Artificial Intelligence and Your Life: The Problems We Must Face
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Published
Apr 30, 2025
Abstract
Artificial intelligence (AI) is transforming human life at an unprecedented pace. From revolutionizing industries and improving health outcomes to shaping how we interact with the world and each other, AI technologies are deeply embedded in modern life. While these systems bring powerful benefits, they also pose serious problems that demand urgent attention. This essay explores key issues related to algorithmic bias, loss of privacy, job displacement, psychological impacts, social inequality, environmental concerns, and inadequate governance. It highlights that as AI continues to evolve, societies must establish ethical frameworks, regulatory policies, and inclusive design processes to ensure AI technologies serve the collective good. Failing to face these problems now may result in long-term consequences that compromise human dignity, autonomy, and societal cohesion.
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Keywords
Artificial Intelligence, Underlying Mechanisms, Human Life, Deep Thinking, Social Autonomy
Supporting Agencies
No funding source declared.
References
Allen, A., Mataraso, S., Siefkas, A., Burdick, H., Braden, G., Dellinger, R. P., McCoy, A., Pellegrini, E., Hoffman, J., Green-Saxena, A., Barnes, G., Calvert, J., & Das, R. (2020). A racially unbiased, machine learning Approach to Prediction of Mortality: Algorithm Development study. JMIR Public Health and Surveillance, 6(4), e22400. https://doi.org/10.2196/22400
Arnold, D., Dobbie, W., & Hull, P. (2021). Measuring racial discrimination in algorithms. AEA Papers and Proceedings, 111, 49–54. https://doi.org/10.1257/pandp.20211080
Baskara, F. R. (2024). Conceptualizing Digital Literacy for the AI Era: A framework for Preparing students in an AI-Driven world. Data & Metadata, 4, 530. https://doi.org/10.56294/dm2025530
Capraro, V., Lentsch, A., Acemoglu, D., Akgun, S., Akhmedova, A., Bilancini, E., Bonnefon, J., Brañas-Garza, P., Butera, L., Douglas, K. M., Everett, J. a. C., Gigerenzer, G., Greenhow, C., Hashimoto, D. A., Holt-Lunstad, J., Jetten, J., Johnson, S., Kunz, W. H., Longoni, C., . . . Viale, R. (2024). The impact of generative artificial intelligence on socioeconomic inequalities and policy making. PNAS Nexus, 3(6). https://doi.org/10.1093/pnasnexus/pgae191
Chen, S. (2025). How much energy will AI really consume? The good, the bad and the unknown. Nature, 639(8053), 22–24. https://doi.org/10.1038/d41586-025-00616-z
Dhirani, L. L., Mukhtiar, N., Chowdhry, B. S., & Newe, T. (2023). Ethical Dilemmas and Privacy Issues in Emerging Technologies: A review. Sensors, 23(3), 1151. https://doi.org/10.3390/s23031151
Glauberman, G., Ito-Fujita, A., Katz, S., & Callahan, J. (2023). Artificial intelligence in nursing Education: Opportunities and challenges. Hawai’i Journal of Health & Social Welfare, 82(12), 302–305. https://pmc.ncbi.nlm.nih.gov/articles/PMC10713739/
Guidotti, R., Monreale, A., & Pedreschi, D. (2025, April 15). DBLP: ERCIM News, 2019. Dblp Computer Science Bibliography. https://dblp.uni-trier.de/db/journals/ercim/ercim2019.html#GuidottiMP19
Gupta, A., Puri, M., Keshan, M., & Tiwari, V. (2025). AI in Financial Decision-Making: Revolutionizing investment strategies and risk management. In Global Forum for Financial Consumers (GFFC) 2024. https://doi.org/10.2139/ssrn.5085764
