Analysis of Dark AI Patterns Manipulation Vulnerability Levels in the E-Commerce Environment
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- Tytuł: Analysis of Dark AI Patterns Manipulation Vulnerability Levels in the E-Commerce Environment
- Autor/Autorzy:
- Nazwa czasopisma: European Research Studies Journal
- Rok: 2026
- Tom: XXIX
- Numer: 1
- ISSN: 1108-2976
- DOI: 10.35808/ersj/4317
- Adres www:: https://ersj.eu/journal/4317
- Strony od-do: 378-390
- Abstrakt: 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.
- Dyscyplina: nauki o polityce i administracji
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- 002 a Analysis of Dark AI Patterns Manipulation Vulnerability Levels in the E-Commerce Environment
- 003 b 0000-0002-9201-9889
- 003 a AGNIESZKA KNAP-STEFANIUK (Autor)
- 003 a Aneta Montano (Autor)
- 003 a Damian Kocot (Autor)
- 003 a Izabela Gontarek (Autor)
- 003 a Magdalena Maciaszczyk (Autor)
- 003 a Marta Pietrzykowska (Autor)
- 003 a Monika Bednarczyk (Autor)
- 004 a Oryginalny artykuł naukowy
- 006 a European Research Studies Journal
- 008 a 2026
- 009 a XXIX
- 010 a 1
- 011 a 1108-2976
- 013 a 10.35808/ersj/4317
- 014 a https://ersj.eu/journal/4317
- 015 a 378-390
- 020 a 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.
- 022 a artificial intelligence
- 022 a Dark AI
- 022 a e-commerce
- 022 a manipulation vulnerabilities
- 022 a trade
- 966 a nauki o polityce i administracji
- 985 a Wydział Pedagogiczny
- 985 b Instytut Nauk o Polityce i Administracji
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- Tytuł: Analysis of Dark AI Patterns Manipulation Vulnerability Levels in the E-Commerce Environment
- Autor (Twórca):
- Tytuł czasopisma : European Research Studies Journal
- Data: 2026
- Dyscyplina: nauki o polityce i administracji
- Słowa kluczowe w j. angielskim:
- Struktura: