Earticle

초록

영어

Generative AI is increasingly shaping human experiences across creative, social, and professional domains. While its digital capabilities offer new opportunities for enhancing user engagement, personalization, and productivity, its dual impact on users’ psychological needs remains underexplored. Grounded in self-determination theory, this study investigates how generative AI both satisfies and frustrates users’ psychological needs and examines the broader implications of this dynamic. Employing a netnographic methodology, the research draws on over 1.5-year of naturalistic online AI Community observation, resulting in a rich dataset comprising 2,062 pages of data. This research uncovers paradoxical relationships between generative AI features and users’ needs – autonomy, competence, and relatedness – highlighting the simultaneous fulfillment and frustration they can provoke. These findings offer critical insights for the user-centered design of generative AI systems, and have implications for developers, business professionals, and policymakers aiming to balance innovation with psychological well-being.

목차

ABSTRACT
Ⅰ. Introduction
Ⅱ. Literature Background
2.1. An Overview of Generative AI Research
2.2. Self-determination Theory and Generative AI
Ⅲ. Research Method
3.1. Data Collection
3.2. Data Analysis
Ⅳ. Findings
4.1. Common Features of Generative AI
4.2. Prompting Mechanism
4.3. Augmenting Mechanism
4.4. Interacting Mechanism
4.5. The Interconnectedness of Three Mechanisms
Ⅴ. Discussion and Implications
5.1. Theoretical Implications
5.2. Implications for Practice
Ⅵ. Conclusion

저자

• Ha Eun Park [ Assistant Professor, Department of Big Data Analytics, School of Management, Kyung Hee University, Korea ] Corresponding Author

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