Jarvis, T., Thornburg, D., Rebecca, A. M., & Teven, C. M. (2020). Artificial intelligence in plastic surgery: current applications, future directions, and ethical implications. Plastic & Reconstructive Surgery Global Open, 8(10), e3200. https://doi.org/10.1097/gox.0000000000003200
Kanchan, S., & Gaidhane, A. (2023). Social media role and its Impact on Public Health: A Narrative review. Cureus. https://doi.org/10.7759/cureus.33737
Kassem, H., Beevi, A., Basheer, S., Lutfi, G., Ismail, L. C., & Papandreou, D. (2025). Investigation and Assessment of AI’s Role in Nutrition—An Updated Narrative Review of the evidence. Nutrients, 17(1), 190. https://doi.org/10.3390/nu17010190
Liang, F., Das, V., Kostyuk, N., & Hussain, M. M. (2018). Constructing a Data‐Driven Society: China’s social credit system as a state surveillance infrastructure. Policy & Internet, 10(4), 415–453. https://doi.org/10.1002/poi3.183
Marriott, H. R., & Pitardi, V. (2023). One is the loneliest number. . . Two can be as bad as one. The influence of AI Friendship Apps on users’ well‐being and addiction. Psychology and Marketing, 41(1), 86–101. https://doi.org/10.1002/mar.21899
Morley, J., Elhalal, A., Garcia, F., Kinsey, L., Mökander, J., & Floridi, L. (2021). Ethics as a service: A pragmatic operationalisation of AI ethics. Minds and Machines, 31(2), 239–256. https://doi.org/10.1007/s11023-021-09563-w
Panch, T., Mattie, H., & Atun, R. (2019). Artificial intelligence and algorithmic bias: implications for health systems. Journal of Global Health, 9(2). https://doi.org/10.7189/jogh.09.0203 18
Pariser, E. (2012). The filter bubble: how the new personalized Web is changing what we read and how we think. Choice Reviews Online, 50(02), 50–0926. https://doi.org/10.5860/choice.50-0926
Patil, D. (2025). Artificial Intelligence In Financial Risk Assessment And Fraud Detection: Opportunities And Ethical Concerns. SSRN. https://doi.org/10.2139/ssrn.5057434
Percy, C., Dragicevic, S., Sarkar, S., & Garcez, A. D. (2022). Accountability in AI: From principles to industry-specific accreditation. AI Communications, 34(3), 181–196. https://doi.org/10.3233/aic-210080
Roshanaei, M., Olivares, H., & Lopez, R. R. (2023). Harnessing AI to Foster equity in Education: Opportunities, challenges, and emerging strategies. Journal of Intelligent Learning Systems and Applications, 15(04), 123–143. https://doi.org/10.4236/jilsa.2023.154009
Rubeis, G. (2023). Liquid Health. Medicine in the age of surveillance capitalism. Social Science & Medicine, 322, 115810. https://doi.org/10.1016/j.socscimed.2023.115810
Schmitt, M., & Koutroumpis, P. (2025). Cyber Shadows: Neutralizing Security Threats with AI and Targeted Policy Measures. IEEE Transactions on Artificial Intelligence, 1–9. https://doi.org/10.1109/tai.2025.3527398
Schuster, N., & Lazar, S. (2024). Attention, moral skill, and algorithmic recommendation. Philosophical Studies. https://doi.org/10.1007/s11098-023-02083-6
Shen, Y., & Zhang, X. (2024). The impact of artificial intelligence on employment: the role of virtual agglomeration. Humanities and Social Sciences Communications, 11(1). https://doi.org/10.1057/s41599-024-02647-9
Uddin, A. S. M. A. (2023). The era of AI: Upholding ethical leadership. Open Journal of Leadership, 12(04), 400–417. https://doi.org/10.4236/ojl.2023.1240 19
