SCIENCE@home

Advancing Ethical Ai: Emerging Trends in Transparency, Fairness, and Explainability

Hajar Majjate,Youssra Bellarhmouch,Adil Jeghal,Ali Yahyaouy,Loubna Laaouina,Hamid Tairi,Khalid Alaoui Zidani

Published 2025 in IEEE International Conference on Circuits and Systems for Communications

ABSTRACT

Artificial Intelligence (AI) has emerged as a revolutionary technology across various domains, including healthcare, finance, education, and autonomous systems. However, the implementation of AI, particularly deep learning intelligence, brings about serious issues concerning data privacy, transparency and user security. These concerns are currently critical, as addressing them is important for building trust, achieving public acceptance, and ensuring fairness and accountability in AI applications. To tackle these challenges, new subfields have been developed, including Explainable AI (XAI), Fairness-Aware Machine Learning, and Responsible AI. These emerging subfields of AI emphasise the importance of creating AI systems that prioritise interpretability, transparency, and trustworthiness while aligning advancements with society's collective values, ethical principles, and regulatory standards. However, a key challenge remains in balancing AI performance with the emphasis on user privacy. This paper contributes to the extant academic discourse surrounding the ethics of artificial intelligence by conducting a comprehensive analysis of emerging trends within this evolving field. Furthermore, it proposes a systematic framework aimed at addressing these trends and provides additional recommendations for the implementation of responsible methodologies in the development of ethical AI models.

PUBLICATION RECORD

CITATION MAP

EXTRACTION MAP

CLAIMS

  • No claims are published for this paper.

CONCEPTS

  • No concepts are published for this paper.

REFERENCES

Showing 1-50 of 50 references · Page 1 of 1

CITED BY

  • No citing papers are available for this paper.

Showing 0-0 of 0 citing papers · Page 1 of 1