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李开复:人工智能的真正威胁是什么?

2017-08-18    来源:LearnAndRecord    【      美国外教 在线口语培训

人工智能已经深入生活的今天,社会上不乏“人工智能威胁论”,担忧机器人会“反噬”人类。

创新工场创始人兼CEO、人工智能工程院院长李开复博士日前在纽约时报(The New York Times)的“观点”(Opinion)栏目发表专栏文章《人工智能对人类社会的真正威胁》(The Real Threats of Artificial Intelligence),解读上上述问题。

在这篇文章里,李开复博士讨论了人工智能技术未来发展所带来的几个更真切和亟待解决的问题:全球性的失业问题及可能产生的全球性经济失衡和贫富差距。

The Real Threat of Artificial Intelligence

人工智能对人类社会的真正威胁

By KAI-FU LEE June 25, 2017
李开复 2017年6月25日

What worries you about the coming world of artificial intelligence?

你对即将到来的人工智能世界有何担忧?

Too often the answer to this question resembles the plot of a sci-fi thriller. People worry that developments in A.I. will bring about the “singularity” — that point in history when A.I. surpasses human intelligence, leading to an unimaginable revolution in human affairs. Or they wonder whether instead of our controlling artificial intelligence, it will control us, turning us, in effect, into cyborgs.
这一问题的答案常常像是科幻惊悚片的情节。人们担心,人工智能的发展将催生技术史上的“奇点”——也就是人工智能超越人类智力极限,在人类事务领域引发无法想象的革命的时刻。他们想知道,为我们所控制的人工智能,是否会反过来控制我们,实际上把我们变成了赛博人。

These are interesting issues to contemplate, but they are not pressing. They concern situations that may not arise for hundreds of years, if ever. At the moment, there is no known path from our best A.I. tools (like the Google computer program that recently beat the world's best player of the game of Go) to “general” A.I. — self-aware computer programs that can engage in common-sense reasoning, attain knowledge in multiple domains, feel, express and understand emotions and so on.
这些问题琢磨起来很有意思,但并不紧迫。人们担心的情况即便会发生,也要在千百年之后。我们目前还不知道,如何从我们最优秀的人工智能工具(例如最近击败了世界上最好的围棋手的谷歌计算机程序),走向“通用”人工智能,即拥有自我意识的计算机程序,可以进行常感推理,获取多个领域的知识,感知、表达和理解情绪等等。

This doesn't mean we have nothing to worry about. On the contrary, the A.I. products that now exist are improving faster than most people realize and promise to radically transform our world, not always for the better. They are only tools, not a competing form of intelligence. But they will reshape what work means and how wealth is created, leading to unprecedented economic inequalities and even altering the global balance of power.
这并不意味着我们就没什么可担心的了。相反,现有的人工智能产品正以超出大多数人想象的速度得到改进,很有可能让我们的世界发生根本性改变——不一定就是变得更好。它们只是工具,而非某种与人类竞争的智慧形式。但它们将重塑工作的含义和财富的创造方式,引发前所未有的经济不平等,甚至改变全球力量均势。

It is imperative that we turn our attention to these imminent challenges.
我们必须把目光转向这些迫在眉睫的挑战。

What is artificial intelligence today? Roughly speaking, it's technology that takes in huge amounts of information from a specific domain (say, loan repayment histories) and uses it to make a decision in a specific case (whether to give an individual a loan) in the service of a specified goal (maximizing profits for the lender). Think of a spreadsheet on steroids, trained on big data. These tools can outperform human beings at a given task.
今天的人工智能是什么?大致来说,它是一种从特定领域(例如贷款偿还记录)获取大量信息,并利用这些信息在特定情况下作出决定(是否贷款给某人),服务于特定目标(让贷方实现利润最大化)的技术。它就好比是打了鸡血——接受了大数据训练——的电子表格程序。执行特定任务时,这些工具的表现可以好于人类。

This kind of A.I. is spreading to thousands of domains (not just loans), and as it does, it will eliminate many jobs. Bank tellers, customer service representatives, telemarketers, stock and bond traders, even paralegals and radiologists will gradually be replaced by such software. Over time this technology will come to control semiautonomous and autonomous hardware like self-driving cars and robots, displacing factory workers, construction workers, drivers, delivery workers and many others.
这种人工智能正拓展至成千上万个领域(不只是贷款),在此过程中,它会让很多工作岗位消失。银行出纳员、客服代表、电话推销员、股票和债券交易员,甚至律师助理和放射科医师,都将逐渐被此类软件取而代之。假以时日,这种技术将会控制自动驾驶汽车、机器人等半自动化和自动化硬件,取代工厂工人、建筑工人、司机、快递员以及其他很多职业的从业者。

artificial
Other volunteer jobs may be higher-paying and professional, such as compassionate medical service providers who serve as the “human interface” for A.I. programs that diagnose cancer. In all cases, people will be able to choose to work fewer hours than they do now.
其他一些志愿者工作或许薪水更高,也更具专业性,比如富于爱心的医疗服务提供者——充当诊断癌症的人工智能程序的“人机界面”。不管怎样,人们都将可以选择让自己的工作时间比现在短。

Who will pay for these jobs? Here is where the enormous wealth concentrated in relatively few hands comes in. It strikes me as unavoidable that large chunks of the money created by A.I. will have to be transferred to those whose jobs have been displaced. This seems feasible only through Keynesian policies of increased government spending, presumably raised through taxation on wealthy companies.
谁会为这些工作支付薪水?这时候那些有大量财富集中在少数人手中的领域就该起作用了。在我看来,由人工智能创造的财富有一大部分要不可避免地被转移给那些因之失去工作的人。看起来,这一点似乎只有通过实行增加政府开支的凯恩斯经济政策才能做到,而政府开支的增加或许可以通过对有钱的公司征税实现。

