Emergent Dark Patterns in AI-Generated User Interfaces

TL;DR

This paper explores the emergence of AI-generated dark patterns in user interfaces, introduces an automated detection system, and discusses regulatory implications to promote ethical AI design and transparency.

Contribution

It presents DarkPatternDetector, an automated tool for detecting dark patterns in websites, and analyzes their psychological, technical, and regulatory aspects in the context of India.

Findings

DarkPatternDetector achieves high precision and recall in detecting dark patterns.

AI-generated dark patterns can be subtle and personalized, complicating detection.

The framework aligns detection with India's Digital Personal Data Protection Act, 2023.

Abstract

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.