Ethical Considerations in AI and Data Science - Addressing Bias, Privacy, and Fairness

Authors

  • Surendranadha Reddy Byrapu Reddy Sr. Data Architect at Lincoln Financial Group, Greensboro, NC, USA Author
  • Prabu Ravichandran Sr. Data Architect, Amazon Web Services Inc., Raleigh, NC, USA Author
  • Srihari Maruthi Senior Technical Solutions Engineer, University Of New Haven, West Haven, Connecticut, USA Author
  • Mohan Raparthi Software Engineer, Google Alphabet (Verily Life Science), Dallas, Texas, USA Author https://orcid.org/0009-0004-7971-9364
  • Praveen Thunki Independent Researcher, Georgia, USA Author https://orcid.org/0009-0008-1690-4481
  • Sarath Babu Dodda Central Michigan University, Mount Pleasant, Michigan, USA Author https://orcid.org/0009-0008-2960-2378

Keywords:

Ethical considerations, AI, data science, bias, privacy, fairness, algorithmic decision-making

Abstract

Artificial intelligence (AI) and data science technologies are increasingly integrated into various aspects of society, revolutionizing industries and services. However, the rapid advancement of these technologies raises significant ethical concerns. This paper explores the ethical considerations in AI and data science, focusing on issues such as bias, privacy concerns, and fairness in algorithmic decision-making processes and outcomes.

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References

Venigandla, Kamala. "Integrating RPA with AI and ML for Enhanced Diagnostic Accuracy in Healthcare." Power System Technology 46.4 (2022).

Pillai, Aravind Sasidharan. "A Natural Language Processing Approach to Grouping Students by Shared Interests." Journal of Empirical Social Science Studies 6.1 (2022): 1-16.

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Published

2022-04-13

Issue

Vol. 2 No. 1 (2022): Australian Journal of Machine Learning Research & Applications

Section

Articles

How to Cite

[1]
Surendranadha Reddy Byrapu Reddy, P. Ravichandran, S. Maruthi, M. Raparthi, P. Thunki, and S. Babu Dodda, “Ethical Considerations in AI and Data Science - Addressing Bias, Privacy, and Fairness”, Australian Journal of Machine Learning Research & Applications, vol. 2, no. 1, pp. 1–12, Apr. 2022, Accessed: May 18, 2024. [Online]. Available: http://sydneyacademics.com/index.php/ajmlra/article/view/7

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