Investigating How Frequent Interactions with AI Technologies Impact Cognitive and Emotional Processes
DOI:
https://doi.org/10.61506/Keywords:
AI Interaction, Cognitive Functioning, Emotional Well-being, Psychological Dependency, Stress, Memory RetentionAbstract
This research explores the cognitive and emotional effects of frequent interactions with Artificial Intelligence (AI) technologies, utilizing a mixed-method approach. The study involved 300 participants for quantitative analysis and 100 for qualitative insights, focusing on how AI impacts memory retention, decision-making, stress, anxiety, and psychological dependency. Quantitative results demonstrated a significant positive correlation between AI usage frequency and cognitive improvements, such as memory short-term (r = 0.663, p < 0.01) and decision accuracy (r = 0.572, p < 0.01), supporting Hypothesis 1 (H1). However, AI usage was also correlated with increased mental stress (r = 0.468, p < 0.01), aligning with Hypotheses 2 (H2) and 4 (H4). Qualitative analysis revealed themes of emotional strain, cognitive benefits with emotional costs, and psychological dependency on AI, further validating Hypothesis 5 (H5). The study concludes that while AI enhances cognitive functions, it also elevates emotional strain and dependency, highlighting the need for AI systems that balance cognitive improvements with emotional well-being.
References
Adamovich, I., Agarwal, S., Ahedo, E., Alves, L. L., Baalrud, S., Babaeva, N., Bogaerts, A., Bourdon, A., Bruggeman, P., & Canal, C. (2022). The 2022 Plasma Roadmap: low temperature plasma science and technology. Journal of Physics D: Applied Physics, 55(37), 373001.
Agarwal, R., & Reed, T. (2021). How to end the COVID-19 pandemic by March 2022. World Bank Policy Research Working Paper.
Araujo, T. (2018). Living up to the chatbot hype: The influence of anthropomorphic design cues and communicative agency framing on conversational agent and company perceptions. Computers in Human Behavior, 85, 183-189.
Baker, C. J., Smith, S. A., & Morrissey, J. H. (2019). Polyphosphate in thrombosis, hemostasis, and inflammation. Research and Practice in Thrombosis and Haemostasis, 3(1), 18-25.
Cao, Y., Wang, J., Jian, F., Xiao, T., Song, W., Yisimayi, A., Huang, W., Li, Q., Wang, P., & An, R. (2022). Omicron escapes the majority of existing SARS-CoV-2 neutralizing antibodies. Nature, 602(7898), 657-663.
Carr, E. S. (2010). Enactments of expertise. Annual review of anthropology, 39(1), 17-32.
Chalmers, D. (2008). Foreword to Andy Clark’s Supersizing the mind. A. Clark. Supersizing the mind: Embodiment, action, and cognitive extension.
Chaudhary, N., Weissman, D., & Whitehead, K. A. (2021). mRNA vaccines for infectious diseases: principles, delivery and clinical translation. Nature reviews Drug discovery, 20(11), 817-838.
Chen, P., Nirula, A., Heller, B., Gottlieb, R. L., Boscia, J., Morris, J., Huhn, G., Cardona, J., Mocherla, B., & Stosor, V. (2021). SARS-CoV-2 neutralizing antibody LY-CoV555 in outpatients with Covid-19. New England Journal of Medicine, 384(3), 229-237.
d'Alpoim Guedes, J., Gonzalez, S., & Rivera‐Collazo, I. (2021). Resistance and Care in the Time of COVID‐19: Archaeology in 2020. American Anthropologist, 123(4), 898-915.
Guzman, A. L., & Lewis, S. C. (2020). Artificial intelligence and communication: A human–machine communication research agenda. New Media & Society, 22(1), 70-86.
Huang, M.-H., & Rust, R. T. (2021). A strategic framework for artificial intelligence in marketing. Journal of the Academy of Marketing Science, 49, 30-50.
Kellermann, J. (2022). Essays in financial econometrics Dissertation, Bochum, Ruhr-Universität Bochum, 2021].
Krammer, F., Srivastava, K., Alshammary, H., Amoako, A. A., Awawda, M. H., Beach, K. F., Bermúdez-González, M. C., Bielak, D. A., Carreño, J. M., & Chernet, R. L. (2021). Antibody responses in seropositive persons after a single dose of SARS-CoV-2 mRNA vaccine. New England Journal of Medicine, 384(14), 1372-1374.
