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人工智能的未来发展趋势及其对人类的深远影响
2018-10-10 君子冲盈 793 6 0  


The Development trend of AI in the Future and its Far-reaching influence on Mankind

人工智能的未来发展趋势及其对人类的深远影响

作者:YUVAL NOAH HARARI



Artificial intelligence could erase many practical advantages of democracy, and erode the ideals of liberty and equality. It will further concentrate power among a small elite if we don’t take steps to stop it.

人工智能(AI)会抹杀民主的许多实际好处,侵蚀自由和平等的理想,如果我们不采取措施阻止这种局面,权力将进一步掌握在少数精英手中。

I. The Growing Fear of Irrelevance

I、“ 无关紧要”(边缘化)的恐惧与日俱增

There is nothing inevitable about democracy. For all the success that democracies have had over the past century or more, they are blips in history. Monarchies, oligarchies, and other forms of authoritarian rule have been far more common modes of human governance.
The emergence of liberal democracies is associated with ideals of liberty and equality that may seem self-evident and irreversible. But these ideals are far more fragile than we believe. Their success in the 20th century depended on unique technological conditions that may prove ephemeral.

民主并非不可避免,尽管民主政体在过去一个世纪或更长的时间里取得了巨大成功,但它们仍是历史上的亮点。君主制、寡头制和其他形式的独裁统治是人类治理的更为常见的模式。
自由民主的出现是与自由平等的理想联系在一起,这些理想似乎是不言而喻和不可逆转,但它们远比我们想象的要脆弱,因为20世纪的成功取决于独特的技术条件,而这些条件可能只是昙花一现。

In the second decade of the 21st century, liberalism has begun to lose credibility. Questions about the ability of liberal democracy to provide for the middle class have grown louder; politics have grown more tribal; and in more and more countries, leaders are showing a penchant for demagoguery and autocracy.
The causes of this political shift are complex, but they appear to be intertwined with current technological developments. The technology that favored democracy is changing, and as artificial intelligence develops, it might change further.

在21世纪的头两个十年里,自由主义开始失去信誉,关于自由民主是否仍有为中产阶级提供支持的能力之类的问题越来越多,政治也变得越来越部落化,越来越多的国家领导人表现出对煽动和专制的偏好。
这种政治转变的原因很复杂,但它似乎与当前的技术发展交织在一起,随着人工智能的发展,支持民主的技术正在进一步改变。

Information technology is continuing to leap forward; biotechnology is beginning to provide a window into our inner lives—our emotions, thoughts, and choices. Together, infotech and biotech will create unprecedented upheavals in human society, eroding human agency and, possibly, subverting human desires. Under such conditions, liberal democracy and free-market economics might become obsolete.

信息技术在继续飞跃发展,生物技术开始为我们的内心生活,情感、思想和选择提供一个窗口,它们将在人类社会中创造前所未有的剧变,侵蚀人类能动性,并可能颠覆人类的欲望,这种情况下,自由民主和自由市场经济可能会过时。

Ordinary people may not understand artificial intelligence and biotechnology in any detail, but they can sense that the future is passing them by. In 1938 the common man’s condition in the Soviet Union, Germany, or the United States may have been grim, but he was constantly told that he was the most important thing in the world, and that he was the future (provided, of course, that he was an “ordinary man,” rather than, say, a Jew or a woman). He looked at the propaganda posters—which typically depicted coal miners and steelworkers in heroic poses—and saw himself there: “I am in that poster! I am the hero of the future!”

普通人可能不了解人工智能和生物技术的任何细节,但可以感觉到未来正从身边擦肩而过。
1938年,苏联、德国和美国普通人的情况可能是严峻的,但他们不断被告知,他们是世界上最重要的事物,他们就是未来( 当然,前提是他是一个“普通男人”,而不是一个犹太人或女人)。
宣传海报通常以英雄姿态描绘煤矿工人和钢铁工人,他们似乎看到自己:“我在那张海报里!我是未来的英雄!“

In 2018 the common person feels increasingly irrelevant. Lots of mysterious terms are bandied about excitedly in ted Talks, at government think tanks, and at high-tech conferences—globalization, blockchain, genetic engineering, AI, machine learning—and common people, both men and women, may well suspect that none of these terms is about them.

到了2018年,普通人感到自己越来越无关紧要了,TED Talk,政府智囊团,在高科技会议上提及的全球化、区块链、基因工程、人工智能、机器学习 这些术语,让普通人怀疑这些术语与他们无关。

In the 20th century, the masses revolted against exploitation and sought to translate their vital role in the economy into political power. Now the masses fear irrelevance, and they are frantic to use their remaining political power before it is too late. Brexit and the rise of Donald Trump may therefore demonstrate a trajectory opposite to that of traditional socialist revolutions. The Russian, Chinese, and Cuban revolutions were made by people who were vital to the economy but lacked political power; in 2016, Trump and Brexit were supported by many people who still enjoyed political power but feared they were losing their economic worth. Perhaps in the 21st century, populist revolts will be staged not against an economic elite that exploits people but against an economic elite that does not need them anymore. This may well be a losing battle. It is much harder to struggle against irrelevance than against exploitation.

