Natural Language Generation enhances human decision-making with uncertain information

TL;DR

This study demonstrates that Natural Language Generation (NLG) significantly improves human decision-making under uncertainty, especially when combined with graphics, with notable benefits observed across genders.

Contribution

The paper provides the first empirical comparison showing NLG's effectiveness over graphical methods in aiding decision-making with uncertain data.

Findings

NLG improves decision accuracy by 24% over graphical methods.

Combining NLG with graphics increases decision accuracy by 44%.

Women benefit significantly more from NLG, with an 87% improvement.

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).