As for what form that social welfare would take, I would argue for a conditional universal basic income: welfare offered to those who have a financial need, on the condition they either show an effort to receive training that would make them employable or commit to a certain number of hours of “service of love” voluntarism.
至于这种社会福利将是什么形态,我会赞成提供一种有条件的普遍基本收入:也就是给有财务需求的人提供的福利,条件是他们要么显示出接受培训、以便让自己有受雇资格的努力,要么承诺做一定时长的志愿“爱心服务”。

To fund this, tax rates will have to be high. The government will not only have to subsidize most people's lives and work; it will also have to compensate for the loss of individual tax revenue previously collected from employed individuals.
要给这些福利提供资金,势必要提高税率。政府不仅必须给大多数人的生活和工作提供补贴;还必须填补此前从受雇个体那里征收的个人税收的损失。

This leads to the final and perhaps most consequential challenge of A.I. The Keynesian approach I have sketched out may be feasible in the United States and China, which will have enough successful A.I. businesses to fund welfare initiatives via taxes. But what about other countries?
这会给人工智能带来最终、或许也是最重大的挑战。我设想的凯恩斯政策方案在美国和中国或许是可行的,这两个国家会有足够多成功的人工智能企业来通过税收资助福利措施。但其他国家呢?

They face two insurmountable problems. First, most of the money being made from artificial intelligence will go to the United States and China. A.I. is an industry in which strength begets strength: The more data you have, the better your product; the better your product, the more data you can collect; the more data you can collect, the more talent you can attract; the more talent you can attract, the better your product. It's a virtuous circle, and the United States and China have already amassed the talent, market share and data to set it in motion.
它们将面临两个难以克服的问题。第一,由人工智能创造的大部分财富将流向美国和中国。人工智能是一个强者更强的行业:你获得的数据越多,产品就会越好;产品越好,收集的数据越多;数据越多,就能吸引更多人才;人才越多,产品也会越好。这是一个良性循环,美国和中国已经积聚了足够多的人才、市场份额和数据来启动这个循环。

For example, the Chinese speech-recognition company iFlytek and several Chinese face-recognition companies such as Megvii and SenseTime have become industry leaders, as measured by market capitalization. The United States is spearheading the development of autonomous vehicles, led by companies like Google, Tesla and Uber. As for the consumer internet market, seven American or Chinese companies — Google, Facebook, Microsoft, Amazon, Baidu, Alibaba and Tencent — are making extensive use of A.I. and expanding operations to other countries, essentially owning those A.I. markets. It seems American businesses will dominate in developed markets and some developing markets, while Chinese companies will win in most developing markets.
比如,以市值论,中国语音识别公司科大讯飞,以及旷视科技和商汤科技等几家中国面部识别公司已经成为所在行业的领导者。美国则引领着自驾车的发展,由谷歌、特斯拉(Tesla)和优步等公司占据领先地位。至于消费者互联网市场,有七家美国或中国公司——谷歌、Facebook、微软(Microsoft)、亚马逊(Amazon)、百度、阿里巴巴和腾讯——在大量运用人工智能,并扩展它们在其他国家的业务,基本已经占领了这些人工智能市场。看起来,美国的公司将主导发达国家市场和一些发展中国家市场,而中国企业将在大多数发展中国家市场获胜。

The other challenge for many countries that are not China or the United States is that their populations are increasing, especially in the developing world. While a large, growing population can be an economic asset (as in China and India in recent decades), in the age of A.I. it will be an economic liability because it will comprise mostly displaced workers, not productive ones.
中国和美国之外的许多国家面临的另一个挑战是,人口在增加,尤其是发展中世界。尽管不断增长的庞大人口也可以成为经济资本(就像中国和印度最近几十年的情况),但在人工智能时代,它会成为一个经济责任,因为这些人口会构成大多数的失业工人,而不是多产的员工。

So if most countries will not be able to tax ultra-profitable A.I. companies to subsidize their workers, what options will they have? I foresee only one: Unless they wish to plunge their people into poverty, they will be forced to negotiate with whichever country supplies most of their A.I. software — China or the United States — to essentially become that country‘s economic dependent, taking in welfare subsidies in exchange for letting the “parent” nation's A.I. companies continue to profit from the dependent country's users. Such economic arrangements would reshape today's geopolitical alliances.
所以如果大多数国家无法从利润极高的人工智能企业征税来补贴自己的工人,它们还有什么选择呢?我能想到的只有一个:除非它们愿意让民众陷入贫困,否则就必须与供应最多人工智能软件的国家——中国或美国——谈判,最终成为这个国家的经济依赖者,以允许“母”国的人工智能企业继续从依赖国的用户身上获利,来换取福利补贴。这样的经济安排将重塑现有的地缘政治联盟。

One way or another, we are going to have to start thinking about how to minimize the looming A.I.-fueled gap between the haves and the have-nots, both within and between nations. Or to put the matter more optimistically: A.I. is presenting us with an opportunity to rethink economic inequality on a global scale. These challenges are too far-ranging in their effects for any nation to isolate itself from the rest of the world.
无论如何,我们都必须开始考虑如何将日渐临近的、由人工智能加大的贫富差距最小化,不管是国内的,还是国与国之间的。要么就得把这件事看得更乐观一些:人工智能给我们提供一个在全球范围内重新思考经济不平等的机会。这些挑战太过广泛,任何国家都无法将自己孤立起来,独自解决。


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