20世纪,人民反对剥削,试图将他们在经济中的重要作用转化为政治权力,现在,人民害怕被边缘化,正疯狂地使用他们剩余的政治权力,迟了可能就没有了。
英国退欧和唐纳德·特朗普的崛起展示出一条与传统社会主义革命相反的轨迹。
俄罗斯、中国和古巴的革命是由对经济至关重要但缺乏政治权力的人发起的,而到了2016年,特朗普和英国退欧得到了许多人的支持,这些人仍享有政治权力,但担心他们丧失经济价值。
21世纪,也许民粹主义抗议活动将不再针对剥削人民的经济精英,而是针对那些不再需要他们的经济精英。
这可能是一场失败的战斗,因为反对边缘化比反对剥削要难得多。

The revolutions in information technology and biotechnology are still in their infancy, and the extent to which they are responsible for the current crisis of liberalism is debatable. Most people in Birmingham, Istanbul, St. Petersburg, and Mumbai are only dimly aware, if they are aware at all, of the rise of AI and its potential impact on their lives. It is undoubtable, however, that the technological revolutions now gathering momentum will in the next few decades confront humankind with the hardest trials it has yet encountered.

信息技术和生物技术革命正处于萌芽阶段,它们对当前自由主义危机的责任究竟多大还有待商榷。
伯明翰、伊斯坦布尔、圣彼得堡和孟买的大多数人只是隐约地意识到人工智能的兴起对他们的生活产生潜在影响,毋庸置疑置的是,目前正积聚势头的技术革命将在今后几十年中让人类面对前所未有的艰难考验。

II. A New Useless Class?

II、新的“  无用阶级”?

Let’s start with jobs and incomes, because whatever liberal democracy’s philosophical appeal, it has gained strength in no small part thanks to a practical advantage: The decentralized approach to decision making that is characteristic of liberalism—in both politics and economics—has allowed liberal democracies to outcompete other states, and to deliver rising affluence to their people.

从就业和收入开始说起。
无论自由民主的哲学诉求是什么,它在很大程度上都得益于一个实际优势:
无论在政治上还是在经济上,以自由主义为特征的权力下放决策方式使自由民主国家超过了其他国家,并为本国人民带来了不断增长的财富。

Liberalism reconciled the proletariat with the bourgeoisie, the faithful with atheists, natives with immigrants, and Europeans with Asians by promising everybody a larger slice of the pie. With a constantly growing pie, that was possible. And the pie may well keep growing. However, economic growth may not solve social problems that are now being created by technological disruption, because such growth is increasingly predicated on the invention of more and more disruptive technologies.

自由主义将无产阶级与资产阶级、信徒与无神论者、当地人与移民、欧洲人与亚洲人调和起来,许诺每个人都能随着馅饼的不断增长,会分到一份更大的馅饼。
馅饼可能会继续增长,但经济增长可能解决不了技术破坏所造成的社会问题,因为这种增长越来越取决于破坏性技术的发明。

Fears of machines pushing people out of the job market are, of course, nothing new, and in the past such fears proved to be unfounded. But artificial intelligence is different from the old machines. In the past, machines competed with humans mainly in manual skills. Now they are beginning to compete with us in cognitive skills. And we don’t know of any third kind of skill—beyond the manual and the cognitive—in which humans will always have an edge.

机器取代人们的工作并不是什么新鲜事,过去这种恐惧是没有根据的,但人工智能与旧机器不同,过去,机器主要在手工技能方面与人类竞争,现在,人工智能开始在认知技能上与我们竞争,除手工和认知技能以外,不知道人类是否拥有第三种技能优势。

At least for a few more decades, human intelligence is likely to far exceed computer intelligence in numerous fields. Hence as computers take over more routine cognitive jobs, new creative jobs for humans will continue to appear. Many of these new jobs will probably depend on cooperation rather than competition between humans and AI. Human-AI teams will likely prove superior not just to humans, but also to computers working on their own.

至少在未来几十年里,人工智能可能在许多领域远超计算机智能,因此,随着计算机接管更多的日常认知工作,人类新的创造性工作将继续出现,许多新工作可能需要人类和人工智能的相互合作而不是竞争。
人类—人工智能的组合可能不仅比人类优越,而且也优于那些独立运作的计算机。

However, most of the new jobs will presumably demand high levels of expertise and ingenuity, and therefore may not provide an answer to the problem of unemployed unskilled laborers, or workers employable only at extremely low wages. Moreover, as AI continues to improve, even jobs that demand high intelligence and creativity might gradually disappear. The world of chess serves as an example of where things might be heading. For several years after IBM’s computer Deep Blue defeated Garry Kasparov in 1997, human chess players still flourished; AI was used to train human prodigies, and teams composed of humans plus computers proved superior to computers playing alone.