Van Noorden, R. (2020). The ethical questions that haunt facial-recognition research. Nature, 587(7834), 354–358. https://doi.org/10.1038/d41586-020-03187-3
Walsh, T. (2022). Will AI end privacy? How do we avoid an Orwellian future. AI & Society, 38(3), 1239–1240. https://doi.org/10.1007/s00146-022-01433-y
Wang, J., Zeng, Z., Li, Z., Liu, G., Zhang, S., Luo, C., Hu, S., Wan, S., & Zhao, L. (2025). The clinical application of artificial intelligence in cancer precision treatment. Journal of Translational Medicine, 23(1). https://doi.org/10.1186/s12967-025-06139-5
Zeng, J. (2020). Artificial intelligence and China’s authoritarian governance. International Affairs, 96(6), 1441–1459. https://doi.org/10.1093/ia/iiaa172
Arnold, D., Dobbie, W., & Hull, P. (2021). Measuring racial discrimination in algorithms. AEA Papers and Proceedings, 111, 49–54. https://doi.org/10.1257/pandp.20211080
Baskara, F. R. (2024). Conceptualizing Digital Literacy for the AI Era: A framework for Preparing students in an AI-Driven world. Data & Metadata, 4, 530. https://doi.org/10.56294/dm2025530
Capraro, V., Lentsch, A., Acemoglu, D., Akgun, S., Akhmedova, A., Bilancini, E., Bonnefon, J., Brañas-Garza, P., Butera, L., Douglas, K. M., Everett, J. a. C., Gigerenzer, G., Greenhow, C., Hashimoto, D. A., Holt-Lunstad, J., Jetten, J., Johnson, S., Kunz, W. H., Longoni, C., . . . Viale, R. (2024). The impact of generative artificial intelligence on socioeconomic inequalities and policy making. PNAS Nexus, 3(6). https://doi.org/10.1093/pnasnexus/pgae191
Chen, S. (2025). How much energy will AI really consume? The good, the bad and the unknown. Nature, 639(8053), 22–24. https://doi.org/10.1038/d41586-025-00616-z
Dhirani, L. L., Mukhtiar, N., Chowdhry, B. S., & Newe, T. (2023). Ethical Dilemmas and Privacy Issues in Emerging Technologies: A review. Sensors, 23(3), 1151. https://doi.org/10.3390/s23031151
Glauberman, G., Ito-Fujita, A., Katz, S., & Callahan, J. (2023). Artificial intelligence in nursing Education: Opportunities and challenges. Hawai’i Journal of Health & Social Welfare, 82(12), 302–305. https://pmc.ncbi.nlm.nih.gov/articles/PMC10713739/
Guidotti, R., Monreale, A., & Pedreschi, D. (2025, April 15). DBLP: ERCIM News, 2019. Dblp Computer Science Bibliography. https://dblp.uni-trier.de/db/journals/ercim/ercim2019.html#GuidottiMP19
Gupta, A., Puri, M., Keshan, M., & Tiwari, V. (2025). AI in Financial Decision-Making: Revolutionizing investment strategies and risk management. In Global Forum for Financial Consumers (GFFC) 2024. https://doi.org/10.2139/ssrn.5085764
Jarvis, T., Thornburg, D., Rebecca, A. M., & Teven, C. M. (2020). Artificial intelligence in plastic surgery: current applications, future directions, and ethical implications. Plastic & Reconstructive Surgery Global Open, 8(10), e3200. https://doi.org/10.1097/gox.0000000000003200
Kanchan, S., & Gaidhane, A. (2023). Social media role and its Impact on Public Health: A Narrative review. Cureus. https://doi.org/10.7759/cureus.33737
Kassem, H., Beevi, A., Basheer, S., Lutfi, G., Ismail, L. C., & Papandreou, D. (2025). Investigation and Assessment of AI’s Role in Nutrition—An Updated Narrative Review of the evidence. Nutrients, 17(1), 190. https://doi.org/10.3390/nu17010190
Liang, F., Das, V., Kostyuk, N., & Hussain, M. M. (2018). Constructing a Data‐Driven Society: China’s social credit system as a state surveillance infrastructure. Policy & Internet, 10(4), 415–453. https://doi.org/10.1002/poi3.183
