Ethical Challenges in Natural Language Processing: A Comparative Study of Solutions Across Multiple Domains

Year : 2026 | Volume : 13 | 01 | Page :
    By

    Khushi Singh,

  • Sheetal Singh,

  • Aritro Chakraborty,

  • Himanshu Singh,

  • Sujeet Kumar,

  1. Student, Department of Computer Application, Echelon Institute of Technology, Faridabad, Haryana, India
  2. Student, Department of Computer Application, Echelon Institute of Technology, Faridabad, Haryana, India
  3. Student, Department of Computer Application, Echelon Institute of Technology, Faridabad, Haryana, India
  4. Student, Department of Computer Application, GL BAJAJ Institute of Management, Greater Noida, Haryana, India
  5. Student, Department of Computer Application, GL BAJAJ Institute of Management, Greater Noida, Haryana, India

Abstract

This comparative analysis investigates the ethical challenges associated with Natural Language Processing (NLP) by reviewing and synthesizing insights from ten influential and widely cited publications in the field. As NLP technologies are increasingly integrated into domains such as healthcare, finance, education, and governance, ethical concerns related to algorithmic bias, data privacy, fairness, accountability, and system transparency have become more prominent. This paper systematically examines how different researchers conceptualize and address these ethical issues, highlighting both converging and diverging perspectives. Particular attention is given to contrasting approaches to data privacy, including consent, anonymization, and responsible data usage, as well as shared strategies aimed at improving transparency and reducing bias in NLP models. Additionally, the study explores the broader societal consequences of ethical decision-making in NLP, such as impacts on marginalized communities and public trust in automated systems. By integrating diverse scholarly viewpoints, this analysis provides a clearer understanding of the current ethical landscape in NLP research and development. The findings aim to inform future research directions and support the design of more responsible, inclusive, and ethically grounded NLP applications.

Keywords: Ethical considerations, Natural Language Processing(NLP), NLP ethics, Bias, Privacy, Fairness, Transparency, ChatGPT

How to cite this article:
Khushi Singh, Sheetal Singh, Aritro Chakraborty, Himanshu Singh, Sujeet Kumar. Ethical Challenges in Natural Language Processing: A Comparative Study of Solutions Across Multiple Domains. Journal of Mobile Computing, Communications & Mobile Networks. 2026; 13(01):-.
How to cite this URL:
Khushi Singh, Sheetal Singh, Aritro Chakraborty, Himanshu Singh, Sujeet Kumar. Ethical Challenges in Natural Language Processing: A Comparative Study of Solutions Across Multiple Domains. Journal of Mobile Computing, Communications & Mobile Networks. 2026; 13(01):-. Available from: https://journals.stmjournals.com/jomccmn/article=2026/view=240087


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Ahead of Print Subscription Review Article
Volume 13
01
Received 20/06/2025
Accepted 08/10/2025
Published 15/04/2026
Publication Time 299 Days
1

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