The human/machine partnership solving Alzheimer's disease 📹

How do we combine the best of humans and machines in Stall Catchers - the game crowdsourcing Alzheimer's disease? It took lots of exploration of the existing machine learning algorithms, calibration of crowd wisdom algorithms, and combination of the two in the best possible way.

Learn all about it in this great talk by Pietro Michelucci, recently delivered at Microsoft Research.

Our greatest opportunity for problem-solving comes not from humans alone or from Artificial Intelligence (AI) alone, but by combining them in distributed networks. Leveraging the complementary abilities of humans and machines allows us to create unprecedented capabilities today. The EyesOnALZ citizen science project accelerates Alzheimer’s disease research by strategically combining machine learning and Crowd AI (human computation) methods. The specific human/machine partnerships that enabled this capability have co-evolved with algorithmic advancements and computing platforms like Azure.



Egle (seplute)

Citizen Science Coordinator at the Human Computation Institute, EyesOnALZ/Stall Catchers Community Manager. Giving science back to the people!

Lithuania

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