透明度(行为)
可解释性
计算机科学
商业智能
数据科学
人工智能
管理科学
知识管理
工程类
计算机安全
作者
Hanna DeSimone,Maikel Leon-Espinosa
标识
DOI:10.1109/icict62343.2024.00093
摘要
This paper provides an in-depth examination of Explainable Artificial Intelligence (XAI) and its significance in developing responsible AI. It covers the history of AI, the fundamental principles, the difference between explainability and interpretability, and the types of explanations. The paper highlights the role of transparency in explainable systems. Moreover, it discusses applications across high-stakes domains. Additionally, it touches on the current regulatory landscape and presents an outlook on the future of XAI research and regulation.
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