A prevalent stereotype is that people become less risk taking and more cautious as they get older. However, in laboratory studies, findings are mixed and often reveal no age differences. In the current series of experiments, we examined whether age differences in risk seeking are more likely to emerge when choices include a certain option (a sure gain or a sure loss). In four experiments, we found that age differences in risk preferences only emerged when participants were offered a choice between a risky and a certain gamble but not when offered two risky gambles. In particular, Experiments 1 and 2 included only gambles about potential gains. Here, compared with younger adults, older adults preferred a certain gain over a chance to win a larger gain and thus, exhibited more risk aversion in the domain of gains. But in Experiments 3 and 4, when offered the chance to take a small sure loss rather than risking a larger loss, older adults exhibited more risk seeking in the domain of losses than younger adults. Both their greater preference for sure gains and greater avoidance of sure losses suggest that older adults weigh certainty more heavily than younger adults. Experiment 4 also indicates that older adults focus more on positive emotions than younger adults do when considering their options and that this emotional shift can at least partially account for age differences in how much people are swayed by certainty in their choices.

For high-impact weather events, forecasts often start days in advance. Forecasters believe that consistency among subsequent forecasts is important to user trust and can be reluctant to make changes when newer, potentially more accurate information becomes available. However, to date, there is little empirical evidence for an effect of inconsistency among weather forecasts on user trust, although the reduction in trust due to inaccuracy is well documented. The experimental studies reported here compared the effects of forecast inconsistency and inaccuracy on user trust. Participants made several school closure decisions based on snow accumulation forecasts for one and two days prior to the target event. Consistency and accuracy were varied systematically. Although inconsistency reduced user trust, the effect of the reduction due to inaccuracy was greater in most cases suggesting that it is inadvisable for forecasters to sacrifice accuracy in favor of consistency.

In the ultimatum game, one player proposes a split of money between him- or herself and another player, who can accept the offer (and both players keep the allocated money) or reject the offer (and both players get nothing). The present study examined predictors of accepting unfair ultimatum offers. In Study 1, 184 participants responded to an unfair ultimatum offer, completed a measure of cognitive reflection, and completed a self-report measure of rational and experiential thinking. Slightly more than half of the participants (54.3%) accepted the unfair offer, and cognitive reflection was positively correlated with accepting unfair offers. The rational and experiential thinking scales were not significantly correlated with ultimatum decisions. In Study 2, 306 participants responded to 20 ultimatum offers that varied in fairness and completed an expanded measure of cognitive reflection. Performance on the cognitive reflection measure predicted the number of ultimatum offers accepted. These results suggest that rejecting ultimatum offers is related to intuitive, heuristic-based thinking, whereas accepting offers is related to deliberate, analytic-based thinking.

People access weather forecasts from multiple sources (mobile apps, newspapers and television) that are not always in agreement for a particular weather event. The experiment reported here investigated the effects of inconsistency among forecasts on user trust, weather-related decisions, and confidence in user decisions. In a computerized task, participants made school closure decisions based on snow forecasts from different sources and answered a series of questions about each forecast. Inconsistency among simultaneous forecasts did not significantly reduce trust, although inaccuracy did. Moreover, inconsistency may convey useful information to decisions makers. Not only do participants appear to incorporate the information provided by all forecasts into their own estimates of the outcome, but our results also suggest that inconsistency gives rise to the impression of greater uncertainty leading to more cautious decisions. The implications for decisions in a variety of domains are discussed.

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, the experiment reported here, 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. Half of participants received single-value forecasts and half also received the probability of 6 or more inches (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 well benefit from well-calibrated uncertainty estimates and newer, more reliable information.