Human-machine super-intelligence may tackle world's problems

The combination of human and computer intelligence may solve the world's most dire problems such as climate change and geopolitical conflicts, according to a new study.
Researchers from the Human Computation Institute (HCI) and Cornell University in New York 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.

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, researchers said.
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, they said.
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.

YardMap allows participants to interact and build on each other's work - something that crowd-sourcing alone cannot achieve.
The project serves as an important model for how such bottom-up, socially networked systems can bring about scalable changes how we manage residential landscapes.
HCI has recently set out to use crowd-power to accelerate Cornell-based Alzheimer's disease research. WeCureAlz.Com combines two successful micro-tasking 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 be pinpointed in the brain by a modified version of the EyeWire system, which has analysed thousands of images online to help build the world's most complete map of human retinal neurons.

"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 HCI director and lead author, Dr Pietro Michelucci.
"This gives an opportunity for anyone, including the tech-savvy generation of caregivers and early stage AD patients, to take the matter into their own hands," said Michelucci.
The research was published in the journal Science.