Hamada, D., Nakayama, M. & Saiki, J. (2020)

Hamada, D., Nakayama, M(中山真孝). & Saiki, J. (2020) Wisdom of crowds and collective decision-making in a survival situation with complex information integration.
複雑な情報統合が必要なサバイバル状況における群衆の智慧と集団意思決定
Cognitive Research: Principles and Implications 5, 48.
https://doi.org/10.1186/s41235-020-00248-z

Background
The wisdom of crowds and collective decision-making are important tools for integrating information between individuals, which can exceed the capacity of individual judgments. They are based on different forms of information integration. The wisdom of crowds refers to the aggregation of many independent judgments without deliberation and consensus, while collective decision-making is aggregation with deliberation and consensus. Recent research has shown that collective decision-making outperforms the wisdom of crowds. Additionally, many studies have shown that metacognitive knowledge of subjective confidence is useful for improving aggregation performance. However, because most of these studies have employed relatively simple problems; for example, involving general knowledge and estimating values and quantities of objects, it remains unclear whether their findings can be generalized to real-life situations involving complex information integration. This study explores the performance and process of the wisdom of crowds and collective decision-making by applying the wisdom of crowds with weighted confidence to a survival situation task commonly used in studies of collective decision-making.

Results
The wisdom of crowds and collective decision-making outperformed individual judgment. However, collective decision-making did not outperform the wisdom of crowds. Contrary to previous studies, weighted confidence showed no advantage from comparison between confidence-weighted and non-weighted aggregations; a simulation analysis varying in group size and sensitivity of confidence weighting revealed interaction between group size and sensitivity of confidence weighting. This reveals that it is because of small group size and not the peculiarity of the survival task that results in no advantage of weighted confidence.

Conclusions
The study’s findings suggest that the wisdom of crowds could be applicable to complex problem-solving tasks, and interaction between group size and sensitivity of confidence weighting is important for confidence-weighted aggregation effects.

Significance Statement
The growth and prevalence of the Internet has resulted in an unprecedented system for gathering a large number of individual opinions. This system allows us to aggregate independent information and communicate face-to-face in online chat rooms. Correctly understanding and utilizing the wisdom of crowds, which aggregates information without consensus, and collective decision-making, which aggregates information with consensus, are urgent modern tasks to improve problem-solving efficiency, both in tasks with correct answers in open-ended tasks dependent on expert knowledge. Unlike most previous studies, which have addressed relatively simple problems, this study investigates the performance and process of the wisdom of crowds through a survival situation task involving complex information integration, and additionally compares with weighted subjective confidence and collective decision-making. The findings demonstrate the effective performance of the wisdom of crowds and collective decision-making and an effect of weighted confidence in interaction between group size and sensitivity of confidence weighting. This suggests that the wisdom of crowds can be applied and generalized to complex real-life situations. Weighted confidence based on large group size is compatible with a system that can collect a large number of opinions. Thus, this study expands the potential application of the wisdom of crowds to real-life problems involving complex information integration.

我々は日々意思決定を行なっています。個人が意思決定をするだけでなく、政府・会社組織といった集団での意思決定は日々の重要な位置を占めています。こういった意思決定では複雑な情報を統合した高度な判断が求められます。しかしながらこれまでの集団(合議)による意思決定の研究や「群衆の知恵」とよばれる複数の個人の判断を集約して意思決定を行うアルゴリズムの研究は、比較的単純な課題(例:牛の体重の見積もり)に限られていました。

本論文では、NASA月面サバイバル課題とよばれる複雑な意思決定課題を用いて、個人による意思決定と、集団による意思決定、集約アルゴリズムによる意思決定を比較しました。その結果、複雑な課題においても、個人による意思決定よりも集団による意思決定や集約アルゴリズムによる意思決定の方が、成績が良いことを示しました。また集約アルゴリズムがうまく働く条件もシミュレーションを用いて検討しました。

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