AI-Generated Short Videos and Their Potential Effects on Users: A Buddhist Self-Awareness Approach to Mindful Media Consumption
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Abstract
This academic article adopts a conceptual approach informed by a narrative review of literature on AI-generated short videos, digital-media consumption, user cognition and emotion, and Buddhist mindfulness. The article thematically examines academic studies and selected primary Buddhist sources to develop a framework for mindful and responsible media consumption. The article addresses three interconnected themes: (1) the emergence of AI-generated short videos on social-media platforms, (2) their potential effects on users, and (3) Buddhist self-awareness as an approach to learning and responsible digital-media consumption.
The reviewed literature indicates a transition from predominantly human-produced short-form videos toward increasing use of AI-assisted and AI-generated content. Generative AI can support scriptwriting, image and voice generation, editing, and other stages of content production, while platform recommendation systems separately rank and personalize the content presented to users. Research on short-form video use raises concerns regarding attention, cognitive fatigue, credibility judgments, and habitual scrolling; however, the available evidence does not establish that AI-generated short videos alone directly cause these outcomes. From a Buddhist perspective, sīla (ethical discipline), sammā-vācā (right speech), sati (mindfulness), and sampajañña (clear comprehension) provide complementary principles for more reflective digital engagement. These principles encourage users to notice what they are doing, examine the purpose and possible consequences of continued viewing or sharing, and make a deliberate ethical choice. The proposed framework therefore treats Buddhist self-awareness not as a rejection of digital media but as a way of engaging with emerging forms of content without surrendering reflective judgment.
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References
Alruwaili, R. F. (2025). Scroll immersion and short-form video use: Predictors of attention, memory, and fatigue among Saudi social media users. Acta Psychologica, 260, 105674. https://doi.org/10.1016/j.actpsy.2025.105674
Bodhi Bhikkhu. (Ed.). (2005). In the Buddha’s words: An anthology of discourses from the Pāli Canon. Wisdom Publications.
Buddharakkhita, A. (Trans.). (1985). The Dhammapada: The Buddha’s path of wisdom. Buddhist Publication Society.
Candogan, O., & Drakopoulos, K. (2020). Optimal signaling of content accuracy: Engagement vs. misinformation. Operations Research, 68(2), 497-515. https://doi.org/10.1287/opre.2019.1897
Chen, H., Wang, P., & Hao, S. (2025). AI in the spotlight: The impact of artificial intelligence disclosure on user engagement in short-form videos. Computers in Human Behavior, 162, 108448. https://doi.org/10.1016/j.chb.2024.108448
Chen, Y., Wang, H., Rao Hill, S., & Li, B. (2024). Consumer attitudes toward AI-generated ads: Appeal types, self-efficacy and AI’s social role. Journal of Business Research, 185, 114867. https://doi.org/10.1016/j.jbusres.2024.114867
Kitchen, P. J., Kerr, G., Schultz, D. E., & Pals, H. (2014). The elaboration likelihood model: Review, critique and research agenda. European Journal of Marketing, 48(11/12), 2033-2050. https://doi.org/10.1108/EJM-12-2011-0776
Lim, S., & Schmälzle, R. (2024). The effect of source disclosure on evaluation of AI-generated messages. Computers in Human Behavior: Artificial Humans, 2(1), 100058. https://doi.org/10.1016/j.chbah.2024.100058
Liu, X., Yang, B., Cheng, H., & Sun, Y. (2023). Investigating the impact of AIGC features on the users’ perception of the persuasiveness of AIGC: A perspective of two-dimensional awe emotions. Proceedings of the International Conference on Electronic Business, 23, 409-418.
Ñāṇamoli Bhikkhu, & Bodhi Bhikkhu. (Trans.). (1995). The middle length discourses of the Buddha: A new translation of the Majjhima Nikāya. Wisdom Publications.
Sundar, S. S. (2008). The MAIN model: A heuristic approach to understanding technology effects on credibility. In M. J. Metzger & A. J. Flanagin (Eds.), Digital media, youth, and credibility (pp. 72-100). MIT Press.
Sundar, S. S., Jia, H., Waddell, T. F., & Huang, Y. (2015). Toward a theory of interactive media effects (TIME): Four models for explaining how interface features affect user psychology. In S. S. Sundar (Ed.), The handbook of the psychology of communication technology (pp. 47-86). Wiley. https://doi.org/10.1002/9781118426456.ch3
Walshe, M. (Trans.). (1995). The long discourses of the Buddha: A translation of the Dīgha Nikāya. Wisdom Publications.
Wang, Y., Pan, Y., Yan, M., Su, Z., & Luan, T. H. (2023). A survey on ChatGPT: AI-generated contents, challenges, and solutions. IEEE Open Journal of the Computer Society, 4, 280-302. https://doi.org/10.1109/OJCS.2023.3300321
Williamson, D. A., & Koch, J. (2024, December 9). The AI ad gap: Why young consumers aren’t yet buying into Gen AI ads. IAB Insights Engine. https://www.iab.com/insights/why-young-consumers-avoid-gen-ai-ads/
Yan, T., Su, C., Xue, W., Hu, Y., & Zhou, H. (2024). Mobile phone short video use negatively impacts attention functions: An EEG study. Frontiers in Human Neuroscience, 18, 1383913. https://doi.org/10.3389/fnhum.2024.1383913
Yan, X. (2026). The effectiveness of AI-generated short-video advertising on social media. Journal of Innovation and Development, 14(3), 147-151. https://doi.org/10.54097/95nzxr11
