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Microsoft publishes the science of human-machine collaboration
Microsoft researchers recently published one of the most exciting advances in AI this year, IMO.
Microsoft researchers recently published one of the most exciting advances in AI this year, IMO. I’m not referring to the company’s announcements regarding huge new NLP neural networks using semi-supervised learning, or the company’s new supercomputer, or the new tools for fairness in AI, although these are all impressive and useful. The new research is in human-machine collaboration.
Human-machine collaboration has been a hot area for years but, outside of social robots, it’s been more the domain of non-technical people than technical people. There simply hasn’t been much in the way of a scientific methodology for engineers to take a hybrid approach. While machine learning engineers focus on the frontier of mathematical and computational capabilities, in the absence of methods for human-machine team work, technology has generally marched on in isolation of the human factors. So while we can talk about “augmentation” of human skills, the reality is often different; shitty automation, sub-optimal task design, algorithmic aversion, hidden bias.
New research changes this. Now we have the math to train models in hybrid human-machine systems, taking into account what it means to consult a human.
Here it is: (or one sample of it)