Explainable Artificial Intelligence addresses the black box problem associated with AI, aiming to promote greater transparency, traceability, and trust in applications of AI. xAI is becoming a vital element in finance and economics in fields like risk management, credit decisions, and regulatory compliance. The need for xAI arises from the challenges in understanding, trusting, and communicating AI-generated results. While some argue for the adoption of inherently interpretable models, others critique popular xAI methods. This special issue explores xAI’s role in finance and its advances, focusing on its implications for future research, practice, and policy in FinTech.

中文翻译：

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金融领域可解释人工智能 （xAI） 的进展


可解释的人工智能解决了与 AI 相关的黑盒问题，旨在提高 AI 应用的透明度、可追溯性和信任度。xAI 正在成为风险管理、信贷决策和监管合规等领域的金融和经济学的重要组成部分。对 xAI 的需求源于理解、信任和交流 AI 生成的结果所面临的挑战。虽然一些人主张采用本质上可解释的模型，但另一些人则批评流行的 xAI 方法。本期特刊探讨了 xAI 在金融中的作用及其进步，重点关注其对金融科技未来研究、实践和政策的影响。