Overprecision in Judgment

Moore, Don A.; Tenney, Elizabeth R.; Haran, Uriel

doi:10.1002/9781118468333.ch6

Cited by 100 publications

(66 citation statements)

References 157 publications

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“…Still, we cannot rule out the possibility that high precision and high confidence go together in statements experts actually make. The conversational norms‐account of overprecision (Moore et al, ) suggests that people try to make their statements as informative as possible. This implies that an expert might try to simultaneously maximize both precision and confidence, at the risk of exaggerating both.…”

Section: Discussionmentioning

confidence: 99%

“…When different groups are instructed to estimate 90 and 50% intervals, they do not appear to be sensitive to the assigned confidence level and produce intervals of the same width (Langnickel & Zeisberger, ; Teigen & Jørgensen, ), leading to overprecise 90% intervals but more well‐calibrated 50% intervals. Thus, overprecision can in part be attributed to a deficient understanding of probability distributions (Moore, Tenney, & Haran, ).…”

Section: Overprecision and The Preciseness Paradoxmentioning

confidence: 99%

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Probabilities Associated with Precise and Vague Forecasts

Løhre

Teigen

2017

Behavioral Decision Making

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Forecasts of future outcomes, such as the consequences of climate change, are given with different degrees of precision. Logically, more precise forecasts (e.g., a temperature increase of 3-4°) have a smaller probability of capturing the actual outcome than less precise forecasts (e.g., a temperature increase of 2-6°). Nevertheless, people often trust precise forecasts more than vague forecasts, perhaps because precision is associated with knowledge and expertise. In five experiments, we ask whether people expect highly confident forecasts to be associated with wider or narrower outcome ranges than less confident forecasts (Experiments 1, 2, and 5), and, conversely, whether they expect precise forecasts to be issued with higher or lower confidence than vague forecasts (Experiments 3 and 4). The results revealed two distinct ways of thinking about confidence intervals, labeled distributional (wide intervals seen as more probable than narrow intervals) and associative (wide intervals seen as more uncertain than narrow intervals). Distributional responses occurred somewhat more often in within-subjects designs, where wide and narrow prediction intervals and high and low probability estimates can be directly compared, whereas separate evaluations (in between-subjects design) suggested associative responses to be slightly more frequent. These findings are relevant for experts communicating forecasts through confidence intervals.

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Section: Discussionmentioning

confidence: 99%

Section: Overprecision and The Preciseness Paradoxmentioning

confidence: 99%

Probabilities Associated with Precise and Vague Forecasts

Løhre

Teigen

2017

Behavioral Decision Making

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“…A better approach to the study of overprecision asks people to specify a confidence interval around their estimates, such as a confidence interval that is wide enough that there is a 90% chance the right answer is inside it and only a 10% chance the right answer is outside it (Alpert & Raiffa, 1982). Results routinely find that hit rates inside 90% confidence intervals are below 50%, implying that people set their ranges too precisely-acting as if they are inappropriately confident their beliefs are accurate (Moore, Tenney, & Haran, 2016). This effect even holds across levels of expertise (Atir, Rosenzweig, & Dunning, 2015;McKenzie, Liersch, & Yaniv, 2008).…”

Section: Overprecisionmentioning

confidence: 99%

The three faces of overconfidence

Moore

Schatz

2017

Social & Personality Psych

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119

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Overconfidence has been studied in 3 distinct ways. Overestimation is thinking that you are better than you are. Overplacement is the exaggerated belief that you are better than others. Overprecision is the excessive faith that you know the truth. These 3 forms of overconfidence manifest themselves under different conditions, have different causes, and have widely varying consequences. It is a mistake to treat them as if they were the same or to assume that they have the same psychological origins. | INTRODUCTIONResearch on overconfidence employs a diversity of approaches and measures as if they all tap the same underlying psychological construct. This is an error. Overconfidence is not a single unitary construct. In this paper, we note the inconsistent results between different approaches to the study of overconfidence. These inconsistencies are further muddled by multiple usages of the term "overconfidence" in the vernacular. In the interests of clarity, we begin this review with a few definitions, beginning with the definition of overconfidence: greater confidence than reality justifies. Measuring overconfidence necessitates a comparison between beliefs and reality. We then consider each of the three types of overconfidence in turn: overestimation, overplacement, and overprecision. Given that overconfident beliefs are (by definition) incorrect, we then confront the question:Can overconfidence be useful? Finally, we consider one way in which researchers assume there is psychological coherence to overconfidence: stable individual differences. Here again, we will question the solidity of the phenomenon and argue that overconfidence does not appear to be a stable difference between people. Our review highlights the diversity and inconsistency in manifestations of overconfidence.There is a great deal of work on confidence, self-efficacy, self-esteem, optimism, and self-enhancement that includes no measure of overconfidence because there is no accuracy benchmark against which beliefs can be compared. The research that does compare beliefs with reality to assess overconfidence has usually employed one of three measures: overestimation, overplacement, or overprecision. Overestimation is thinking that you are better than you are. Donald Trump's claim to be worth $10 billion (White, 2016) represented an overestimate relative to a more credible estimate of $4.5 billion by Forbes magazine (Peterson-Withorn, 2016). A second measure of overconfidence is overplacement: the exaggerated belief that you are better than others. When Trump claimed to have achieved the largest electoral victory since Ronald Reagan (Cummings, 2017), he was overplacing himself relative to other presidents. A third form of overconfidence is overprecision: being too sure you know the truth. Trump displays overprecision when he claims certainty about views, which are contradicted by reality. . Does the better-than-average effect show that people are overconfident?: Two experiments.

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“…In evaluating the performance of probability forecasters, we assess their accuracy and their confidence. While alternative definitions of accuracy exist in the literature on evaluating subjective probabilities (e.g., Lichtenstein, Fischhoff, & Phillips, ; Moore, Tenney, & Haran, ; Yaniv & Foster, ), we will hereafter consider accuracy to be a measure of the degree of correspondence between the participants' predictions (which are the probabilities of event occurrences) and the observed outcomes. The average Brier score (Brier, ) is used to evaluate and compare participants' long‐term accuracy.…”

Section: Performance Measures and The Value Of Discussionmentioning

confidence: 99%

The Value of Performance Weights and Discussion in Aggregated Expert Judgments

et al. 2018

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In risky situations characterized by imminent decisions, scarce resources, and insufficient data, policymakers rely on experts to estimate model parameters and their associated uncertainties. Different elicitation and aggregation methods can vary substantially in their efficacy and robustness. While it is generally agreed that biases in expert judgments can be mitigated using structured elicitations involving groups rather than individuals, there is still some disagreement about how to best elicit and aggregate judgments. This mostly concerns the merits of using performance-based weighting schemes to combine judgments of different individuals (rather than assigning equal weights to individual experts), and the way that interaction between experts should be handled. This article aims to contribute to, and complement, the ongoing discussion on these topics.

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Overprecision in Judgment

Cited by 100 publications

References 157 publications

Probabilities Associated with Precise and Vague Forecasts

Probabilities Associated with Precise and Vague Forecasts

The three faces of overconfidence

The Value of Performance Weights and Discussion in Aggregated Expert Judgments

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