然而大多数新工作可能需要高水平的专业知识和创造力,因此可能无法解决非熟练技术工人或从事极低工资的工人失业问题。
此外,随着人工智能的不断改善,要求高智力和创造力的工作也可能会逐渐消失。
人机对决就是一个例子,1997年IBM公司的计算机“深蓝”在象棋比赛中击败了加里·卡斯帕罗夫,随后几年人类棋手仍然蓬勃发展,人工智能被用来训练人类天才,事实证明由人类和计算机组成的团队比比单独使用电脑更优越。

Yet in recent years, computers have become so good at playing chess that their human collaborators have lost their value and might soon become entirely irrelevant. On December 6, 2017, another crucial milestone was reached when Google’s AlphaZero program defeated the Stockfish 8 program. Stockfish 8 had won a world computer chess championship in 2016. It had access to centuries of accumulated human experience in chess, as well as decades of computer experience. By contrast, AlphaZero had not been taught any chess strategies by its human creators—not even standard openings. Rather, it used the latest machine-learning principles to teach itself chess by playing against itself. Nevertheless, out of 100 games that the novice AlphaZero played against Stockfish 8, AlphaZero won 28 and tied 72—it didn’t lose once. Since AlphaZero had learned nothing from any human, many of its winning moves and strategies seemed unconventional to the human eye. They could be described as creative, if not downright genius.

近几年来,人工智能已经非常擅长下棋,以至于人类合作者已经失去了价值,可能很快就会变得无用。
2017年12月6日,谷歌的Alpha Zero项目击败了Stockfish 8,这是另一个重要的里程碑。Stockfish 8在2016年赢得了世界计算机象棋锦标赛的冠军,它有人类几个世纪积累的国际象棋经验和几十年的计算机经验。
相比之下,Alpha Zero 从未从人类创造者那里学过任何国际象棋策略,甚至连标准的开局都没学。
它利用最新的“ 机器学习”原理,通过与自己对弈来自学,尽管如此,新手 Alpha Zero在与 Stockfish 8 的100场比赛中,AlphaZero赢了28场,平局72场,没有输过一场比赛。
由于Alpha Zero 没有从人类身上学任何东西,它运用的许多成功举动和策略是非比寻常的,如果它不是彻头彻尾的天才的话,那它可是很有创造力。

Can you guess how long AlphaZero spent learning chess from scratch, preparing for the match against Stockfish 8, and developing its genius instincts? Four hours. For centuries, chess was considered one of the crowning glories of human intelligence. AlphaZero went from utter ignorance to creative mastery in four hours, without the help of any human guide.

猜猜Alpha Zero花了多长时间从头开始学习国际象棋,并在比赛中击败了Stockfish 8?
——4个小时。
几个世纪以来,国际象棋一直被认为是人类智慧的最高荣耀之一,在没有任何人类向导帮助的情况下,Alpha Zero在4个小时内从彻底的无知变成了创造性的掌握。

AlphaZero is not the only imaginative software out there. One of the ways to catch cheaters in chess tournaments today is to monitor the level of originality that players exhibit. If they play an exceptionally creative move, the judges will often suspect that it could not possibly be a human move—it must be a computer move. At least in chess, creativity is already considered to be the trademark of computers rather than humans! So if chess is our canary in the coal mine, we have been duly warned that the canary is dying. What is happening today to human-AI teams in chess might happen down the road to human-AI teams in policing, medicine, banking, and many other fields.

Alpha Zero并不是世界上唯一有创造力的软件,在如今的国际象棋比赛中,捕捉作弊者的方法之一是监控棋手们所展示的创意水平。
如果他们使用了一个极具创造性的动作,评委们通常会怀疑这是电脑的动作,而不可能是人类的。
至少在国际象棋中,创造力被认为是计算机的标志,而不是人类!
如果说国家象棋是我们这座“煤矿里的金丝雀 ”,那么我们已被适时地警告了——这只金丝雀快要死了。
今天发生在国际象棋中的人类-人工智能组合,很可能会在警务、医学、银行业和其他许多领域中发生。

What’s more, AI enjoys uniquely nonhuman abilities, which makes the difference between AI and a human worker one of kind rather than merely of degree. Two particularly important nonhuman abilities that AI possesses are connectivity and updatability.

更重要的是,人工智能具有独特的非人类能力,这使人工智能和人类工作者之间的区别只是存在某种程度上的区别。人工智能拥有两个特别重要的非人类能力,即连通性和可更新性。

For example, many drivers are unfamiliar with all the changing traffic regulations on the roads they drive, and they often violate them. In addition, since every driver is a singular entity, when two vehicles approach the same intersection, the drivers sometimes miscommunicate their intentions and collide. Self-driving cars, by contrast, will know all the traffic regulations and never disobey them on purpose, and they could all be connected to one another. When two such vehicles approach the same junction, they won’t really be two separate entities, but part of a single algorithm. The chances that they might miscommunicate and collide will therefore be far smaller.

