• AI-driven UI design now adapts and personalizes, but also amplifies dark pattern risks. • Dark patterns exploit psychological biases, learned from existing deceptive data, becoming more subtle. • The paper introduces DarkPatternDetector, combining UI heuristics, NLP, and behavioral signals. • Detector achieves high precision and recall on curated dataset of dark vs benign webpages. • Alignment with India’s Digital Personal Data Protection Act 2023 offers regulatory framework. • Findings aim to support ethical AI design, enforcement, and transparency in digital interfaces. • Technical mechanisms include temporal behavior analysis to spot evolving manipulations. • The study highlights need for cross-disciplinary oversight in AI interface development.
Article Summaries:
- Researchers report that AI‑driven user interfaces are increasingly reproducing “dark patterns” - subtle, manipulative design tactics that steer users toward actions benefiting businesses or advertisers. The study analyzes how AI systems, trained on data containing deceptive practices, can learn and refine these tactics, making them more personalized and harder to spot. To counter this, the authors present DarkPatternDetector, an automated tool that scans websites using UI heuristics, natural‑language processing, and behavioral signals, achieving high precision and recall on a curated dataset. The paper also aligns detection outputs with India’s Digital Personal Data Protection Act, 2023, proposing a regulatory framework to aid enforcement and promote ethical AI design.
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