Human-Machine Superintelligence Can Solve the World's Most Dire Problems

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The combination of human and computer intelligence might be just what we need to solve the "wicked" problems of the world, such as climate change and geopolitical conflict, say researchers from the Human Computation Institute (HCI) and Cornell University.

In an article published in the journal Science, the authors present a new vision of human computation (the science of crowd-powered systems), which pushes beyond traditional limits, and takes on hard problems that until recently have remained out of reach.

Humans surpass machines at many things, ranging from simple pattern recognition to creative abstraction. With the help of computers, these cognitive abilities can be effectively combined into multidimensional collaborative networks that achieve what traditional problem-solving cannot.

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, say the authors. A radically new approach is needed to solve "wicked problems" - those that involve many interacting systems that are constantly changing, and whose solutions have unforeseen consequences (e.g., corruption resulting from financial aid given in response to a natural disaster).

New human computation technologies can help. Recent techniques provide real-time access to crowd-based inputs, where individual contributions can be processed by a computer and sent to the next person for improvement or analysis of a different kind. This enables the construction of more flexible collaborative environments that can better address the most challenging issues.

This idea is already taking shape in several human computation projects, including YardMap.org, which was launched by the Cornell in 2012 to map global conservation efforts one parcel at a time.

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