Advancing Responsible, Generative, and Explainable AI: Challenges, Opportunities, and Future Directions

Abstract

As AI continues to evolve rapidly, many new and productive models have emerged in the industry. But lack of transparency and accountability even after huge developments in the field of Artificial Intelligence (AI). The reason for the lack is the focus on Responsible, Generative, and Explainable AI(RGX-AI). In this paper, we propose an integration framework for GAI (Generative AIs), XAI (Explainable AIs), and RAI (Responsible AIs). Furthermore, this paper highlights some of the challenges faced in RGX-AI, such as bias, interpretability, and governance, and suggests enhancements through technological innovations, interdisciplinary collaboration, and global policy frameworks. This paper also proposes a roadmap for advancing RGX-AI, with a strong emphasis on developing scalable solutions that are both ethical and transparent, thereby gaining societal trust and delivering benefits.

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