举个例子:许多司机不熟悉他们所驾驶的道路上不断变化的交通规则,导致经常违规,此外,每个司机都是一个单一的实体,当两辆车接近同一个交叉路口时,司机们有时会误解彼此的意图而发生碰撞。
相比之下,自动驾驶汽车知道所有的交通规则,从来不会故意违规,而且它们还可以相互连接。
当两辆自动驾驶汽车接近同一个路口时,它们实际上并不是两个独立的实体,而是一个单一算法的一部分,因此,它们发生误传和碰撞的可能性要小得多。

Similarly, if the World Health Organization identifies a new disease, or if a laboratory produces a new medicine, it can’t immediately update all the human doctors in the world. Yet even if you had billions of AI doctors in the world—each monitoring the health of a single human being—you could still update all of them within a split second, and they could all communicate to one another their assessments of the new disease or medicine. These potential advantages of connectivity and updatability are so huge that at least in some lines of work, it might make sense to replace all humans with computers, even if individually some humans still do a better job than the machines.

类似的,如果世界卫生组织发现了一种新疾病,或者一个实验室生产了一种新药,它不能立即“更新”世界上所有的人类医生,但是假如世界上有数十亿人工智能医生,每个这样的医生都可以监测一个人的健康,你就可以在瞬间更新所有这些智能医生,让它们可以对这种新疾病相互交流或者对新药物做出评估。
连接性和可更新性的潜在优势是如此巨大,以至于在某些工作领域,用计算机取代人类是有意义的,即使个别人类仍然做得比机器更好。

The same technologies that might make billions of people economically irrelevant might also make them easier to monitor and control.
All of this leads to one very important conclusion: The automation revolution will not consist of a single watershed event, after which the job market will settle into some new equilibrium. Rather, it will be a cascade of ever bigger disruptions. Old jobs will disappear and new jobs will emerge, but the new jobs will also rapidly change and vanish. People will need to retrain and reinvent themselves not just once, but many times.

同样的技术,可能使数十亿人在经济上变得无关紧要,也可能使他们更容易被监测和控制。
所有这些导致了一个非常重要的结论:自动化革命将不会是一个单一的分水岭事件,在此之后就业市场未必会稳定在某种新的均衡状态,相反,这将是一连串的混乱,旧的工作消失,新的工作出现,但新的工作也会迅速改变和消失。
人们将需要重新训练和改造自己,不是一次而是多次。

Just as in the 20th century governments established massive education systems for young people, in the 21st century they will need to establish massive reeducation systems for adults. But will that be enough? Change is always stressful, and the hectic world of the early 21st century has produced a global epidemic of stress. As job volatility increases, will people be able to cope? By 2050, a useless class might emerge, the result not only of a shortage of jobs or a lack of relevant education but also of insufficient mental stamina to continue learning new skills.

正如20世纪的政府为年轻人建立了大规模的教育体系那样,21世纪需要为成年人建立大规模的再教育体系。
这样就可以了吗?
变化总是充满压力的,21世纪初忙乱的世界产生了全球性的压力。
人们能够应付工作变化吗?
到2050年,可能会出现一个“无用阶级”,不仅是缺乏就业机会或缺乏相关教育,而且还缺乏继续学习新技能的心理耐力。

III. The Rise of Digital Dictatorships

III. 数字独裁的崛起

As many people lose their economic value, they might also come to lose their political power. The same technologies that might make billions of people economically irrelevant might also make them easier to monitor and control.

许多人失去经济价值的同时,也可能失去政治权力,同样的技术可能使数十亿人在经济上变得无关紧要,也可能使他们更容易被监测和控制。

AI frightens many people because they don’t trust it to remain obedient. Science fiction makes much of the possibility that computers or robots will develop consciousness—and shortly thereafter will try to kill all humans. But there is no particular reason to believe that AI will develop consciousness as it becomes more intelligent. We should instead l fear AI because it will probably always obey its human masters, and never rebel. AI is a tool and a weapon unlike any other that human beings have developed; it will almost certainly allow the already powerful to consolidate their power further.

人工智能让人恐慌,因为人们不相信它会顺从,很多科幻小说描述计算机或机器人可能会发展出意识,并在不久之后试图杀死所有人类。
但目前还没有特别的理由让人相信人工智能会因越来越智能而发展出意识,相反,我们不应该害怕人工智能,因为它可能永远服从人类主人,永远不会造反。
人工智能是一种不同于人类开发的其他工具和武器,它会让强大的国家进一步巩固力量。

Consider surveillance. Numerous countries around the world, including several democracies, are busy building unprecedented systems of surveillance. For example, Israel is a leader in the field of surveillance technology, and has created in the occupied West Bank a working prototype for a total-surveillance regime. Already today whenever Palestinians make a phone call, post something on Facebook, or travel from one city to another, they are likely to be monitored by Israeli microphones, cameras, drones, or spy software. Algorithms analyze the gathered data, helping the Israeli security forces pinpoint and neutralize what they consider to be potential threats. The Palestinians may administer some towns and villages in the West Bank, but the Israelis command the sky, the airwaves, and cyberspace. It therefore takes surprisingly few Israeli soldiers to effectively control the roughly 2.5 million Palestinians who live in the West Bank.

