Human-machine superintelligence pegged as key to solving global problems

Ravi Mandalia at Dispatch Tribunal: “Global complex problems such as climate change and geopolitical conflicts need a new approach if we want to solve them and researchers have suggested that human-machine super intelligence could be the key.

These so called ‘wicked’ problems are some of the most dire ones that need our immediate attention and researchers from the Human Computation Institute (HCI) and Cornell University have presented their new vision of human computation that could help solve these problems in an article published in the journal Science.

Scientists behind the article have cited how power of human computation has helped push the traditional limits to new heights – something that was not achievable until now. Humans are still ahead of machines at great many things – cognitive abilities is one the key areas – but if their powers are combined with those of machines, the result would be multidimensional collaborative networks that achieve what traditional problem-solving cannot.

Researchers have already proved that micro-tasking has helped with some complex problems including build the world’s most complete map of human retinal neurons; however, this approach isn’t always viable to solve much more complex problems of today and entirely new and innovative approach is required 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).

Recently developed human computation technologies that provide real-time access to crowd-based inputs could enable creation of more flexible collaborative environments and such setups are more apt for addressing the most challenging issues.

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

“By sharing and observing practices in a map-based social network, people can begin to relate their individual efforts to the global conservation potential of living and working landscapes,” says Janis Dickinson, Professor and Director of Citizen Science at the Cornell Lab of Ornithology.

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 how we manage residential landscapes.

HCI has recently set out to use crowd-power to accelerate Cornell-based Alzheimer’s disease research. 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….(More)”