in AI-Generated User Interfaces Pandey, Daksh Human-Computer Interaction The advancement of artificial intelligence has transformed user interface design by enabling adaptive and personalized systems. Alongside these benefits, AI driven interfaces have also enabled the emergence of dark patterns, which are manipulative design strategies that influence user behavior for financial or business gain. As AI systems learn from data that already contains deceptive practices, they can replicate and optimize these patterns in increasingly subtle and personalized ways. This paper examines AI generated dark patterns, their psychological foundations, technical mechanisms, and regulatory implications in India. We introduce DarkPatternDetector, an automated system that crawls and analyzes websites to detect dark patterns using a combination of UI heuristics, natural language processing, and temporal behavioral signals. The system is evaluated on a curated dataset of dark and benign webpages and achieves strong precision and recall. By aligning detection results with India's Digital Personal Data Protection Act, 2023, this work provides a technical and regulatory framework for identifying and mitigating deceptive interface practices. The goal is to support ethical AI design, regulatory enforcement, and greater transparency in modern digital systems. |
| title | Emergent Dark Patterns in AI-Generated User Interfaces |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2602.18445 |