Proceedings of the Conference on Bridging Engineering Disciplines with AI and Machine Learning (BEDAIML 2026)

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A Systematic Analysis and Taxonomy of Ethical AI Frameworks: Principles, Practices, and Future Directions

Authors
Harpreet Singh Dalla1, Sonal Rattan1, 2, *, Gesu Thakur3
1AIT-CSE, Chandigarh University, Mohali, India
2Dept of UCRD, Chandigarh University, Mohali, India
3College of Smart Computing, COER University, Roorkee, India
*Corresponding author. Email: sonal.e15123@cumail.in
Corresponding Author
Sonal Rattan
Available Online 4 June 2026.
DOI
10.2991/978-94-6239-697-5_7How to use a DOI?
Keywords
AI governance; ethical AI; Taxonomy; systematic review; AI Ethics Frameworks
Abstract

Artificial Intelligence (AI) has become an important technology in different sectors such as finance, healthcare, education, transportation and public administration. Various industries are achieving production efficiency, accuracy and innovation with AI’s power of analyzing data, making predictions and taking automated decisions. Undoubtedly, AI has proved to be beneficial, however there are some ethical issues such as privacy risks, lack of transparency, bias, discrimination and accountability issues associated with it. Many governments, corporations and universities have developed various frameworks to ensure responsible AI design and use; however, these frameworks are either inconsistent and fragmented or difficult to implement. This research focuses on systematic review of various AI frameworks introduced by different organisations. Several AI frameworks from different sources have been analyzed before proposing a multi-level taxonomy to classify these frameworks based on stakeholders, lifecycle stages and principles. This paper also discusses challenges, trends and research gaps in accomplishing the successful implementation of AI ethics. The main goal is to help policymakers, researchers and practitioners to develop trustworthy AI frameworks which will increase transparency, governance and public interest in AI technologies.

Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the Conference on Bridging Engineering Disciplines with AI and Machine Learning (BEDAIML 2026)
Series
Advances in Intelligent Systems Research
Publication Date
4 June 2026
ISBN
978-94-6239-697-5
ISSN
1951-6851
DOI
10.2991/978-94-6239-697-5_7How to use a DOI?
Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Harpreet Singh Dalla
AU  - Sonal Rattan
AU  - Gesu Thakur
PY  - 2026
DA  - 2026/06/04
TI  - A Systematic Analysis and Taxonomy of Ethical AI Frameworks: Principles, Practices, and Future Directions
BT  - Proceedings of the Conference on Bridging Engineering Disciplines with AI and Machine Learning (BEDAIML 2026)
PB  - Atlantis Press
SP  - 60
EP  - 66
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6239-697-5_7
DO  - 10.2991/978-94-6239-697-5_7
ID  - Dalla2026
ER  -