Natural Language Generation enhances human decision-making with uncertain information
June 10, 2016 ยท Declared Dead ยท ๐ Annual Meeting of the Association for Computational Linguistics
"No code URL or promise found in abstract"
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Authors
Dimitra Gkatzia, Oliver Lemon, Verena Rieser
arXiv ID
1606.03254
Category
cs.CL: Computation & Language
Cross-listed
cs.AI
Citations
61
Venue
Annual Meeting of the Association for Computational Linguistics
Last Checked
5 months ago
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).
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