解析可解释AI的最新进展与未来趋势，聚焦可信AI与元推理融合。
Explainable AI the Latest Advancements and New Trends
- 系统梳理全球可信AI伦理框架与可解释性技术
- 揭示可解释AI与自主系统元推理的深层关联
- 适合关注AI透明性与可信决策的研究者
近年来，人工智能在各领域广泛应用，但神经网络算法的复杂性使其决策过程难以理解。为此，可信AI技术日益受到重视。可信性涉及跨学科标准，需通过技术手段满足社会伦理要求。本文首先综述了各国在使人工智能可信的伦理要素方面的进展，随后聚焦于当前可解释性AI的前沿研究。我们深入调研了实现AI可解释性的各类技术与方法，并识别出新趋势。特别强调了可解释AI与自主系统元推理之间的紧密联系。元推理即‘对推理进行推理’，与可解释AI的目标高度一致。二者结合有望推动未来可解释性AI系统的发展。
原文摘要 · Abstract (English)
In recent years, Artificial Intelligence technology has excelled in various applications across all domains and fields. However, the various algorithms in neural networks make it difficult to understand the reasons behind decisions. For this reason, trustworthy AI techniques have started gaining popularity. The concept of trustworthiness is cross-disciplinary; it must meet societal standards and principles, and technology is used to fulfill these requirements. In this paper, we first surveyed developments from various countries and regions on the ethical elements that make AI algorithms trustworthy; and then focused our survey on the state of the art research into the interpretability of AI. We have conducted an intensive survey on technologies and techniques used in making AI explainable. Finally, we identified new trends in achieving explainable AI. In particular, we elaborate on the strong link between the explainability of AI and the meta-reasoning of autonomous systems. The concept of meta-reasoning is 'reason the reasoning', which coincides with the intention and goal of explainable Al. The integration of the approaches could pave the way for future interpretable AI systems.
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