Digital Addictions and Artificial Intelligence: Between the Algorithm and Well-Being

Main Article Content

Shilia Lisset Vargas Echeverría

Abstract

Digital technology has transformed our lives, but it has also introduced new challenges, such as the compulsive use of devices and digital platforms. Digital addiction, particularly in the context of social media, video games, and content consumption, has become a growing phenomenon with significant implications for mental and social health. In this context, AI emerges as a key player with a dual role: on one hand, it contributes to the development of these addictions through recommendation algorithms that maximize screen time; on the other, it offers innovative solutions for prevention and treatment through tools like therapeutic chatbots and early detection systems.

Keywords:
Digital addiction ,  Artificial intelligence ,  TTechnological prevention
Published: Jun 27, 2025

Article Details

How to Cite
Vargas Echeverría, S. L. (2025). Digital Addictions and Artificial Intelligence: Between the Algorithm and Well-Being. Revista Internacional De Investigación En Adicciones, 11(1), 89–90. https://doi.org/10.28931/riiad.2025.381
Section
Experts Opinions

References

American Psychiatric Association [APA]. (2023). Addiction to technology, social media, and gaming. American Psychiatric Association. Recuperado de https://www.psychiatry.org/patients-families/la-salud-mental/adiccion-a-la-tecnologia-redes-sociales-juegos-en

Anderson, J., & Rainie, L. (2018). The future of well-being in a tech-saturated world. Pew Research Center.

Brown, L. (17 de febrero de 2025). Technology addicts suffer same withdrawal symptoms as heroin addicts, therapist finds. New York Post. Recuperado de https://nypost.com/2025/02/17/technology-addicts-suffer-same-withdrawal-symptoms-as-heroin-addicts-therapist-finds

Hilty, D. M., Torous, J., Parish, M. B., Chan, S., & Yellowlees, P. M. (2020). A review of mobile health (mHealth) and apps for addressing mental health challenges during COVID-19. Journal of Technology in Behavioral Science, 5(4), 1-16.

Inkster, B., Sarda, S., & Subramanian, V. (2018). An empathy-driven, conversational artificial intelligence agent (Wysa) for digital mental well-being: Real-world data evaluation. JMIR mHealth and uHealth, 6(11), e12106.

King, D. L., & Delfabbro, P. H. (2018). Internet gaming disorder: Theory, assessment, treatment, and prevention. Journal of Behavioral Addictions, 7(1), 1-6.

Mallick, D., Chakraborty, P., & Ghosh, S. (2023). Visual representation for patterned proliferation of social media addiction: Quantitative model and network analysis. arXiv.org. https://arxiv.org/abs/2307.09902

Mental Health Europe. (2025). Mental Health Europe launches a study on artificial intelligence in mental healthcare. Recuperado de https://www.mentalhealtheurope.org/mental-health-europe-launches-a-study-on-artificial-intelligence-in-mental-healthcare/

Montag, C., Wegmann, E., Sariyska, R., Demetrovics, Z., & Brand, M. (2021). How to overcome taxonomical problems in the study of Internet use disorders and what to do with “smartphone addiction”? Journal of Behavioral Addictions, 10(1), 1-7.

Morley, J., Machado, C. C. V., Burr, C., Cowls, J., Taddeo, M., & Floridi, L. (2020). The ethics of AI in health care: A mapping review. Social Science & Medicine, 260, 113172.

Park, J., & Kim, S. (2022). Review of persuasive user interface as strategy for technology addiction in virtual environments. arXiv.org. https://arxiv.org/abs/2210.09628

Torous, J., Myrick, K., Rauseo-Ricupero, N., & Firth, J. (2021). Digital mental health and COVID-19: Using technology today to accelerate the curve on access and quality tomorrow.JMIR Mental Health, 8(3), e18848.

Xiang, L., Xu, J., & Sun, X. (2021). Do persuasive designs make smartphones more addictive? – A mixed-methods study on Chinese university students. arXiv.org. https://arxiv.org/abs/2106.02604

Young, K. S. (1998). Caught in the Net: How to Recognize the Signs of Internet Addiction—and a Winning Strategy for Recovery. John Wiley & Sons.

Zhou, Y., & Li, H. (2024). Amplification of addictive new media features in the Metaverse. arXiv.org. https://arxiv.org/abs/2401.03461