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

The authors have benefited from discussions with Rui Albuquerque, Elizabeth Blankespoor (discussant), Emilio Calvano (discussant), Lauren Cohen (discussant), Will Cong (discussant), Ilia Dichev, Arup Ganguly (discussant), Jillian Grennan, Rebecca Hann, Bing Han, Kathleen Hanley (discussant), Gerard Hoberg (discussant), Byoung-Hyoun Hwang (discussant), Chris Hennessy, Alan Huang (discussant), Bin Ke (discussant), Michael Kimbrough, Leonid Kogan, Augustin Landier (discussant), Tim Loughran (discussant), Song Ma, Ville Rantala (discussant), Max Rohrer (discussant), Gustavo Schwenkler (discussant), Kelly Shue, Suhas Sridharan, Isabel Wang (discussant), Teri Yohn, Gwen Yu, Dexin Zhou, and comments and suggestions from participants in seminars and conferences at Columbia, ECB, EDHEC, Emory, Georgia State, Harvard, London Business School, Maryland, Michigan, Michigan State, Peking University, Stockholm Business School, Toronto, Utah, Washington, the NBER Economics of Artificial Intelligence Conference, the NBER Big Data and Securities Markets Conference, AFA 2022, the Pacific Center for Asset Management, the SOAR Symposium at Singapore Management University, the Third Bergen FinTech Conference at the NHH Norwegian School of Economics, Machine Learning and Business Conference at University of Miami, RCFS Winter Conference, 11th Financial Markets and Corporate Governance Conference, the China FinTech Research Conference, the Adam Smith Workshop, the Conference on Financing Innovation at Stevens Institute of Technology, FIRS 2021, the Cambridge Alternative Finance Sixth Annual Conference, 2021 CAPANA Research Conference, CICF 2021, and NFA 2021. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.

• SSRN

• October 13, 2020