As the old saying goes, “Two heads are better than one.” This is the idea behind research currently being conducted at the Human Computation Institute (HCI) and Cornell University, but instead of putting two human brains together, they’re looking to team up a human with a computer.

Their article, published in Science , describes the potential for human computation — a technique in which a machine outsources some of its jobs to humans. The research team, led by HCI Director Dr. Pietro Michelucci, believe human computation can be used to combat our greatest problems, like climate change and geopolitical conflict.

“Human computation is the secret sauce that makes crowdsourcing work,” Michelucci said in a press release video. “It’s an offshoot of artificial intelligence, which is about making machines smarter. Human computation puts a special twist on this by cheating. Instead of making smarter machines, we let machines do the things they do best like counting and keeping track of things, and give the really hard jobs to people.”

Currently, human computation is used for well-known projects like Wikipedia, and smaller projects like EyeWire, which outsourced thousands of online images to 165,000 volunteers, who will help build a complete map of human retinal neurons. Another project called YardMap is “ a citizen science project designed to cultivate a richer understanding of bird habitat, for both professional scientists and people concerned with their local environments.” It lets people interact and build on another person’s work, effectively building a community of helpers.

However, Michelucci says human computation as we know it today is kind of stuck in its place. Most human computation projects involve simple microtasks — jobs that are easy for a human to complete but hard for a computer. “The computer breaks down a big problem into tiny pieces and then sends out these little microtasks, which are all basically the same, and then puts the pieces back together,” he said. In EyeWire, for example, the big problem is mapping human retinal neurons. So, broken down into a game, players slowly build 3D puzzles of neural segments, which will be added later on to complete the map. Yet, to solve bigger, world-threatening issues, Michelucci believe we need new approaches.

These problems are diverse, and finding a solution alone or in small groups could cause unforeseen side effects that could otherwise be avoided through more widespread conversation. When combating global warming, for example, an unforeseen side effect could be the extinction of polar bears. Therefore, Michelucci said we need to create “information ecosystems that can help billions of people reason together effectively, and build models of the problem space that allow prospective solutions to be evaluated in theory before they’re implemented in practice.”

To do this, we need to design workflows that help us solve these problems far better than we would be able to right now. This workflow would be similar to the human brain, Michelucci said, in that each person or computer is a neuron. Studies would also help in developing these systems, since they would compare different approaches to find which ones work best.

That said, as “wicked” problems like climate change, global warming, and war ravage our world, and leaders struggle to come up with solutions, maybe putting our collective minds together is the answer.

Source: Michelucci P, Dickinson J. The power of crowds: Combining humans and machines can help tackle increasingly hard problems. Science. 2015.