说到监视,世界上许多国家,包括几个民主国家,正忙于建立前所未有的监测系统。
例如,以色列是监视技术领域的领导者,并正在西岸建立了一个基于全面监视制度的工作原型。
今天,不管巴勒斯坦人何时打电话、或在Facebook上发布信息、或从一个城市到另一个城市旅行,他们都可能会受到以色列语音、摄像机、无人机或间谍软件的监视。
算法分析收集到的数据可以帮助以色列安全部队找出并消除他们认为潜在的威胁。
巴勒斯坦人可能控制着约旦河西岸的一些城镇和村庄,但以色列人控制着天空、广播和网络空间。
因此,只需很少的以色列士兵就能有效控制住在约旦河西岸的大约250万巴勒斯坦人。

In one incident in October 2017, a Palestinian laborer posted to his private Facebook account a picture of himself in his workplace, alongside a bulldozer. Adjacent to the image he wrote, “Good morning!” A Facebook translation algorithm made a small error when transliterating the Arabic letters. Instead of Ysabechhum (which means “Good morning”), the algorithm identified the letters as Ydbachhum (which means “Hurt them”). Suspecting that the man might be a terrorist intending to use a bulldozer to run people over, Israeli security forces swiftly arrested him. They released him after they realized that the algorithm had made a mistake. Even so, the offending Facebook post was taken down—you can never be too careful. What Palestinians are experiencing today in the West Bank may be just a primitive preview of what billions of people will eventually experience all over the planet.

在2017年10月的一次事件中,一名巴勒斯坦劳工在自己的私人 Facebook 账户上发布了一张自己在工作场所的照片,旁边还有一台推土机,他在图片旁边写道:“早上好!”
Facebook 翻译算法在音译阿拉伯字母时犯了一个小错误,该算法将Ysabechhum (意思是“早上好”),识别为Ydbachhum( 意思是“伤害他们”)。
以色列安全部队怀疑这名男子可能是企图用推土机碾压他人的恐怖分子,迅速逮捕了他,当他们意识到是算法出错后就放了他。
即便如此,这条令人不快的 Facebook 帖子还是被撤下了——再怎么小心也不为过。
今天西岸的巴勒斯坦人所经历的这些,可能是全世界数十亿人民最终都将经历的一种预演。

Imagine, for instance, that the current regime in North Korea gained a more advanced version of this sort of technology in the future. North Koreans might be required to wear a biometric bracelet that monitors everything they do and say, as well as their blood pressure and brain activity. Using the growing understanding of the human brain and drawing on the immense powers of machine learning, the North Korean government might eventually be able to gauge what each and every citizen is thinking at each and every moment. If a North Korean looked at a picture of Kim Jong Un and the biometric sensors picked up telltale signs of anger (higher blood pressure, increased activity in the amygdala), that person could be in the gulag the next day.

想象一下,假如目前的朝鲜政权在未来获得了这种技术的升级版,朝鲜人可能被要求佩戴一个生物识别手镯,以便监控他们的言行,血压和大脑活动。
借助机器的强大学习力量结合对人脑与日俱增的了解,朝鲜政府或许最终能够衡量每一个公民在每一个时刻的想法,如果一个朝鲜人看到金正恩的照片,生物识别传感器检测到愤怒的迹象( 血压升高,杏仁核活动增加 ),那么这个人可能第二天就会被关进劳改营。

The conflict between democracy and dictatorship is actually a conflict between two different data-processing systems. AI may swing the advantage toward the latter.

民主和独裁之间的冲突实际上是两个不同数据处理系统之间的冲突,人工智能会把优势转向后者。

And yet such hard-edged tactics may not prove necessary, at least much of the time. A facade of free choice and free voting may remain in place in some countries, even as the public exerts less and less actual control. To be sure, attempts to manipulate voters’ feelings are not new. But once somebody (whether in San Francisco or Beijing or Moscow) gains the technological ability to manipulate the human heart—reliably, cheaply, and at scale—democratic politics will mutate into an emotional puppet show.

在大多数情况下,这样的强硬策略没有必要,一些国家可能仍存在自由选择和自由投票的假象,而公众实际行使的权力越来越少。
实际上试图操纵选民感情并不是什么新鲜事。一旦某个人( 无论是在旧金山、北京还是莫斯科 ) 获得了大规模、可靠、廉价操纵人心的技术能力,民主政治就会演变成一场有情感的木偶戏。

We are unlikely to face a rebellion of sentient machines in the coming decades, but we might have to deal with hordes of bots that know how to press our emotional buttons better than our mother does and that use this uncanny ability, at the behest of a human elite, to try to sell us something—be it a car, a politician, or an entire ideology. The bots might identify our deepest fears, hatreds, and cravings and use them against us. We have already been given a foretaste of this in recent elections and referendums across the world, when hackers learned how to manipulate individual voters by analyzing data about them and exploiting their prejudices. While science-fiction thrillers are drawn to dramatic apocalypses of fire and smoke, in reality we may be facing a banal apocalypse by clicking.

