让复杂AI可理解，提升可信度与社会接受度
Trustworthy XAI and Application
- 从透明、可解释到可信三方面构建XAI体系
- 强调真实场景中责任与公平的重要性
- 适合关注AI伦理与落地应用的研究者
人工智能已成为日常生活中不可或缺的部分，应用于自动驾驶汽车和智能手机助手等场景。由于其复杂的系统结构，尤其是深度神经网络，常被称作‘黑箱’，引发对责任归属、偏见与公平性的担忧，尽管其准确性较高。可解释人工智能（XAI）对于建立信任至关重要，有助于确保AI系统可靠且合乎伦理。本文探讨XAI的三大核心要素：透明性、可解释性与可信性，并分析这些要素在现实情境中的重要性。同时回顾了近年来不同领域中XAI的应用研究。最终指出，获得社会对AI系统的信任，是其成功推广的关键。
原文摘要 · Abstract (English)
Artificial Intelligence (AI) is an important part of our everyday lives. We use it in self-driving cars and smartphone assistants. People often call it a "black box" because its complex systems, especially deep neural networks, are hard to understand. This complexity raises concerns about accountability, bias, and fairness, even though AI can be quite accurate. Explainable Artificial Intelligence (XAI) is important for building trust. It helps ensure that AI systems work reliably and ethically. This article looks at XAI and its three main parts: transparency, explainability, and trustworthiness. We will discuss why these components matter in real-life situations. We will also review recent studies that show how XAI is used in different fields. Ultimately, gaining trust in AI systems is crucial for their successful use in society.
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