By linking the power of the human brain — the greatest complex information processor known to humanity — and the ever evolving power of supercomputers, humanity may just have a chance of solving some of its most dire problems.
There are some global problems which seem to plague humanity — wars, pandemic disease and most recently climate change, are all human issues we have yet to solve.
Referred to as “wicked” problems by researchers from the Human Computation Institute (HCI) and Cornell University, these issues involve many interacting systems that are constantly changing, and our solutions to them sometimes have unforeseen consequences (e.g., corruption resulting from financial aid given in response to a natural disaster).
In “The Power of Crowds,” a recent article published in the journal Science, the authors present a new vision of human computation (the science of crowd-powered systems), which combines the collective intelligence of humanity and supercharges it with rapidly evolving machine computing power to take on hard problems that until recently have remained out of reach.
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“Instead of trying to make smarter and smart machines, we let machines do the things they do best, like counting and keeping track of things, and then give the really hard jobs to people,” said HCI director and lead author, Dr. Pietro Michelucci.
“It turns out in many cases this is an effective combination,” he said.
According to the HCI, most of today's human computation systems rely on sending bite-sized 'micro-tasks' to many individuals and then stitching together the results. For example, 165,000 volunteers in EyeWire have analyzed thousands of images online to help build the world's most complete map of human retinal neurons.
This microtasking approach alone cannot address the tough challenges we face today, said the authors — a radically new approach is needed to solve "wicked problems."
“To attack these issues we need to build information ecosystem that can help millions of people reason together effectively and build models of the problem space that allow prospective solutions to be evaluated in theory, before they are implemented in practice,” said Michelucci. “In a sense we are trying to build distributed brain, in which each neuron is a person or computer.”
This idea is already taking shape in several human computation projects, including YardMap.org, which was launched by Cornell in 2012 to map global conservation efforts one parcel at a time.
YardMap allows participants to interact and build on each other's work — something that crowdsourcing alone cannot achieve. The project serves as an important model for how such bottom-up, socially networked systems can bring about scalable changes and how we manage residential landscapes.
The HCI has recently set out to use crowd-power to accelerate Cornell-based Alzheimer's disease research. WeCureAlz.com combines two successful microtasking systems into an interactive analytic pipeline that builds blood flow models of mouse brains. The stardust@home system, which was used to search for comet dust in one million images of aerogel, is being adapted to identify stalled blood vessels, which will then be pinpointed in the brain by a modified version of the EyeWire system.
"By enabling members of the general public to play some simple online game, we expect to reduce the time to treatment discovery from decades to just a few years," said Michelucci. “Human computation and machine intelligence may end up being mutual catalysts, either way I don't see machine intelligence surpassing human intelligence in the near future, but putting the two together could produce something that is more than the sum of its parts.”