在未来几十年里,我们不太可能面对“ 有情感机器”的反叛,但可能不得不面对一大群比我们母亲更懂得我们情感需求的机器人。
人类精英利用这种不可思议的能力,试图向我们推销汽车、政客,或是整个意识形态,机器人可能会识别我们内心最深的恐惧、仇恨和渴望——这些被精英们用来操控我们。
从世界各地最近的选举和公投中,我们已经预先体验到了这一点,即黑客通过分析有关选民个人的数据——利用他们的偏见来操控他们。
当我们被科幻惊悚片戏剧性的灾难所吸引时,实际上我们可能正面临的是一个通过“点击”产生的平庸天启。

The biggest and most frightening impact of the AI revolution might be on the relative efficiency of democracies and dictatorships. Historically, autocracies have faced crippling handicaps in regard to innovation and economic growth. In the late 20th century, democracies usually outperformed dictatorships, because they were far better at processing information. We tend to think about the conflict between democracy and dictatorship as a conflict between two different ethical systems, but it is actually a conflict between two different data-processing systems. Democracy distributes the power to process information and make decisions among many people and institutions, whereas dictatorship concentrates information and power in one place. Given 20th-century technology, it was inefficient to concentrate too much information and power in one place. Nobody had the ability to process all available information fast enough and make the right decisions. This is one reason the Soviet Union made far worse decisions than the United States, and why the Soviet economy lagged far behind the American economy.

人工智能革命的最大和最可怕的影响可能是民主和独裁的相对效率。
历史上,独裁政权在创新和经济增长方面面临着严重的障碍。
在20世纪末,民主国家通常比独裁国家表现得更好,因为它们在处理信息方面要好得多。
我们倾向于认为民主和独裁之间的冲突是两种不同的伦理体系之间的冲突,但它实际上是两种不同的数据处理系统之间的冲突。
民主将处理信息和决策的权力分配给许多人和机构,而独裁则将信息和权力集中在一个地方。
考虑到20世纪的技术,把太多的信息和权力集中在一个地方是没有效率的,没有人有能力以足够快的速度处理所有可用的信息,并做出正确的决定。
这是苏联做出比美国糟糕得多的决定的原因之一,也是苏联经济远远落后于美国经济的原因之一。

However, artificial intelligence may soon swing the pendulum in the opposite direction. AI makes it possible to process enormous amounts of information centrally. In fact, it might make centralized systems far more efficient than diffuse systems, because machine learning works better when the machine has more information to analyze. If you disregard all privacy concerns and concentrate all the information relating to a billion people in one database, you’ll wind up with much better algorithms than if you respect individual privacy and have in your database only partial information on a million people. An authoritarian government that orders all its citizens to have their DNA sequenced and to share their medical data with some central authority would gain an immense advantage in genetics and medical research over societies in which medical data are strictly private. The main handicap of authoritarian regimes in the 20th century—the desire to concentrate all information and power in one place—may become their decisive advantage in the 21st century.

人工智能可能很快就会将天平推向相反的方向,人工智能使集中处理大量信息成为可能,事实上,它可能使集中式系统比分散系统更有效,因为机器学习在机器有更多信息可供分析时工作得更好。
如果你不理会隐私问题,把与10亿人有关的所有信息集中在一个数据库中,你会得到比尊重个人隐私更好的算法,远强于你的数据库中只有100万人的部分信息。
一个威权政府命令其所有公民进行DNA测序,并与某些中央当局分享他们的医疗数据,将在遗传学和医学研究方面获得巨大的优势,而在这些社会中,医疗数据是严格保密的。
20世纪独裁政权的主要障碍——将所有信息和权力集中在一个地方的愿望——可能成为他们在21世纪的决定性优势。

New technologies will continue to emerge, of course, and some of them may encourage the distribution rather than the concentration of information and power. Blockchain technology, and the use of cryptocurrencies enabled by it, is currently touted as a possible counterweight to centralized power. But blockchain technology is still in the embryonic stage, and we don’t yet know whether it will indeed counterbalance the centralizing tendencies of AI. Remember that the Internet, too, was hyped in its early days as a libertarian panacea that would free people from all centralized systems—but is now poised to make centralized authority more powerful than ever.