Langer, N., Schürmann, C., Stoll, K., Marchant, P., Lennon, D., Mahy, L., De Mink, S., Quast, M., Riedel, W., & Sana, H. (2020). Properties of OB star− black hole systems derived from detailed binary evolution models. Astronomy & Astrophysics, 638, A39.
Lee, B. T., Barber, G. P., Benet-Pagès, A., Casper, J., Clawson, H., Diekhans, M., Fischer, C., Gonzalez, J. N., Hinrichs, A. S., & Lee, C. M. (2022). The UCSC genome browser database: 2022 update. Nucleic acids research, 50(D1), D1115-D1122.
Martin, P. P., Lewis, R. K., & Guzmán, B. L. (2023). Racial reckoning, resistance, and the revolution: A call to community psychology to move forward. In (Vol. 71, pp. 3-7): Wiley Online Library.
Müller, A., Österlund, H., Marsalek, J., & Viklander, M. (2020). The pollution conveyed by urban runoff: A review of sources. Science of the Total Environment, 709, 136125.
Nye, J. S. (2021). Soft power: the evolution of a concept. In Essays on Evolutions in the Study of Political Power (pp. 196-208). Routledge.
Pettinato, M. C. (2021). Introduction to antibody-drug conjugates. Antibodies, 10(4), 42.
Pradhan, D., Sukla, L. B., Mishra, B. B., & Devi, N. (2019). Biosorption for removal of hexavalent chromium using microalgae Scenedesmus sp. Journal of Cleaner Production, 209, 617-629.
Shneiderman, B. (2021). Responsible AI: Bridging from ethics to practice. Communications of the ACM, 64(8), 32-35.
Skulmowski, A., & Xu, K. M. (2022). Understanding cognitive load in digital and online learning: A new perspective on extraneous cognitive load. Educational psychology review, 34(1), 171-196.
Topol, E. J. (2019). High-performance medicine: the convergence of human and artificial intelligence. Nature medicine, 25(1), 44-56.
Tsao, C. W., Aday, A. W., Almarzooq, Z. I., Alonso, A., Beaton, A. Z., Bittencourt, M. S., Boehme, A. K., Buxton, A. E., Carson, A. P., & Commodore-Mensah, Y. (2022). Heart disease and stroke statistics—2022 update: a report from the American Heart Association. Circulation, 145(8), e153-e639.
Weiss, J. C., & Dafoe, A. (2019). Authoritarian audiences, rhetoric, and propaganda in international crises: Evidence from China. International Studies Quarterly, 63(4), 963-973.
West, R., Michie, S., Rubin, G. J., & Amlôt, R. (2020). Applying principles of behaviour change to reduce SARS-CoV-2 transmission. Nature human behaviour, 4(5), 451-459.
Wölfel, R., Corman, V. M., Guggemos, W., Seilmaier, M., Zange, S., Müller, M. A., Niemeyer, D., Jones, T. C., Vollmar, P., & Rothe, C. (2020). Virological assessment of hospitalized patients with COVID-2019. Nature, 581(7809), 465-469.
Wu, C., Chen, X., Cai, Y., Zhou, X., Xu, S., Huang, H., Zhang, L., Zhou, X., Du, C., & Zhang, Y. (2020). Risk factors associated with acute respiratory distress syndrome and death in patients with coronavirus disease 2019 pneumonia in Wuhan, China. JAMA internal medicine, 180(7), 934-943.
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education–where are the educators? International Journal of Educational Technology in Higher Education, 16(1), 1-27.
Zhang, B., Anderljung, M., Kahn, L., Dreksler, N., Horowitz, M. C., & Dafoe, A. (2021). Ethics and governance of artificial intelligence: Evidence from a survey of machine learning researchers. Journal of Artificial Intelligence Research, 71, 591–666-591–666.
Zhang, B., Dreksler, N., Anderljung, M., Kahn, L., Giattino, C., Dafoe, A., & Horowitz, M. C. (2022). Forecasting AI progress: Evidence from a survey of machine learning researchers. arXiv preprint arXiv:2206.04132.
