Title
Analysis of Dark AI Patterns Manipulation Vulnerability Levels in the E-Commerce Environment
Authors
[ 1 ] Wydział Ekonomiczny, Akademia im. Jakuba z Paradyża | [ P ] employee
Scientific discipline (Law 2.0)
Year of publication
2026
Published in
Article type
scientific article
Publication language
english
Keywords
EN
- Dark AI
- e-commerce
- manipulation vulnerabilities
- artificial intelligence
- trade
Abstract
EN Purpose: The study aims to examine the levels of consumer susceptibility to Dark AI Patterns in the e-commerce environment and to identify the psychological and behavioral factors that shape this vulnerability. Design/Methodology/Approach: The research was conducted using an online survey carried out in 2025 on a sample of 429 respondents, measuring their responses to algorithmic pressure techniques such as scarcity cues, countdown timers, social proof, and AI-driven recommendations. Findings: The results indicate a moderate and relatively uniform susceptibility to Dark AI Patterns, with higher personalization and trust in AI increasing vulnerability, while greater algorithmic awareness plays a protective role. Practical Implications: The study highlights the need for responsible design of AI-enhanced interfaces, emphasizing transparency, limitation of manipulative cues, and support for users’ informed decision-making. Originality/Value: The article provides one of the first empirical assessments of consumer susceptibility to AI-driven manipulative design, offering insights relevant for researchers, practitioners, and regulators shaping the future of ethical e-commerce.
Date of online publication
2026
Pages (from - to)
378 - 390
License type
CC BY (attribution alone)
Open Access Mode
open journal
Open Access Text Version
final published version
Release date
03.2026
Date of Open Access to the publication
at the time of publication
Ministry points / journal
100
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