当然,新技术将继续出现,其中一些技术可能鼓励信息和权力的分散,而不是集中。
比如区块链技术,以及它所支持的加密货币的使用,目前被吹捧为对集中权力的一种可能的抗衡。、
但是区块链技术还处于萌芽阶段,我们还不知道它是否真的会抵消人工智能的集中化趋势。
请注意,互联网在其早期也曾被宣传为一种自由意志的灵丹妙药,它将人们从所有的中央集权体系中解放出来——但现在,它正准备使中央集权比以往任何时候都更加强大。

IV. The Transfer of Authority to Machines

IV、权力向机器移交

Even if some societies remain ostensibly democratic, the increasing efficiency of algorithms will still shift more and more authority from individual humans to networked machines. We might willingly give up more and more authority over our lives because we will learn from experience to trust the algorithms more than our own feelings, eventually losing our ability to make many decisions for ourselves. Just think of the way that, within a mere two decades, billions of people have come to entrust Google’s search algorithm with one of the most important tasks of all: finding relevant and trustworthy information. As we rely more on Google for answers, our ability to locate information independently diminishes. Already today, “truth” is defined by the top results of a Google search. This process has likewise affected our physical abilities, such as navigating space. People ask Google not just to find information but also to guide them around. Self-driving cars and AI physicians would represent further erosion: While these innovations would put truckers and human doctors out of work, their larger import lies in the continuing transfer of authority and responsibility to machines.

即使一些社会表面上仍然是民主的,但算法的日益提高的效率仍然会把越来越多的权威从个人转移到联网的机器上。
我们可能会心甘情愿地放弃越来越多我们生活中的权威——因为我们将从经验中认识到应该更多的信任算法,而不是我们自己的感觉,并最终失去我们为自己做出许多决定的能力。
想想看,在短短20年的时间里,数十亿人开始把最重要的任务之一 ——寻找相关和可信的信息——托付给谷歌搜索算法,当我们更多地依赖谷歌来寻找答案时,我们独立定位信息的能力就会减弱。
如今,“真相”已经由谷歌搜索的顶级搜索结果定义,这个过程也同样影响了我们的身体能力,比如导航(空间感)。
人们要求谷歌不仅要找到信息,还要引导他们到处走,自动驾驶汽车和人工智能医生将代表进一步的侵蚀:
尽管这些创新将使卡车司机和医生失业,但它们更重要的意义在于继续将权力和责任移交给机器。

Humans are used to thinking about life as a drama of decision making. Liberal democracy and free-market capitalism see the individual as an autonomous agent constantly making choices about the world. Works of art—be they Shakespeare plays, Jane Austen novels, or cheesy Hollywood comedies—usually revolve around the hero having to make some crucial decision. To be or not to be? To listen to my wife and kill King Duncan, or listen to my conscience and spare him? To marry Mr. Collins or Mr. Darcy? Christian and Muslim theology similarly focus on the drama of decision making, arguing that everlasting salvation depends on making the right choice.
What will happen to this view of life as we rely on AI to make ever more decisions for us? Even now we trust Netflix to recommend movies and Spotify to pick music we’ll like. But why should AI’s helpfulness stop there?

人类习惯于把生活看作是一场决策的戏剧,自由民主和自由市场资本主义视个人为一个自主的代理人,不断地对世界作出选择。
艺术作品——无论是莎士比亚的戏剧、简·奥斯汀的小说,还是俗气的好莱坞喜剧——通常都围绕着主人公必须做出的一些关键的决定,生存还是毁灭,听我妻子的话杀了邓肯国王,还是听我的良心饶了他?嫁给柯林斯先生还是达西先生?
基督教和穆斯林神学同样关注这种决策的戏剧,认为永恒的救赎取决于做出正确的选择。
当我们依赖人工智能为我们做更多的决定时,我们的人生观会发生怎样的变化?
即使是现在,我们也相信 Netflix 会推荐电影,Spotify 会挑选我们喜欢的音乐,但为什么人工智能的帮助就止步于此呢?

Every year millions of college students need to decide what to study. This is a very important and difficult decision, made under pressure from parents, friends, and professors who have varying interests and opinions. It is also influenced by students’ own individual fears and fantasies, which are themselves shaped by movies, novels, and advertising campaigns. Complicating matters, a given student does not really know what it takes to succeed in a given profession, and doesn’t necessarily have a realistic sense of his or her own strengths and weaknesses.

每年,数以百万计的大学生需要决定学习什么,这是一个非常重要和困难的决定,是在父母、朋友和教授的压力下做出的,他们的兴趣和观点各不相同,它也受到学生自己的恐惧和幻想的影响,而这些恐惧和幻想本身就是由电影、小说和广告活动塑造的,使事情复杂化的是,一个特定的学生并不真正知道如何才能在特定的职业中取得成功,也不一定对他或她自己的长处和短处有一个现实的认识。

It’s not so hard to see how AI could one day make better decisions than we do about careers, and perhaps even about relationships. But once we begin to count on AI to decide what to study, where to work, and whom to date or even marry, human life will cease to be a drama of decision making, and our conception of life will need to change. Democratic elections and free markets might cease to make sense. So might most religions and works of art. Imagine Anna Karenina taking out her smartphone and asking Siri whether she should stay married to Karenin or elope with the dashing Count Vronsky. Or imagine your favorite Shakespeare play with all the crucial decisions made by a Google algorithm. Hamlet and Macbeth would have much more comfortable lives, but what kind of lives would those be? Do we have models for making sense of such lives?

