Technology versus Humanity

“And what about experts in neuroethics, psychology, law? Musk says it’s just “an engineering problem. … If we can just use engineering to get neurons to talk to computers, we’ll have done our job, and machine learning can do much of the rest.””

Elon Musk wants to enhance us as superhuman cyborgs to deal with superintelligent AI | KurzweilAI
http://www.kurzweilai.net/elon-musk-wants-to-enhance-us-as-superhuman-cyborgs-to-deal-with-superintelligent-ai
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“Matt McMullen says he’s helping the socially isolated, but once it becomes possible for a man to own a companion whose sole reason for existing is to give him pleasure, without the inconvenience of its own ambitions and needs, menstrual cycles and jealous passions, bathroom habits and in-laws, he may turn away from human relationships altogether.”

The race to build the world’s first sex robot
http://www.theguardian.com/technology/2017/apr/27/race-to-build-world-first-sex-robot
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“I will extend that further to claim that the only way to get a very human-like thought process is to run the computation on very human-like wet tissue. That also means that very big, complex artificial intelligences run on dry silicon will produce big, complex, unhuman-like minds. If it would be possible to build artificial wet brains using human-like grown neurons, my prediction is that their thought will be more similar to ours. The benefits of such a wet brain are proportional to how similar we make the substrate. The costs of creating wetware is huge and the closer that tissue is to human brain tissue, the more cost-efficient it is to just make a human. After all, making a human is something we can do in nine months.”

The Myth of a Superhuman AI – Backchannel
https://backchannel.com/the-myth-of-a-superhuman-ai-59282b686c62
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“This raises mind-boggling questions. As the technology advances, we might soon cross some threshold beyond which using AI requires a leap of faith. Sure, we humans can’t always truly explain our thought processes either—but we find ways to intuitively trust and gauge people. Will that also be possible with machines that think and make decisions differently from the way a human would? We’ve never before built machines that operate in ways their creators don’t understand. How well can we expect to communicate—and get along with—intelligent machines that could be unpredictable and inscrutable? These questions took me on a journey to the bleeding edge of research on AI algorithms, from Google to Apple and many places in between, including a meeting with one of the great philosophers of our time.”

There’s a big problem with AI: even its creators can’t explain how it works
https://www.technologyreview.com/s/604087/the-dark-secret-at-the-heart-of-ai/
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“Blue-collar workers—forget about it. The robots will kill off the positions of half a million oil-rig hands, up to half the industry’s workforce around the world, along with hundreds of thousands of warehouse employees, Amazon-ized by automated forklifts and other machines. Then there are the drivers—the navigators of taxis and long-haul trucks, who make up some 17% of the adult US work force, adding up to about 7 million people, to be replaced by robot cars if competition from Uber’s roster of of 1.5 million drivers doesn’t put them out of business first. Fast-food workers—the hard-working teens, first-generation immigrants, and return-to-work moms who are the bedrock of burger joints everywhere—are also on the firing line as ordering kiosks begin to take the place of human cashiers”

No one is prepared to stop the robot onslaught. So what will we do when it arrives?
https://qz.com/940977/no-one-is-prepared-to-stop-the-robot-onslaught-so-what-will-we-do-when-it-arrives/
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