Tailoring heuristics and timing AI interventions for supporting news veracity assessments

The detection of false and misleading news has become a top priority to researchers and practitioners. Despite the large number of efforts in this area, many questions remain unanswered about the ideal design of interventions, so that they effectively inform news consumers. In this work, we seek to...

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Autores principales:	Benjamin D. Horne, Dorit Nevo, Sibel Adali, Lydia Manikonda, Clare Arrington
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2020
Materias:	Fake news Misinformation Heuristics AI Electronic computers. Computer science QA75.5-76.95 Psychology BF1-990
Acceso en línea:	https://doaj.org/article/75be93c14a644baa8ccb920d2a44c6aa
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spelling	oai:doaj.org-article:75be93c14a644baa8ccb920d2a44c6aa2021-12-01T05:03:37ZTailoring heuristics and timing AI interventions for supporting news veracity assessments2451-958810.1016/j.chbr.2020.100043https://doaj.org/article/75be93c14a644baa8ccb920d2a44c6aa2020-08-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2451958820300439https://doaj.org/toc/2451-9588The detection of false and misleading news has become a top priority to researchers and practitioners. Despite the large number of efforts in this area, many questions remain unanswered about the ideal design of interventions, so that they effectively inform news consumers. In this work, we seek to fill part of this gap by exploring two important elements of tools’ design: the timing of news veracity interventions and the format of the presented interventions. Specifically, in two sequential studies, using data collected from news consumers through Amazon Mechanical Turk (AMT), we study whether there are differences in their ability to correctly identify fake news under two conditions: when the intervention targets novel news situations and when the intervention is tailored to specific heuristics. We find that in novel news situations users are more receptive to the advice of the AI, and further, under this condition tailored advice is more effective than generic one. We link our findings to prior literature on confirmation bias and we provide insights for news providers and AI tool designers to help mitigate the negative consequences of misinformation.Benjamin D. HorneDorit NevoSibel AdaliLydia ManikondaClare ArringtonElsevierarticleFake newsMisinformationHeuristicsAIElectronic computers. Computer scienceQA75.5-76.95PsychologyBF1-990ENComputers in Human Behavior Reports, Vol 2, Iss , Pp 100043- (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Fake news Misinformation Heuristics AI Electronic computers. Computer science QA75.5-76.95 Psychology BF1-990
spellingShingle	Fake news Misinformation Heuristics AI Electronic computers. Computer science QA75.5-76.95 Psychology BF1-990 Benjamin D. Horne Dorit Nevo Sibel Adali Lydia Manikonda Clare Arrington Tailoring heuristics and timing AI interventions for supporting news veracity assessments
description	The detection of false and misleading news has become a top priority to researchers and practitioners. Despite the large number of efforts in this area, many questions remain unanswered about the ideal design of interventions, so that they effectively inform news consumers. In this work, we seek to fill part of this gap by exploring two important elements of tools’ design: the timing of news veracity interventions and the format of the presented interventions. Specifically, in two sequential studies, using data collected from news consumers through Amazon Mechanical Turk (AMT), we study whether there are differences in their ability to correctly identify fake news under two conditions: when the intervention targets novel news situations and when the intervention is tailored to specific heuristics. We find that in novel news situations users are more receptive to the advice of the AI, and further, under this condition tailored advice is more effective than generic one. We link our findings to prior literature on confirmation bias and we provide insights for news providers and AI tool designers to help mitigate the negative consequences of misinformation.
format	article
author	Benjamin D. Horne Dorit Nevo Sibel Adali Lydia Manikonda Clare Arrington
author_facet	Benjamin D. Horne Dorit Nevo Sibel Adali Lydia Manikonda Clare Arrington
author_sort	Benjamin D. Horne
title	Tailoring heuristics and timing AI interventions for supporting news veracity assessments
title_short	Tailoring heuristics and timing AI interventions for supporting news veracity assessments
title_full	Tailoring heuristics and timing AI interventions for supporting news veracity assessments
title_fullStr	Tailoring heuristics and timing AI interventions for supporting news veracity assessments
title_full_unstemmed	Tailoring heuristics and timing AI interventions for supporting news veracity assessments
title_sort	tailoring heuristics and timing ai interventions for supporting news veracity assessments
publisher	Elsevier
publishDate	2020
url	https://doaj.org/article/75be93c14a644baa8ccb920d2a44c6aa
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Tailoring heuristics and timing AI interventions for supporting news veracity assessments

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