Aggregated knowledge from a small number of debates outperforms the wisdom of large crowds
| Autor: | G. D. Garbulsky, Mariano Sigman, Joaquin Navajas, Bahador Bahrami, Tamara Niella |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
FOS: Computer and information sciences
Physics - Physics and Society Social Psychology media_common.quotation_subject Judgement Decision Making FOS: Physical sciences Experimental and Cognitive Psychology Physics and Society (physics.soc-ph) 050105 experimental psychology deliberation 03 medical and health sciences Behavioral Neuroscience 0302 clinical medicine Crowds Collective wisdom 0501 psychology and cognitive sciences media_common Financial forecasting Social influence Social and Information Networks (cs.SI) wisdom of crowds Small number 05 social sciences Otras Ciencias Naturales y Exactas Computer Science - Social and Information Networks Deliberation Data science Psychology 030217 neurology & neurosurgery social influence CIENCIAS NATURALES Y EXACTAS Diversity (business) |
| Popis: | The aggregation of many independent estimates can outperform the most accurate individual judgement 1-3. This centenarian finding 1,2, popularly known as the 'wisdom of crowds' 3, has been applied to problems ranging from the diagnosis of cancer 4 to financial forecasting 5. It is widely believed that social influence undermines collective wisdom by reducing the diversity of opinions within the crowd. Here, we show that if a large crowd is structured in small independent groups, deliberation and social influence within groups improve the crowd's collective accuracy. We asked a live crowd (N = 5,180) to respond to general-knowledge questions (for example, "What is the height of the Eiffel Tower?"). Participants first answered individually, then deliberated and made consensus decisions in groups of five, and finally provided revised individual estimates. We found that averaging consensus decisions was substantially more accurate than aggregating the initial independent opinions. Remarkably, combining as few as four consensus choices outperformed the wisdom of thousands of individuals. Fil: Navajas Ahumada, Joaquin Mariano. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Torcuato Di Tella; Argentina Fil: Niella, Tamara. State University of Oregon; Estados Unidos. Universidad Torcuato Di Tella; Argentina Fil: Garbulsky, Gerry. TED; Argentina Fil: Bahrami, Bahador. University College London; Estados Unidos. Universidad de Múnich; Alemania Fil: Sigman, Mariano. Universidad Torcuato Di Tella; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina |
| Databáze: | OpenAIRE |
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