The method used of assessing collective intelligence by Anita Woolley only worked on small groups. The largest group was around 40 people. Larger groups would likely require a different methodology.

Small Groups in Anita Woolley's Test of Collective Intelligence

To test a froups collective intelligence, it required and intervention where a group was formed and asked to do something they would typically not do. It did not reflect how a group naturally acted perfroming a task they needed or intended to do. 

Intervention in Anita Woolley's Test of Collective Intelligence

San Jose State University

Anita Woolley, Thomas Malone, and their team developed a test for measuring group intelligence. The group intelligence test involved selecting a diverse set of tasks specifically designed for group collaboration. The approach involved choosing tasks that aligned with key categories in social psychologist Joseph McGrath's framework for group tasks. A wide array of tasks that groups encounter in real-world scenarios were represented. To ensure a balanced representation of participants, the study recruited groups from the general public through various channels, including public websites like Craigslist, rather than relying solely on university students. This approach aimed to provide a broader cross-section of the community and maintain similarity to the general U.S. population's intelligence distribution as determined by short individual intelligence tests.

Anita Woolley's Group Intelligence Test

Malone, Thomas W. 2018. Superminds: The Surprising Power of People and Computers Thinking Together. Little, Brown Spark.

https://cci.mit.edu/superminds-by-thomas-w-malone/

Superminds: The Surprising Power of People and Computers Thinking Together

Anita Woolley and their team found that groups, like individuals, possess a single statistical factor, akin to individual intelligence, which predicts their performance across various tasks. Termed collective intelligence, this group factor mirrors the concept of general intelligence found in individuals, shedding light on what makes groups effective across tasks. In initial studies, it was assessed whether collective intelligence could predict performance on tasks not included in its calculation. Groups were assigned complex tasks requiring a combination of abilities, like playing checkers against a computer or constructing structures with building blocks under specific rules. Results revealed that collective intelligence scores strongly predicted performance on these complex tasks, surpassing the predictive power of either the group members' average or maximum individual intelligence.

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