The MIT Media Lab’s Collective Learning group is no longer active. This site provides background on some of the people and projects that were associated with this research. The most current information about Media Lab research can be found in our Research section.
The Collective Learning group at the MIT Media Lab focuses on how teams, organizations, cities, and nations learn. Our research addresses both the study of knowledge and knowhow accumulated in social groups, as well as the creation of tools that democratize data analysis and facilitate collective learning.
Established as the Macro Connections group in 2010, it was renamed as Collective Learning in 2017. The group has pioneered the study of collective learning in economies—by advancing the theory and practice of economic complexity, and in history—by creating the largest structured dataset on biographical records. The work has also encompassed extensive mapping of urban perceptions and innovative tools for predicting urban change.
The group is renowned for the development of large data visualization engines, which are tools that algorithmically transform data into stories. These visualization engines receive millions of visitors every year and include:
- The Observatory of Economic Complexity
- DataUSA (with spinoff Datawheel)
- DataViva (with Datawheel)
- Pantheon
- PlacePulse
- Streetscore
- Streetchange