Marriott, H. R., & Pitardi, V. (2023). One is the loneliest number. . . Two can be as bad as one. The influence of AI Friendship Apps on users’ well‐being and addiction. Psychology and Marketing, 41(1), 86–101. https://doi.org/10.1002/mar.21899
Morley, J., Elhalal, A., Garcia, F., Kinsey, L., Mökander, J., & Floridi, L. (2021). Ethics as a service: A pragmatic operationalisation of AI ethics. Minds and Machines, 31(2), 239–256. https://doi.org/10.1007/s11023-021-09563-w
Panch, T., Mattie, H., & Atun, R. (2019). Artificial intelligence and algorithmic bias: implications for health systems. Journal of Global Health, 9(2). https://doi.org/10.7189/jogh.09.0203 18
Pariser, E. (2012). The filter bubble: how the new personalized Web is changing what we read and how we think. Choice Reviews Online, 50(02), 50–0926. https://doi.org/10.5860/choice.50-0926
Patil, D. (2025). Artificial Intelligence In Financial Risk Assessment And Fraud Detection: Opportunities And Ethical Concerns. SSRN. https://doi.org/10.2139/ssrn.5057434
Percy, C., Dragicevic, S., Sarkar, S., & Garcez, A. D. (2022). Accountability in AI: From principles to industry-specific accreditation. AI Communications, 34(3), 181–196. https://doi.org/10.3233/aic-210080
Roshanaei, M., Olivares, H., & Lopez, R. R. (2023). Harnessing AI to Foster equity in Education: Opportunities, challenges, and emerging strategies. Journal of Intelligent Learning Systems and Applications, 15(04), 123–143. https://doi.org/10.4236/jilsa.2023.154009
Rubeis, G. (2023). Liquid Health. Medicine in the age of surveillance capitalism. Social Science & Medicine, 322, 115810. https://doi.org/10.1016/j.socscimed.2023.115810
Schmitt, M., & Koutroumpis, P. (2025). Cyber Shadows: Neutralizing Security Threats with AI and Targeted Policy Measures. IEEE Transactions on Artificial Intelligence, 1–9. https://doi.org/10.1109/tai.2025.3527398
Schuster, N., & Lazar, S. (2024). Attention, moral skill, and algorithmic recommendation. Philosophical Studies. https://doi.org/10.1007/s11098-023-02083-6
Shen, Y., & Zhang, X. (2024). The impact of artificial intelligence on employment: the role of virtual agglomeration. Humanities and Social Sciences Communications, 11(1). https://doi.org/10.1057/s41599-024-02647-9
Uddin, A. S. M. A. (2023). The era of AI: Upholding ethical leadership. Open Journal of Leadership, 12(04), 400–417. https://doi.org/10.4236/ojl.2023.1240 19
Van Noorden, R. (2020). The ethical questions that haunt facial-recognition research. Nature, 587(7834), 354–358. https://doi.org/10.1038/d41586-020-03187-3
Walsh, T. (2022). Will AI end privacy? How do we avoid an Orwellian future. AI & Society, 38(3), 1239–1240. https://doi.org/10.1007/s00146-022-01433-y
Wang, J., Zeng, Z., Li, Z., Liu, G., Zhang, S., Luo, C., Hu, S., Wan, S., & Zhao, L. (2025). The clinical application of artificial intelligence in cancer precision treatment. Journal of Translational Medicine, 23(1). https://doi.org/10.1186/s12967-025-06139-5
Zeng, J. (2020). Artificial intelligence and China’s authoritarian governance. International Affairs, 96(6), 1441–1459. https://doi.org/10.1093/ia/iiaa172
How to Cite
Ko, G. E. (2025). Artificial Intelligence and Your Life: The Problems We Must Face. Science Insights, 46(4), 1799–1803. https://doi.org/10.15354/si.25.pe211
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