Kate Crawford (previously) takes to the New York Times's editorial page to ask why rich white guys act like the big risk of machine-learning systems is that they'll evolve into Skynet-like apex-predators that subjugate the human race, when there are already rampant problems with machine learning: algorithmic racist sentencing, algorithmic, racist and sexist discrimination, algorithmic harassment, algorithmic hiring bias, algorithmic terrorist watchlisting, algorithmic racist policing, and a host of other algorithmic cruelties and nonsense, each one imbued with unassailable objectivity thanks to its mathematical underpinnings.
Focusing our energies on hypothetical science fiction disasters from machine learning means taking the spotlight off of the real-world, here-and-now ways that software isn't just eating the world -- it's also shitting all over it.
While machine-learning technology can offer unexpected insights and new forms of convenience, we must address the current implications for communities that have less power, for those who aren’t dominant in elite Silicon Valley circles.
Currently the loudest voices debating the potential dangers of superintelligence are affluent white men, and, perhaps for them, the biggest threat is the rise of an artificially intelligent apex predator.
But for those who already face marginalization or bias, the threats are here.
Artificial Intelligence’s White Guy Problem
[Kate Crawford/NY Times]
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