| Issue |
E3S Web Conf.
Volume 399, 2023
International Conference on Newer Engineering Concepts and Technology (ICONNECT-2023)
|
|
|---|---|---|
| Article Number | 04030 | |
| Number of page(s) | 9 | |
| Section | Computer Science | |
| DOI | https://doi.org/10.1051/e3sconf/202339904030 | |
| Published online | 12 July 2023 | |
Exploring Explainable Artificial Intelligence for Transparent Decision Making
1 Assistant Professor, School of Business and Management, CHRIST (Deemed to be University), Bangalore
2 Assistant Professor, School of Business and Management, CHRIST (Deemed to be University), Bangalore
3 Assistant Professor, Prince Shri Venkateshwara Padmavathy Engineering College, Chennai – 127
4 College of technical engineering, The Islamic university, Najaf, Iraq
5 Tashkent State Pedagogical University, Tashkent, Uzbekistan
6 Department of electronics and communication engineering, K. Ramakrishnan college of technology, Tiruchirapalli
7 Department of artificial intelligence and data science, K. Ramakrishnan college of technology, Tiruchirapalli
vennila.c_maths@psvpec.in
ahmedalawadi@iunajaf.edu.iq
diyoratohirovna@gmail.com
Artificial intelligence (AI) has become a potent tool in many fields, allowing complicated tasks to be completed with astounding effectiveness. However, as AI systems get more complex, worries about their interpretability and transparency have become increasingly prominent. It is now more important than ever to use Explainable Artificial Intelligence (XAI) methodologies in decision-making processes, where the capacity to comprehend and trust AI-based judgments is crucial. This abstract explores the idea of XAI and how important it is for promoting transparent decision-making. Finally, the development of Explainable Artificial Intelligence (XAI) has shown to be crucial for promoting clear decision-making in AI systems. XAI approaches close the cognitive gap between complicated algorithms and human comprehension by empowering users to comprehend and analyze the inner workings of AI models. XAI equips stakeholders to evaluate and trust AI systems, assuring fairness, accountability, and ethical standards in fields like healthcare and finance where AI-based choices have substantial ramifications. The development of XAI is essential for attaining AI's full potential while retaining transparency and human-centric decision making, despite ongoing hurdles.
Key words: Artificial Intelligence / Data Collection and Preprocessing / Transparent Decision Making
© The Authors, published by EDP Sciences, 2023
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