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July 28, 2019 02:48 pm PDT

"Intellectual Debt": It's bad enough when AI gets its predictions wrong, but it's potentially WORSE when AI gets it right

Jonathan Zittrain (previously) is consistently a source of interesting insights that often arrive years ahead of their wider acceptance in tech, law, ethics and culture (2008's The Future of the Internet (and how to stop it) is surprisingly relevant 11 years later); in a new long essay on Medium (shorter version in the New Yorker), Zittrain examines the perils of the "intellectual debt" that we incur when we allow machine learning systems that make predictions whose rationale we don't understand, because without an underlying theory of those predictions, we can't know their limitations.

Zittrain cites Arthur C Clarke's third law, that "any sufficiently advanced technology is indistinguishable from magic" as the core problem here: like a pulp sf novel where the descendants of the crew of a generation ship have forgotten that they're on a space-ship and have no idea where the controls are, the system works great so long as it doesn't bump into anything the automated systems can't handle, but when that (inevitably) happens, everybody dies when the ship flies itself into a star or a black hole or a meteor.

In other words, while machine learning presents lots of problems when it gets things wrong (say, when algorithmic bias enshrines and automates racism or other forms of discrimination) at least we know enough to be wary of the predictions produced by the system and to argue that they shouldn't be blindly followed: but if a system performs perfectly (and we don't know why), then we come to rely on it and forget about it and are blindsided when it goes wrong. Read the rest


Original Link: http://feeds.boingboing.net/~r/boingboing/iBag/~3/KRy-9k5afeo/orphans-of-the-sky.html

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