A Study on the Ethical Implications and Data Privacy Challenges in the Age of Artificial Intelligence

Year : 2026 | Volume : 16 | Issue : 02 | Page : 01 13
By

Shardul Santosh Kolte,

Saurabh Sanjay Kumar,

Shirshendu Maitra,

  1. Research Scholar, Department MCA, Thakur Institute of Management Studies, Career Development & Research (TIMSCDR) Mumbai, Maharashtra, India
  2. Research Scholar, Department MCA, Thakur Institute of Management Studies, Career Development & Research (TIMSCDR) Mumbai, Maharashtra, India
  3. Assistant Professor, Department MCA, Thakur Institute of Management Studies, Career Development & Research (TIMSCDR) Mumbai, Maharashtra, India

Abstract

The fast adoption of Artificial Intelligence (AI) in areas like education, business, and everyday life comes with both tectonic and important ethical and data privacy issues. This paper examines the principle-practice divide between the ideals of the ethics as they are set and applied in the realities of AI implementation. The study is based on a mixed-methodology design, comprising of a quantitative survey of 52 participants and a qualitative study of four famous case studies, to survey the perceptions of the stakeholders and the sufficiency of existing regulatory frameworks, such as GDPR and the DPDP Act of India. Findings show that the respondents are in unison that AI is an issue of concern ethically, with data privacy being the most notable. A significant difference was determined to exist where the understanding of data protection laws does not generate trust in their effective application (p < 0.01). Although not all the survey data provided testimony to the point, case studies conducted qualitatively allowed establishing that absence of organizational and platform governance is a direct cause of privacy breaches. In addition, the study found that the transparency is an effective predictor of user trust (p < 0.001). The paper concludes that to solve this ethical dilemma, a multi-dimensional solution is necessary in implementing adaptive legal frameworks, strong governance, and clear AI design to make AI deployment responsible and trustworthy.

Keywords: Artificial intelligence (AI), AI ethics, data privacy, algorithmic bias, AI governance, transparency

[This article belongs to Current Trends in Information Technology ]

How to cite this article: Shardul Santosh Kolte, Saurabh Sanjay Kumar, Shirshendu Maitra. A Study on the Ethical Implications and Data Privacy Challenges in the Age of Artificial Intelligence. Current Trends in Information Technology. 2026; 16(02):01-13.
How to cite this URL: Shardul Santosh Kolte, Saurabh Sanjay Kumar, Shirshendu Maitra. A Study on the Ethical Implications and Data Privacy Challenges in the Age of Artificial Intelligence. Current Trends in Information Technology. 2026; 16(02):01-13. Available from: https://journals.stmjournals.com/ctit/article=2026/view=247693

