Forecasts about future emotion are often inaccurate, so why do people rely on them to make decisions? People may forecast some features of their emotional experience better than others, and they may report relying on forecasts that are more accurate to make decisions. To test this, four studies assessed the features of emotion people reported forecasting to make decisions about their careers, education, politics, and health. In Study 1, graduating medical students reported relying more on forecast emotional intensity than frequency or duration to decide how to rank residency programs as part of the process of being matched with a program. Similarly, participants reported relying more on forecast emotional intensity than frequency or duration to decide which universities to apply to (Study 2), which presidential candidate to vote for (Study 3), and whether to travel as Covid-19 rates declined (Study 4). Studies 1 and 3 also assessed forecasting accuracy. Participants forecast emotional intensity more accurately than frequency or duration. People make better decisions when they can anticipate the future. Thus, people’s reports of relying on forecast emotional intensity to guide life-changing decisions, and the greater accuracy of these forecasts, provide important new evidence of the adaptive value of affective forecasts.
When forecasts for a major weather event begin days in advance, updates may be more accurate but inconsistent with the original forecast. Evidence suggests that resulting inconsistency may reduce user trust. However, adding an uncertainty estimate to the forecast may attenuate any loss of trust due to forecast inconsistency, as has been shown with forecast inaccuracy. To evaluate this hypothesis, this experiment tested the impact on trust of adding probabilistic snow-accumulation forecasts to single-value forecasts in a series of original and revised forecast pairs (based on historical records) that varied in both consistency and accuracy. Participants rated their trust in the forecasts and used them to make school-closure decisions. One-half of the participants received single-value forecasts, and one-half also received the probability of 6 in. or more (decision threshold in the assigned task). As with previous research, forecast inaccuracy was detrimental to trust, although probabilistic forecasts attenuated the effect. Moreover, the inclusion of probabilistic forecasts allowed participants to make economically better decisions. Surprisingly, in this study inconsistency increased rather than decreased trust, perhaps because it alerted participants to uncertainty and led them to make more cautious decisions. Furthermore, the positive effect of inconsistency on trust was enhanced by the inclusion of probabilistic forecast. This work has important implications for practical settings, suggesting that both probabilistic forecasts and forecast inconsistency provide useful information to decision-makers. Therefore, members of the public may benefit from well-calibrated uncertainty estimates and newer, more reliable information.
The purpose of this study was to clarify how explicit uncertainty information and forecast inconsistency impact trust and decision-making in the context of sequential forecasts from the same source. This is important because trust is critical for effective risk communication. In the absence of trust, people may not use available information and subsequently may put themselves and others at greater-than necessary risk. Our results suggest that updating forecasts when newer, more reliable information is available and providing reliable uncertainty estimates can support user trust and decision-making.
- PAR ID:
- 10438734
- Publisher / Repository:
- American Meteorological Society
- Date Published:
- Journal Name:
- Weather, Climate, and Society
- Volume:
- 15
- Issue:
- 3
- ISSN:
- 1948-8327
- Page Range / eLocation ID:
- p. 693-709
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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