$恒生指数(HKHSI)$ “人工智能给投资者带来的风险？”这个观点大家怎么看？现在的市场现状跟这个有关吗？
1. Gary Gensler, chair of the U.S. Securities and Exchange Commission, has been speaking publicly in recent weeks about the risks that artificial intelligence poses to investors.
1.美国证券交易委员会(SEC)主席加里•詹斯勒(Gary Gensler)最近几周一直在公开谈论人工智能给投资者带来的风险。
The topic is not new to him. While a professor at MIT Sloan, Gensler explored these issues in-depth in a 2020 paper, “Deep Learning and Financial Stability,” written with then-research assistant Lily Bailey. The paper outlines five pathways whereby broad adoption of deep learning, a subset of AI, could 网页链接{increase fragility in the financial system}.
这个话题对他来说并不新鲜。作为麻省理工学院斯隆管理学院的教授，詹斯勒在2020年与当时的研究助理莉莉 · 贝利(Lily Bailey)共同撰写的论文《深度学习与金融稳定》(Deep Learning and Financial Stability)中深入探讨了这些问题。这篇论文概述了五种途径，广泛采用深度学习(人工智能的一个子集)可能会增加金融体系的脆弱性。
Among the authors’ areas of concern:
作者关注的领域包括:
Data. Across different economic sectors, Gensler and Bailey noted coalescence around important datasets. “Models built on the same datasets are likely to generate highly correlated predictions that proceed in lockstep, causing crowding and herding,” the authors wrote.百科。在不同的经济部门，Gensler 和 Bailey 注意到重要数据集的合并。作者写道: “建立在相同数据集上的模型可能会产生高度相关的预测，这些预测会同步进行，从而导致拥挤和羊群。”。
Model design. The unique attributes and construction of deep learning models might increase market sensitivity. When models coordinate and communicate with each other to optimize results, it’s possible that they will execute the same strategies, increasing volatility.模型设计。深度学习模型的独特属性和结构可能会增加市场敏感性。当模型相互协调和沟通以优化结果时，它们可能会执行相同的策略，从而增加波动性。
User interfaces. Large financial institutions and fintech startups alike offer chatbots and virtual assistants. But the standardization of these tools could cause herding across client decision-making and, potentially, across an entire asset class or sector.用户界面。大型金融机构和金融科技初创企业都提供聊天机器人和虚拟助理。但是，这些工具的标准化可能导致客户决策过程中的羊群行为，甚至可能导致整个资产类别或部门的羊群行为。