Democratizing AI: Empowering Users Through Explainable Artificial Intelligence

EasyChair Preprint no. 12312

Abstract

Artificial Intelligence (AI) has become increasingly pervasive, impacting various facets of modern life, from healthcare to finance, education, and beyond. However, as AI systems become more sophisticated, concerns about their opacity and lack of interpretability have grown. This has led to a call for Explainable Artificial Intelligence (XAI), which aims to make AI systems transparent and understandable to users. Democratizing AI through XAI is crucial for fostering trust, accountability, and inclusivity in AI-driven decision-making processes. This paper explores the concept of democratizing AI through XAI, emphasizing the importance of empowering users with insights into AI models' inner workings. We discuss key principles and techniques of XAI, such as model interpretability, transparency, and accountability. Finally, we highlight challenges and future directions in the pursuit of democratizing AI through XAI, emphasizing the need for interdisciplinary collaboration, regulatory frameworks, and ongoing research to realize the full potential of transparent and accountable AI systems in promoting societal well-being and equitable access to AI technologies.

Keyphrases: Democratizing AI, Explainable Artificial Intelligence, transparency

@Booklet{EasyChair:12312,
  author = {Jane Elsa and Hakan Halil},
  title = {Democratizing AI: Empowering Users Through Explainable Artificial Intelligence},
  howpublished = {EasyChair Preprint no. 12312},

  year = {EasyChair, 2024}}