This was the main outcome paper of the big collective intelligence study I conducted during my PostDoc at MIT.


Intelligence is a complicated topic but in the sciences it means a generalized problem solving capacity that is inherent to a person and somewhat stable over time. The underlying observation is that people that are good at one kind of mental task (e.g. math) tend to be good at other kinds of mental tasks (e.g. memorization). While this seems obvious these days it wasn’t always the case. It was a valid hypothesis that our brain could be specialized to one kind of task at the expense of being able to excel at others.

Based on the observation of correlated performances scientists can do a principal component analysis. The first factor accounts for a large chunk of the variance across different human performances. This first factor is referred to as the g-factor or the general factor and is what IQ tests usually measure.

Collective Intelligence

In the original paper by Woolley et al that was published in Science the question was posed: “Does a similar factor emerge when groups of people solve different kinds of tasks?” As it turns out there does. Teams were given different kinds of tasks, their performances were scored and a principal component analysis was done. And in the same way as for individuals one main factor emerged that described a similarly large portion of the variance. This factor was called c.

The obvious question that follows is: “What factors of individuals or group composition drive c?” As it turns out, number of women in the group was a good predictor of c. A statistical analysis revealed that the underlying ability that was driving this performance was a theory-of-mind or mentalizing ability on which women, on average score higher.

Collective Intelligence in online Groups

This brings us to our study. The theory-of-mind ability measures the ability to correctly perceive the mood or mental state of other persons. The tests that measure this ability rely on guessing the mood from a picture of just the eyes. The question we were looking to answer in this study was: Is this ability equally important in an online setting where the communication and interaction is purely based on chat. Or put more bluntly: “Do social skills matter for team performance in purely online settings?”

And the data interestingly shows: Yes. theory-of-mind skills predict collective intelligence even in online teams. The implications are interesting. Even when working remotely with other team members, even when all you use to communicate is chat, your ability to reason about the mental state of others is still an important predictor of general team performance.


Recent research with face-to-face groups found that a measure of general group effectiveness (called “collective intelligence”) predicted a group’s performance on a wide range of different tasks. The same research also found that collective intelligence was correlated with the individual group members’ ability to reason about the mental states of others (an ability called “Theory of Mind” or “ToM”). Since ToM was measured in this work by a test that requires participants to “read” the mental states of others from looking at their eyes (the “Reading the Mind in the Eyes” test), it is uncertain whether the same results would emerge in online groups where these visual cues are not available. Here we find that: (1) a collective intelligence factor characterizes group performance approximately as well for online groups as for face-to-face groups; and (2) surprisingly, the ToM measure is equally predictive of collective intelligence in both face-to-face and online groups, even though the online groups communicate only via text and never see each other at all. This provides strong evidence that ToM abilities are just as important to group performance in online environments with limited nonverbal cues as they are face-to-face. It also suggests that the Reading the Mind in the Eyes test measures a deeper, domain-independent aspect of social reasoning, not merely the ability to recognize facial expressions of mental states.


Engel D, Woolley AW, Jing LX, Chabris CF, Malone TW (2014) Reading the Mind in the Eyes or Reading between the Lines? Theory of Mind Predicts Collective Intelligence Equally Well Online and Face-To-Face. PLoS ONE 9(12): e115212.

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