Humans are by nature social beings, and for many of us, parts of our social lives play out online.

While we may be aware that the trails of our social media interactions — every post, purchase, “like” and shared pygmy goat video — are being aggregated into a trove of “big social data,” we may not know about the ways that information can be put to use.

For scientists like Brian Uzzi, access to big social data for computational social science research has the potential to provide deep insight into human behavior. The ability to examine a data set as large as an entire social network makes it possible to accurately predict how people will act in a given situation, creating a guide to better decision-making and opening the door to human-machine partnerships that can improve our lives in ways we haven’t yet imagined.

“People all over the world are sharing all this information,” says Uzzi, the Richard L. Thomas Professor of Leadership and Organizational Change and co-director of the Northwestern Institute on Complex Systems. The effectiveness of these masses of data hinges on how data logic and human cognition interact. “With computational social science, we are able to rank it, filter it and make it useful for a machine.”

Gaining a more nuanced understanding of the ways ideas diffuse through a population and how opinions change has great potential for business leaders across industries and functions. It turns out, others may influence us more than we realize.

“Until recently, we believed that each of us made our own decisions, and that our friends influenced us here or there, but not in a big way,” Uzzi says. “All the social media data we’ve collected shows that we are incredibly sensitive to what other people do. That’s often the thing that drives our behavior, rather than our own interests or desires or preferences.” Incorporating this kind of data into the development of human-machine partnerships has the potential to improve human decision-making on both societal and individual levels. Uzzi sees these partnerships as a way to optimize the best qualities of both humans and machines.

“Human beings have whole sets of cognitive biases that lead them to make irrational decisions,” Uzzi says. “The idea of hu-man-machine partnerships is that the machine can help you overcome these innate, hard-wired cognitive biases to make sure that you look at information from more perspectives. It also provides a feedback loop that allows you to learn where you might have taken oblivious missteps.”

For Uzzi, the real sweet spot in human-machine partnerships is figuring out how to meld the great qualities of human beings, like spontaneity and improvisation, with machines that do rule-bound work better than humans can.

“That would create a complementarity between the two that gives you more than either one could possibly give you on its own.”