Cambridge Analytica pioneered the use of deep learning by scanning the Facebook and Twitter social graphs to indentify voters' political affiliations.
But if you're Elon Musk, that's okay: Nobody in was expecting a Nazi revival inright. I'm biting my tongue and trying not to take sides here: Now — onward to the free printables. While its adherents tend to be vehement atheists, they can't quite escape from the history that gave rise to our current western civilization.
Advertising tries to maximize its hold on the attention of the minds behind each human eyeball: What lessons from the history of the company can we draw that tell us about the likely behaviour of the type of artificial intelligence we are all interested in today.
The Brexit upset was largely the result of a protest vote against the British political establishment; the election of Donald Trump likewise, with a side-order of racism on top. I'm a cat person. With addiction-seeking deep learning and neural-network generated images, it is in principle possible to feed you an endlessly escallating payload of arousal-maximizing inputs.
Unfortunately the term 'cyberwar' seems to have stuck. Of course, there were plenty of other things happening between the sixteenth and twenty-first centuries that changed the shape of the world we live in.
The ad-supported web that we live with today wasn't inevitable. The tools developed by web advertisers to sell products have now been weaponized for political purposes, and the amount of personal information about our affiliations that we expose on social media makes us vulnerable.
I don't see much evidence for human-like, self-directed artificial intelligences coming along any time now, and a fair bit of evidence that nobody except some freaks in university cognitive science departments even want it. That's an example of human-programmer-induced bias. Corporations generally pursue their instrumental goals—notably maximizing revenue—as a side-effect of the pursuit of their overt goal.
What happens when we get pervasive social networks with learned biases against, say, feminism or Islam or melanin.
Let me give you four examples—of new types of AI applications—that are going to warp our societies even worse than the old slow AIs of yore have done.
Fear of loss of social status and privilege is a powerful stimulus, and fear and xenophobia are useful tools for attracting eyeballs. We humans are living in a world shaped by the desires and needs of AIs, forced to live on their terms, and we are taught that we are valuable only insofar as we contribute to the rule of the machines.
For example, the reforms of the British railway network in the s dismembered many branch services and coincided with a surge in road building and automobile sales. Apple have put a lot of effort into making realtime face recognition work with the iPhone X.
Finally, I'd like to raise a really hair-raising spectre that goes well beyond the use of deep learning and targeted propaganda in cyberwar. Go back to the s and cars didn't come with seat belts as standard.
Don't worry, Cambridge Analytica can work them out with Add a service that can identify peoples affiliation and location, and you have the beginning of a flash mob app: I've skipped the whole of the Enlightenment and the age of revolutions. What we're getting, instead, is self-optimizing tools that defy human comprehension but are not, in fact, any more like our kind of intelligence than a Boeing is like a seagull.
That meant that the tech industry's heady pace of development was the first testbed for treating corporate growth as the greatest virtue, built on the lie of the fiduciary duty to increase profit above all other considerations.
You Might Also Enjoy: The problem with corporations is that despite their overt goals—whether they make electric vehicles or beer or sell life insurance policies—they are all subject to instrumental convergence insofar as they all have a common implicit paperclip-maximizer goal: If you want to find someone you fell out of touch with thirty years ago, Facebook probably knows where they live, what their favourite colour is, what size shoes they wear, and what they said about you to your friends all those years ago that made you cut them off.
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