It’s not Skynet yet: in machine learning there’s still a role for humans

March 20, 2013

If you’ve ever seen any of The Terminator films, you’re familiar with Skynet, the self-aware computing system at odds with humanity. But, even though a perception persists that machines can increasingly solve complex problems and process large amounts of data on their own, machine learning experts say humans still play a very important role.

Human intervention is critical at multiple layers, from choosing the algorithms to apply to feature creation to crafting the entire structure within which a machine will learn, said Scott Brave, founder and CTO of Baynote, at GigaOM’s Structure: Data conference Wednesday.

Down the road, he said, there will be more opportunities for machine-man collaboration, as data scientists observe what the machines may be learning and then add new inputs and ideas to the system.

Still, Timothy Estes, founder and CEO of Digital Reasoning, pointed out that there are three key areas in which machine bests man — and, over time, they could give rise to some interesting social and cultural questions.

Humans will never be able to consume the sheer amount of data machines can process (unless it’s with some “Ray Kurzweil-style” man and machine merging). […]