Ethical Considerations in Explainable Artificial Intelligence: Transparency and Accountability in AI Decision-Making

Jamil, Tahir (2024) Ethical Considerations in Explainable Artificial Intelligence: Transparency and Accountability in AI Decision-Making. Masters thesis, Dublin, National College of Ireland.

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Abstract

In many industries, AI has emerged as a powerful tool, which has raised valid concerns over the opaqueness of algorithms used in decision making processes. This paper aims to investigate the ethical considerations surrounding AXI with a focus on critical industries including; healthcare, banking and criminal justice. The main question is focused on how to effectively address the problem of realizing the applications of AI techniques as well as the demands for the interpretability, explainability, and audibility of AI decisions while promoting justice, accountability, and privacy. In a similar manner, XAI approaches are assessed, prototyped within this study, and case studies were conducted to explain how XAI could be implemented. It also entails consultations with the stakeholders in order to identify some of the issues and goals that they may have regarding the use of AI in activities such as transparency and accountability. The study’s implications indicate that XAI has the potential to improve AI governance to become more transparent and fair in applying AI technologies through eliminating risks and algorithm bias, as well as strengthening the level of trust of all interested parties. Recognizing the lack of congruency between technology adoption and its ethical implications in literature, this research will help in the progression of proper implementation policies of AI solutions.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Byrne, Brian UNSPECIFIED
Subjects:	B Philosophy. Psychology. Religion > BJ Ethics Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science Q Science > QH Natural history > QH301 Biology > Methods of research. Technique. Experimental biology > Data processing. Bioinformatics > Artificial intelligence Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Artificial intelligence
Divisions:	School of Computing > Master of Science in Artificial Intelligence for Business
Depositing User:	Ciara O'Brien
Date Deposited:	02 Jul 2025 14:34
Last Modified:	02 Jul 2025 14:34
URI:	https://norma.ncirl.ie/id/eprint/7986

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