How to Talk When a Machine is Listening: Corporate Disclosure in the Age of AI

S. Cao, Wei Jiang, Baozhong Yang, Alan L. Zhang
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引用次数: 50

Abstract

Growing AI readership (proxied for by machine downloads and ownership by AI-equipped investors) motivates firms to prepare filings friendlier to machine processing and to mitigate linguistic tones that are unfavorably perceived by algorithms. Loughran and McDonald (2011) and BERT available since 2018 serve as event studies supporting attribution of the decrease in the measured negative sentiment to increased machine readership. This relationship is stronger among firms with higher benefits to (e.g., external financing needs) or lower cost (e.g., litigation risk) of sentiment management. This is the first study exploring the feedback effect on corporate disclosure in response to technology.
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机器在倾听时如何说话:人工智能时代的企业信息披露
越来越多的人工智能读者(以机器下载和人工智能投资者的所有权为代表)促使公司准备对机器处理更友好的文件,并减轻算法所感知的不利语言语调。Loughran和McDonald(2011)以及自2018年以来可用的BERT作为事件研究,支持将测量的负面情绪减少归因于机器读者人数的增加。在情绪管理收益较高(如外部融资需求)或成本较低(如诉讼风险)的公司中,这种关系更强。本研究首次探讨科技对企业信息披露的反馈效应。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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