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AI Can Now Self-Reproduce—Should Humans Be Worried?
AI Self-Reproduce Cover.jpg
Information
Guest(s) Eric Weinstein
Length 00:05:30
Release Date 22 May 2017
Links
YouTube Watch
Portal Blog Read
All Appearances


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AI Can Now Self-Reproduce—Should Humans Be Worried? was a video with Eric Weinstein on Big Think.

Description

Those among us who fear world domination at the metallic hands of super-intelligent AI have gotten a few steps ahead of themselves. We might actually be outsmarted first by fairly dumb AI, says Eric Weinstein. Humans rarely create products with a reproductive system—you never have to worry about waking up one morning to see that your car has spawned a new car on the driveway (and if it did: cha-ching!), but artificial intelligence has the capability to respond to selective pressures, to self-replicate and spawn daughter programs that we may not easily be able to terminate. Furthermore, there are examples in nature of organisms without brains parasitizing more complex and intelligent organisms, like the mirror orchid. Rather than spend its energy producing costly nectar as a lure, it merely fools the bee into mating with its lower petal through pattern imitation: this orchid hijacks the bee's brain to meet its own agenda. Weinstein believes all the elements necessary for AI programs to parasitize humans and have us serve its needs already exists, and although it may be a "crazy-sounding future problem which no humans have ever encountered," Weinstein thinks it would be wise to devote energy to these possibilities that are not as often in the limelight.


ERIC WEINSTEIN:

Eric Weinstein is an American mathematician and economist. He earned his Ph.D in mathematical physics from Harvard University in 1992, is a research fellow at the Mathematical Institute of Oxford University, and is a managing director of Thiel Capital in San Francisco. He has published works and is an expert speaker on a range of topics including economics, immigration, elite labor, mitigating financial risk and incentivizing of creative risks in the hard sciences.

Transcript

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