The wisdom of the inner crowd in three large natural experiments

  title={The wisdom of the inner crowd in three large natural experiments},
  author={Dennie van Dolder and Martijn J. van den Assem},
  journal={Nature Human Behaviour},
The quality of decisions depends on the accuracy of estimates of relevant quantities. According to the wisdom of crowds principle, accurate estimates can be obtained by combining the judgements of different individuals1,2. This principle has been successfully applied to improve, for example, economic forecasts3–5, medical judgements6–9 and meteorological predictions10–13. Unfortunately, there are many situations in which it is infeasible to collect judgements of others. Recent research proposes… 
Extending the wisdom of crowds: How to harness the wisdom of the inner crowd
The wisdom-of-crowds effect describes how aggregating judgments of multiple individuals can lead to a more accurate judgment than that of the typical—or even best—individual. We investigated when
How the “wisdom of the inner crowd” can boost accuracy of confidence judgments.
Simulation and analytical results show that irrespective of the type of item, averaging consistently improves confidence judgments, but maximizing is risky: It outperformed averaging only once items were answered correctly 60% of the time or more—a result that has not been established in prior work.
How the wisdom of crowds, and of the crowd within, are affected by expertise
The data suggest that experts give almost the same answer every time they are asked and so they should consult the outer crowd rather than solicit multiple estimates from themselves.
The Psychology of Second Guesses: Implications for the Wisdom of the Inner Crowd
Prior research suggests that averaging two guesses from the same person can improve quantitative judgments, a phenomenon known as the “wisdom of the inner crowd.” In this article, we find that this
The Psychology of Second Guesses: Implications for the Wisdom of the Inner Crowd
It is found that asking people to explicitly indicate whether their first Guess was too high or too low before making their second guess made people more likely to provide a second guess that was more extreme than their first guess.
Robust Opinion Aggregation and its Dynamics
It is shown that under this general model, it is still possible to link the long-run behavior of the opinions to the structure of the underlying network and to provide sufficient conditions for convergence and consensus and to offer some bounds on the rate of convergence.
When experts make inconsistent decisions
Cases on which diagnosticians strongly agree are associated with highly confident initial decisions that were unlikely to change---independent of whether the experts' consensus decision was correct or wrong.
Measuring Dynamics in Evacuation Behaviour with Deep Learning
This study proposes a framework of deep learning to extract a key dynamical parameter that drives crowd evacuation behaviour in a cellular automaton (CA) model, and provides a platform to quantitatively measure the optimal strategy in evacuation.
Social Media Sentiments and Firm Value
ABSTRACT This paper examines the link between social media sentiments and firm value. Using a sample of Fortune 500 firms from 2010 to 2017, we find that positive social media sentiments increase


How social influence can undermine the wisdom of crowd effect
This work demonstrates by experimental evidence that even mild social influence can undermine the wisdom of crowd effect in simple estimation tasks.
Measuring the Crowd Within
Measuring the crowd within: probabilistic representations within individuals finds any benefit of averaging two responses from one person would yield support for this hypothesis, which is consistent with such models that responses of many people are distributed probabilistically.
The Wisdom of Many in One Mind
The conditions under which dialectical bootstrapping fosters accuracy are derived and an empirical demonstration that its benefits go beyond reliability gains is provided.
Two Reasons to Make Aggregated Probability Forecasts More Extreme
It is shown that the same transformation function can approximately eliminate both distorting effects with different parameters for the mean and the median, and how, in principle, use of the median can help distinguish the two effects.
Measuring the crowd within again: a pre-registered replication study
A high-powered, pre-registered replication study of the crowd within effect, both when the second guess was made immediately after the first guess, as well as when it was made 3 weeks later.
Intuitions About Combining Opinions: Misappreciation of the Averaging Principle
It is described how people may face few opportunities to learn the benefits of averaging and how misappreciating averaging contributes to poor intuitive strategies for combining estimates.
Smaller is better (when sampling from the crowd within): Low memory-span individuals benefit more from multiple opportunities for estimation.
The results demonstrate a rare circumstance in which lower memory span confers a relative advantage on a cognitive task by showing that averaging 2 guesses from lower span individuals is more beneficial than averaging two guesses from higher span individuals.
The effects of averaging subjective probability estimates between and within judges.
Two studies test 3 predictions regarding averaging that follow from theorems based on a cognitive model of the judges and idealizations of the judgment situation, showing the extent to which they hold as the information conditions depart from the ideal and as J increases.
Are We Wise About the Wisdom of Crowds? The Use of Group Judgments in Belief Revision
Four studies examining intuitions about group wisdom and the informational influence of groups find that when provided advice, participants relied more on groups than individuals to update their beliefs, but were only modestly sensitive to group size.