Journal article : Comment

Misinformation reloaded? Fears about the impact of generative AI on misinformation are overblown

Abstract:: Many observers of the current explosion of generative AI worry about its impact on our information environment, with concerns being raised about the increased quantity, quality, and personalization of misinformation. We assess these arguments with evidence from communication studies, cognitive science, and political science. We argue that current concerns about the effects of generative AI on the misinformation landscape are overblown.

Publication status:: Published

Peer review status:: Peer reviewed

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APA Style

Simon, F. M., Altay, S., & Mercier, H. (2023). Misinformation reloaded? Fears about the impact of generative AI on misinformation are overblown. Harvard Kennedy School Misinformation Review, 4(5).

MLA Style

Simon, F. M., et al. “Misinformation Reloaded? Fears about the Impact of Generative AI on Misinformation Are Overblown.” Harvard Kennedy School Misinformation Review, vol. 4, no. 5, Harvard Kennedy School, 2023.

Chicago Style

Simon, FM, S Altay, and H Mercier. 2023. “Misinformation Reloaded? Fears about the Impact of Generative AI on Misinformation Are Overblown.” Harvard Kennedy School Misinformation Review 4 (5).
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Files:: Simon_et_al_2023_Misinformation_reloaded_Fears.pdf

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Publisher copy:: 10.37016/mr-2020-127

Authors

+ Simon, FM More by this author

Institution:: University of Oxford
Division:: SSD
Department:: Oxford Internet Institute
Role:: Author

+ Altay, S More by this author

Role:: Author

+ Mercier, H More by this author

Role:: Author

Publisher:: Harvard Kennedy School
Journal:: Harvard Kennedy School Misinformation Review More from this journal
Volume:: 4
Issue:: 5
Publication date:: 2023-10-18
Acceptance date:: 2023-09-25
DOI:: 10.37016/mr-2020-127
ISSN:: 2766-1652

Language:: English
Keywords:: FFR

artificial intelligence
Subtype:: Comment
Pubs id:: 1545140
Local pid:: pubs:1545140
Deposit date:: 2023-10-18

Terms of use

Copyright holder:: Simon et al
Copyright date:: 2023
Rights statement:: ©2023 The Authors. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided that the original author and source are properly credited.

Licence:: CC Attribution (CC BY)

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