Natural Language Generation enhances human decision-making with uncertain information

Dimitra Gkatzia, Oliver Lemon, Verena Rieser

Research output: Chapter in Book/Report/Conference proceedingConference contribution

15 Citations (Scopus)

Abstract

Decision-making is often dependent on uncertain data, e.g. data associated with confidence scores or probabilities. We present a comparison of different information presentations for uncertain data and,for the first time, measure their effects on human decision-making. We show that the use of Natural Language Generation (NLG) improves decision-making under uncertainty, compared to state-of-the art graphical-based representation methods.In a task-based study with 442 adults,we found that presentations using NLG lead to 24% better decision-making on average than the graphical presentations, and to 44% better decision-making when NLG is combined with graphics. We also show that women achieve significantly better results when presented with NLG output(an 87% increase on average compared to graphical presentations).
Original languageEnglish
Title of host publicationProceedings of the 54th Annual Meeting of the Association for Computational Linguistics
PublisherAssociation for Computational Linguistics
Pages264-268
Number of pages5
Volume2
ISBN (Print)9781945626012
DOIs
Publication statusPublished - 2016
Event54th Annual Meeting of the Association for Computational Linguistics 2016 - Berlin, Germany
Duration: 7 Aug 201612 Aug 2016

Conference

Conference54th Annual Meeting of the Association for Computational Linguistics 2016
Abbreviated titleACL 2016
CountryGermany
CityBerlin
Period7/08/1612/08/16

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