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

Sean Cao Robert H. Smith, Wei Jiang, Baozhong Yang J. Mack Robinson, Alan Zhang and Tarun Ramadorai

The Review of Financial Studies, 2023, vol. 36, issue 9, 3603-3642

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.Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

JEL-codes: D83 G14 G30 (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (4)

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Working Paper: How to Talk When a Machine is Listening?: Corporate Disclosure in the Age of AI (2020)
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