Self-organized flexible leadership promotes collective intelligence in human groups

Area of Science:

• Behavioral Ecology
• Social Psychology
• Computational Social Science

Background:

• Collective intelligence enables groups to surpass individual decision-making capabilities.
• Mechanisms driving collective intelligence in natural systems remain largely unexplored.
• Understanding group dynamics is crucial for fields ranging from ecology to artificial intelligence.

Purpose of the Study:

• To investigate a novel mechanism for collective intelligence: self-organization based on information quality.
• To determine how individuals adjust their behavior in group decision-making based on personal information accuracy.
• To explore the flexible roles individuals adopt within a group based on information reliability.

Main Methods:

• Simulated predator detection experiments were conducted with human groups.
• Individual response times and personal information accuracy were continuously tracked.
• Analysis focused on how information quality influenced decision timing and collective accuracy.

Main Results:

• Individuals dynamically adjusted their response times according to the accuracy of their personal information.
• Those with accurate information decided quickly; those with inaccurate information waited to incorporate social cues.
• Delayed decisions increased the likelihood of changing initial judgments, thereby enhancing collective accuracy.

Conclusions:

• Groups exhibit self-organization based on member information accuracy, promoting collective intelligence.
• Individuals flexibly switch between leadership and followership roles depending on their information's quality.
• This adaptive self-organization is a key mechanism for improving group decision-making in natural environments.