Level 7
Unit 2
Part3
Machine intelligence makes human morals more important
机器智能使人类道德更重要
by Zeynep Tufekci
So, I started my first job as a computer programmer in my very first year of college -- basically, as a teenager.sort of是什么意思英语
所以，我在大学一年级时就开始了我的第一份电脑程序员的工作，基本上是一个十几岁的孩子。
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.
我开始工作后不久，在一家公司写软件，一位在公司工作的经理来到我所在的地方，他低声对我说：“他能告诉我我在撒谎吗”房间里没有其他人。
"Can who tell if you're lying And why are we whispering"
“谁能告诉我你在撒谎我们为什么要窃窃私语”
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.
经理指着房间里的电脑。“他能告诉我我在撒谎吗”嗯，那个经理和接待员有暧昧关系。
(Laughter)
（笑声）
And I was still a teenager. So I whisper-shouted back to him, "Yes, the computer can tell if you're lying."
我还是个十几岁的孩子。于是我小声地对他喊道：“是的，电脑能分辨出你在撒谎。”
(Laughter)
（笑声）
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.
嗯，我笑了，但事实上，我笑了。现在，有一些计算系统可以解决情绪状态，甚至可以从处理人脸上撒谎。广告商甚至政府都很感兴趣。
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.
我已经成为一名电脑程序员，因为我是一个对数学和科学着迷的孩子。但我在某个地方学到了核武器，我真的很关心科学的伦理学。我很烦恼。然而，由于家庭情况，我也需要尽快开始工作。因此，我想，嘿，让我选择一个技术领域，我可以轻松地到一份工作，在那里我不需要处理任何棘手的道德问题。所以我选择了电脑。
(Laughter)
（笑声）
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.
哈，哈，哈！所有的笑声都在我身上。如今，计算机科学家正在构建一个平台，控制着每天有十亿人看到的东西。他们正在开发可以决定谁来跑的汽车。他们甚至制造机器，武器，可能会在战争中杀死人类。这是道德的一路下滑。
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.
机器智能在这里。我们现在使用计算来做所有的决定，但也有新的决定。我们问的问题是没有一个正确答案的计算，这是主观的，开放的和价值的。
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"
我们在问这样的问题：“公司应该雇佣谁”“你应该从哪个朋友那里得到更新”“哪一个犯人更有可能重新犯罪”“应该向人们推荐哪种新闻或电影”
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.
看，是的，我们已经使用了一段时间的电脑，但这是不同的。这是一个历史的转折，因为我们不能锚定计算这样的主观决定的方式，我们可以锚定计算的飞行飞机，建造桥梁，去月球。
飞机安全吗这座桥摇晃了吗在那里，我们已经达成一致，相当明确的基准，我们有自然法则来指导我们。在混乱的人类事务中，我们没有这样的锚定和基准。
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 algorithms have made great strides. They can recognize human faces. They can decipher handwriting. They can detect credit card fraud and block spam and they can translate between languages. They can detect tumors in medical imaging. They can beat humans in chess and Go.
为了使事情变得更复杂，我们的软件变得越来越强大，但它也变得越来越不透明，越来越复杂。最近，在过去的十年中，复杂的算法取得了很大的进步。他们可以识别人脸。他们能辨认笔迹。他们可以检测信用卡和阻止垃圾邮件，他们可以翻译之间的语言。他们可以在医学影像中发现肿瘤。他们可以在国际象棋中击败人类。
Much of this progress comes from a method called "machine learning." Machine learning is
different than traditional programming, where you give the computer detailed, exact, painstaking instructions. It's more like you take the system and you feed it lots of data, including unstructured data, like the kind we generate in our digital lives. And the system learns by churning through this data. And also, crucially, these systems don't operate under a single-answer logic. They don't produce a simple answer; it's more probabilistic: "This one is probably more like what you're looking for."

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