Forecast Uncertainty Information Improves Multi-Alternative Risky Decision-Making

Jee Hoon Han a University of Washington, Seattle, Washington, USA

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Susan Joslyn a University of Washington, Seattle, Washington, USA

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Abstract

Research suggests that non-experts make better decisions in binary decision tasks and have higher trust in forecasts that include numeric uncertainty estimates (e.g., 30% chance) compared to single value forecasts (e.g., 6 inches snow accumulation). However, in real-world situations in which one must choose between protective action at a cost or risking a larger probabilistic loss, there is often an intermediate option. Two experiments, reported here, tested whether the previously shown advantages for numeric uncertainty forecasts generalize to decisions with three options. In a snow-day school closure paradigm, a 2-option condition (close, open) was compared to a 3-option condition that also included a cheaper alternative (delay) with less protection than closing, but more protection than staying open when snow occurred. The advantages of probabilistic forecasts persisted regardless of the number of options. In addition, the risk-seeking tendency, typical for decisions between losses, was attenuated in the 3-option condition in Experiment 1 and reversed in Experiment 2.

© 2025 American Meteorological Society. This is an Author Accepted Manuscript distributed under the terms of the default AMS reuse license. For information regarding reuse and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Jee Hoon Han, jhan326@u.washington.edu

Abstract

Research suggests that non-experts make better decisions in binary decision tasks and have higher trust in forecasts that include numeric uncertainty estimates (e.g., 30% chance) compared to single value forecasts (e.g., 6 inches snow accumulation). However, in real-world situations in which one must choose between protective action at a cost or risking a larger probabilistic loss, there is often an intermediate option. Two experiments, reported here, tested whether the previously shown advantages for numeric uncertainty forecasts generalize to decisions with three options. In a snow-day school closure paradigm, a 2-option condition (close, open) was compared to a 3-option condition that also included a cheaper alternative (delay) with less protection than closing, but more protection than staying open when snow occurred. The advantages of probabilistic forecasts persisted regardless of the number of options. In addition, the risk-seeking tendency, typical for decisions between losses, was attenuated in the 3-option condition in Experiment 1 and reversed in Experiment 2.

© 2025 American Meteorological Society. This is an Author Accepted Manuscript distributed under the terms of the default AMS reuse license. For information regarding reuse and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Jee Hoon Han, jhan326@u.washington.edu
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