References

  1. Malalla B, Al Mubarak M. Ethical challenges in artificial intelligence technology: business applications. In: Al Mubarak M, editor. Sustainable Digital Technology and Ethics in an Ever-Changing Environment. Vol. 1. Springer Nature; 2025. p. 27-46. doi:10.1007/978-3-031-86712-5_2.
  2. Timan T, Mann Z. Data protection in the era of artificial intelligence: trends, existing solutions and recommendations for privacy-preserving technologies. In: The Elements of Big Data Value: Foundations of the Research and Innovation Ecosystem. Springer International Publishing; 2021. p. 153-75.
  3. Kordzadeh N, Ghasemaghaei M. Algorithmic bias: review, synthesis, and future research directions. Eur J Inf Syst. 2022;31:388-409. doi:10.1080/0960085X.2021.1927212.
  4. Das BC, Amini MH, Wu Y. Security and privacy challenges of large language models: a survey. ACM Comput Surv. 2025;57:1-39. doi:10.1145/3712001.
  5. Chen J, Yan H, Liu Z, Zhang M, Xiong H, Yu S. When federated learning meets privacy-preserving computation. ACM Comput Surv. 2024;56:1-36. doi:10.1145/3679013.
  6. Ganesh P, Tran C, Shokri R, Fioretto F. The data minimization principle in machine learning. In: Proceedings of the 2025 ACM Conference on Fairness, Accountability, and Transparency; 2025. p. 3075-93. doi:10.1145/3715275.3732195.
  7. Kaushik K, Khan A, Kumari A, Sharma I, Dubey R. Ethical considerations in AI-based cybersecurity. In: Kaushik K, Sharma I, editors. Next-Generation Cybersecurity: AI, ML, and Blockchain. Springer Nature; 2024. p. 437-70. doi:10.1007/978-981-97-1249-6_19.
  8. Lastrucci A, Pirrera A, Lepri G, Giansanti D. Algorethics in healthcare: balancing innovation and integrity in AI development. Algorithms. 2024;17:432. doi:10.3390/a17100432.
  9. Huang L. Ethics of artificial intelligence in education: student privacy and data protection. Sci Insights Educ Front. 2023;16:2577-87. doi:10.15354/sief.23.re202.
  10. Kashefi P, Kashefi Y, Ghafouri Mirsaraei A. Shaping the future of AI: balancing innovation and ethics in global regulation. Uniform Law Rev. 2024;29:524-48. doi:10.1093/ulr/unae040.
  11. Tahaei M, Constantinides M, Quercia D, Muller M. A systematic literature review of human-centered, ethical, and responsible AI. arXiv [Preprint]. 2023 Feb 10. arXiv:2302.05284.
  12. Thalpage N. Unlocking the black box: explainable artificial intelligence (XAI) for trust and transparency in AI systems. J Digit Art Humanit. 2023;4:31-6. doi:10.33847/2712-8148.4.1_4.
  13. Spehar GD, Mittal A. Responsible AI horizons: a multi-dimensional framework for verifiable AI behavioral assessment with cryptographic verification. In: International Conference on Artificial Intelligence, Systems, and Emerging Technologies (ICAISET); 2026. Institute of Electrical and Electronics Engineers; p. 1-8. doi:10.1109/ICAISET66439.2026.11541913.
  14. Sayyed H. Artificial intelligence and criminal liability in India: exploring legal implications and challenges. Cogent Soc Sci. 2024;10:2343195. doi:10.1080/23311886.2024.2343195.
  15. Koplin JJ. Dual-use implications of AI text generation. Ethics Inf Technol. 2023;25:32. doi:10.1007/s10676-023-09703-z.
  16. Hagerty A, Rubinov I. Global AI ethics: a review of the social impacts and ethical implications of artificial intelligence. arXiv [Preprint]. 2019 Jul 18. arXiv:1907.07892.
  17. Wei Y, Carney J, Stamper J, Belmont N. From defense to advocacy: empowering users to leverage the blind spot of AI inference. arXiv [Preprint]. 2026 Jan 16. arXiv:2601.11817.
  18. Pang CK. A comparative analysis of artificial intelligence regulation: implications for Singapore. Sing Acad Law J. 2025;37:189-232.
  19. Kumar D, Sahu CK. Artificial intelligence governance and social policy divergence: a comparative political economy perspective on global AI regulation. Int J Sociol Soc Policy. 2026:1-25. doi:10.1108/IJSSP-02-2026-0129.
  20. Burton S, Habli I, Lawton T, McDermid J, Morgan P, Porter Z. Mind the gaps: assuring the safety of autonomous systems from an engineering, ethical, and legal perspective. Artif Intell. 2020;279:103201. doi:10.1016/j.artint.2019.103201.
  21. Ebenibo L, Enyejo JO, Addo G, Olola TM. Evaluating the sufficiency of the Data Protection Act 2023 in the age of artificial intelligence (AI): a comparative case study of Nigeria and the USA. Int J Sch Res Rev. 2024;5:88-107. doi:10.56781/ijsrr.2024.5.1.0044.
  22. Swarnali SH. AI-enhanced ERP financial intelligence systems for real-time business analytics and risk decision support. ASRC Procedia Glob Perspect Sci Scholarsh. 2025;1:2703-41. doi:10.63125/t1zw3w09.
  23. Schmidt P, Biessmann F, Teubner T. Transparency and trust in artificial intelligence systems. J Decis Syst. 2020;29:260-78. doi:10.1080/12460125.2020.1819094.
  24. Tiwari R. Explainable AI (XAI) and its applications in building trust and understanding in AI decision making. Int J Sci Res Eng Manag. 2023;7:1-3. doi:10.55041/IJSREM17592.
  25. Narayanan DB. Data engineering for responsible AI: architecting ethical and transparent analytical pipelines. Int J Emerg Res Eng Technol. 2024;5:97-105.
  26. Chang X. Gender bias in hiring: an analysis of the impact of Amazon’s recruiting algorithm. Adv Econ Manag Polit Sci. 2023;23:134-40. doi:10.54254/2754-1169/23/20230367.
Regular Issue Subscription Original Research
Volume 16
Issue 02
Received 10/03/2026
Accepted 09/06/2026
Published 26/06/2026
Publication Time 108 Days

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