Ethical Challenges of Social Media Algorithms: Balancing Personalization, Privacy, and Accountability

  • Unique Paper ID: 186485
  • Volume: 12
  • Issue: no
  • PageNo: 282-284
  • Abstract:
  • In this age of social networks, coordination of user behavior, for which the networks depend on targeted content distribution, is greatly emphasized and facilitated. The purpose of this research is to analyze social media algorithms’ structure and functions with the perspective on their interaction with the people and media: how they are aimed at the escalation of the practices of enhancing the users’ activity and the creation of the echo chambers, and how they spread the lies. In this regard, the algorithms are investigated that perform the primary functions of this management: content ranking, recommending, and personalizing the content via machine learning. The article also looks at the issue of privacy, the accountability of the algorithms, and the social delegation of decision-making to algorithms, which may have bias built-in. The evidence provided suggests a further evolution of the arguments about acceptable discrimination in algorithmic design that may not overly exploit the economic incentives of platforms at the expense of social good. This research expands the important discussion about designing ethical algorithms and regulating them in the context of rapidly changing digital environment. Collecting this data shows investors that they are getting involved in a business that has done its homework.

Copyright & License

Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

BibTeX

@article{186485,
        author = {Dr. Sampada B. Deshmukh and Ayush Jadhav and Aman Padave},
        title = {Ethical Challenges of Social Media Algorithms: Balancing Personalization, Privacy, and Accountability},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {12},
        number = {no},
        pages = {282-284},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=186485},
        abstract = {In this age of social networks, coordination of user behavior, for which the networks depend on targeted content distribution, is greatly emphasized and facilitated. The purpose of this research is to analyze social media algorithms’ structure and functions with the perspective on their interaction with the people and media: how they are aimed at the escalation of the practices of enhancing the users’ activity and the creation of the echo chambers, and how they spread the lies. In this regard, the algorithms are investigated that perform the primary functions of this management: content ranking, recommending, and personalizing the content via machine learning. The article also looks at the issue of privacy, the accountability of the algorithms, and the social delegation of decision-making to algorithms, which may have bias built-in. The evidence provided suggests a further evolution of the arguments about acceptable discrimination in algorithmic design that may not overly exploit the economic incentives of platforms at the expense of social good. This research expands the important discussion about designing ethical algorithms and regulating them in the context of rapidly changing digital environment. Collecting this data shows investors that they are getting involved in a business that has done its homework.},
        keywords = {Balancing Personalization, Privacy, and Accountability.},
        month = {},
        }

Cite This Article

  • ISSN: 2349-6002
  • Volume: 12
  • Issue: no
  • PageNo: 282-284

Ethical Challenges of Social Media Algorithms: Balancing Personalization, Privacy, and Accountability

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