Wisdom or Madness: Expert Data on Wisdom of Crowds

From structured expert judgment data with realizations it is concluded that (1) experts' Mean Absolute Percentage Errors are very fat tailed, making convergence problematic, (2) probabilistic proximity of experts' median forecasts to realizations are modestly dependent, whereas experts' abilities to catch realizations in their 90% bands are much less so, (3) expert agreement does not predict expert panel performance, (4) regarding the performance metrics Statistical Accuracy and Mean Absolute Percentage Errors, number of experts is helpful for the first, harmful for the second whereas dependence in placement of medians is harmful for the first, helpful for the second, and ( 5) following Jensen's inequality, averaging experts' median assessments is slightly better than choosing a random expert but (from a previous publication) much worse than the median of equally weighted or performance weighted combinations of experts' distributions, underscoring the importance of method of aggregation.Probabilistic crowds are wiser than point forecast crowds.

Authors

Institutions

Publication Details

Published
2025-01-01
DOI
https://doi.org/10.3850/978-981-94-3281-3_esrel-sra-e2025-p9059-cd
Primary Topic
Appreciative Inquiry and Organizational Change
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Wisdom or Madness: Expert Data on Wisdom of Crowds

Roger Cooke
Appreciative Inquiry and Organizational Change
article

Wisdom or Madness: Expert Data on Wisdom of Crowds

Roger Cooke
article en

Abstract

From structured expert judgment data with realizations it is concluded that (1) experts' Mean Absolute Percentage Errors are very fat tailed, making convergence problematic, (2) probabilistic proximity of experts' median forecasts to realizations are modestly dependent, whereas experts' abilities to catch realizations in their 90% bands are much less so, (3) expert agreement does not predict expert panel performance, (4) regarding the performance metrics Statistical Accuracy and Mean Absolute Percentage Errors, number of experts is helpful for the first, harmful for the second whereas dependence in placement of medians is harmful for the first, helpful for the second, and ( 5) following Jensen's inequality, averaging experts' median assessments is slightly better than choosing a random expert but (from a previous publication) much worse than the median of equally weighted or performance weighted combinations of experts' distributions, underscoring the importance of method of aggregation.Probabilistic crowds are wiser than point forecast crowds.

Delft University of Technology (NL)
Openalex Percentile: Top 67%
Appreciative Inquiry and Organizational Change
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Wisdom or Madness: Expert Data on Wisdom of Crowds — Roger Cooke · (2025) | TGRS Research Map | TGRS