The impact of the use of artificial intelligence in dark pattern strategies on consumer behaviour.

作者
Danilavičienė, Vytautė,
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摘要

Artificial intelligence technologies are increasingly used in marketing to personalize content, predict consumer behavior and increase user engagement. Despite the positive aspects of this technology, AI is also being increasingly used to implement manipulative strategies particularly using dark patterns, which influence user decisions based on their behavioral data. While such dark patterns have long been used in user interface design, AI transforms the way they work, with algorithms that allow real-time analysis of user data and automated adaptation of the design solution to influence user decisions. AI-driven dark patterns are no longer static but dynamic and personalized, making them harder for users to detect. Despite a comprehensive theoretical classification of dark patterns, there is still a lack of empirical studies investigating the impact of these strategies on consumer behavior in real interactions. The application of AI to dark patterns strategies opens up a new direction of research, where it is important to analyze not only how AI transforms them, but also what impact it has on consumer behavior. The object of the research – the interaction of AI-driven dark pattern strategies and consumer behavior. The aim of the research – to explore theoretically and empirically how AI-driven dark pattern strategies influence consumer behavior. Research findings. The empirical part of the study is based on qualitative research methods and semi-structured interviews with 12 active users of online platforms. The research findings revealed that the impact of dark pattern strategies on user behavior is multifaceted and depends on interface design, individual user characteristics and their level of awareness. Fake scarcity dark patterns had the strongest impact stimulating decision-making, perception of scarcity as false and emotional responses. Fake urgency dark patterns stimulated impulsive behavior. Meanwhile, social proof dark patterns were evaluated more critically – users recognized and evaluated them negatively. The results of research indicate that AI-driven dark pattern strategies can have short and long-term effects – users who recognized these strategies experienced not only immediate emotional responses but also a longlasting decrease in trust, behavioral adjustments and abandonment of platforms. Based on the results of the research, practical recommendations are made for both consumers to increase their awareness and resilience and for businesses to create an ethical digital environment.

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