TED | Machine intelligence makes human morals more important

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Video 1: On Machine Intelligence I
So, I started my first job as a computer programmer in my very first year of college – basically, as a teenager.
Soon after I started working, writing software in a company,
a manager who worked at the company came down to where I was,
and he whispered to me, “Can he tell if I’m lying?”
There was nobody else in the room.
“Can who tell if you’re lying? And why are we whispering?”
The manager pointed at the computer in the room. “Can he tell if I’m lying?”
Well, that manager was having an affair with the receptionist.
(Laughter)
And I was still a teenager.
So I whisper-shouted back to him, “Yes, the computer can tell if you’re lying.”
(Laughter)
Well, I laughed, but actually, the laugh’s on me.
Nowadays, there are computational systems that can suss out emotional states and even lying from processing human faces.
Advertisers and even governments are very interested.
I had become a computer programmer because I was one of those kids crazy about math and science.
But somewhere along the line I’d learned about nuclear weapons, and I’d gotten really concerned with the ethics of science. I was troubled.
However, because of family circumstances, I also needed to start working as soon as possible.
So I thought to myself, hey, let me pick a technical field where I can get a job easily and where I don’t have to deal with any troublesome questions of ethics.
So I picked computers.
(Laughter)
Well, ha, ha, ha! All the laughs are on me.
Nowadays, computer scientists are building platforms that control what a billion people see every day.
They’re developing cars that could decide who to run over.
They’re even building machines, weapons, that might kill human beings in war.
It’s ethics all the way down.

Video 2： On Machine Intelligence II
Machine intelligence is here.
We’re now using computation to make all sort of decisions, but also new kinds of decisions.
We’re asking questions to computation that have no single right answers, that are subjective and open-ended and value-laden.
We’re asking questions like, “Who should the company hire?”
“Which update from which friend should you be shown?”
“Which convict is more likely to reoffend?”
“Which news item or movie should be recommended to people?”
Look, yes, we’ve been using computers for a while, but this is different.
This is a historical twist, because we cannot anchor computation for such subjective decisions the way we can anchor computation for flying airplanes, building bridges, going to the moon.
Are airplanes safer?
Did the bridge sway and fall?
There, we have agreed-upon, fairly clear benchmarks, and we have laws of nature to guide us.
We have no such anchors and benchmarks for decisions in messy human affairs.
To make things more complicated, our software is getting more powerful, but it’s also getting less transparent and more complex.
Recently, in the past decade, complex algo

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