不难看出,人工智能有一天会做出比我们更好的职业决定,甚至是人际关系方面的决定。
但一旦我们开始依赖人工智能来决定学习什么,在哪里工作,和谁约会,甚至结婚,人类的生活将不再是一场决策的戏剧,我们的生活观念将被改变。
民主选举和自由市场可能不再有意义,大多数宗教和艺术作品也是如此。
想象一下,安娜·卡列尼娜拿出她的智能手机,问Siri 她是应该和卡列宁保持婚姻,还是应该和风度翩翩的渥伦斯基伯爵私奔。或者想象一下,你最喜欢的莎士比亚戏剧中,所有的关键决策都是由谷歌算法做出的,哈姆雷特和麦克白的生活可能会更舒适,但那会是什么样的生活呢?我们有了解这种生活的模型吗?

Can parliaments and political parties overcome these challenges and forestall the darker scenarios? At the current moment this does not seem likely. Technological disruption is not even a leading item on the political agenda. During the 2016 U.S. presidential race, the main reference to disruptive technology concerned Hillary Clinton’s email debacle, and despite all the talk about job loss, neither candidate directly addressed the potential impact of automation. Donald Trump warned voters that Mexicans would take their jobs, and that the U.S. should therefore build a wall on its southern border. He never warned voters that algorithms would take their jobs, nor did he suggest building a firewall around California.

议会和政党能否克服这些挑战,防止出现更黑暗的局面?目前看来,似乎不太可能。
技术破坏甚至不是政治议程上的一个主要项目,2016年美国总统大选期间,主要提及到的颠覆性技术的是希拉里·克林顿的电子邮件丑闻,尽管各方都在谈论失业问题,但两位候选人都没有直接谈到自动化的潜在影响。
唐纳德·特朗普警告选民,墨西哥人会抢走他们的工作,因此美国应该在其南部边境修建一道墙,他从来没有警告过选民算法会夺走他们的工作,也没有建议在加州周围建立防火墙。

So what should we do?
For starters, we need to place a much higher priority on understanding how the human mind works—particularly how our own wisdom and compassion can be cultivated. If we invest too much in AI and too little in developing the human mind, the very sophisticated artificial intelligence of computers might serve only to empower the natural stupidity of humans, and to nurture our worst (but also, perhaps, most powerful) impulses, among them greed and hatred. To avoid such an outcome, for every dollar and every minute we invest in improving AI, we would be wise to invest a dollar and a minute in exploring and developing human consciousness.

那我们该怎么办?
首先,我们需要更加重视理解人类思维是如何运作的——特别是我们的智慧和同情心是如何被培养起来的。
如果我们在人工智能上投入太多,而在开发人类思维方面投入太少,那么非常复杂的计算机人工智能可能只会增强人类天生的愚蠢,并培养我们最坏的( 但也可能是最强大的 )冲动,其中包括贪婪和仇恨。
为了避免这样的结果,我们不但要投入时间和金钱改善人工智能,也应该地投入时间和金钱来探索和发展人类意识,这才是明智之举。

More practically, and more immediately, if we want to prevent the concentration of all wealth and power in the hands of a small elite, we must regulate the ownership of data. In ancient times, land was the most important asset, so politics was a struggle to control land. In the modern era, machines and factories became more important than land, so political struggles focused on controlling these vital means of production. In the 21st century, data will eclipse both land and machinery as the most important asset, so politics will be a struggle to control data’s flow.

如果我们想防止所有财富和权力集中在少数精英手中,我们就必须更实际、更直接地管理数据的所有权。
在古代,土地是最重要的资产,所以政治是一场控制土地的斗争,在现代,机器和工厂变得比土地更重要,因此政治斗争集中在控制这些重要的生产资料上,在21世纪,数据将取代土地和机器,成为最重要的资产,因此政治将是一场控制数据流动的斗争。

Unfortunately, we don’t have much experience in regulating the ownership of data, which is inherently a far more difficult task than regulating land or machines. Data are everywhere and nowhere at the same time, they can move at the speed of light, and you can create as many copies of them as you want. Do the data collected about my DNA, my brain, and my life belong to me, or to the government, or to a corporation, or to the human collective?

不幸的是,我们在管理数据所有权方面没有太多的经验,这在本质上是一项比管理土地或机器要困难得多的任务,数据无处不在,同时又无处可寻,它们可以光速移动,你可以创建任意数量的数据拷贝,收集到的关于我的DNA、大脑和生命的数据是属于我的,还是属于政府的,属于公司的,还是属于人类集体的?

The race to accumulate data is already on, and is currently headed by giants such as Google and Facebook and, in China, Baidu and Tencent. So far, many of these companies have acted as “attention merchants”—they capture our attention by providing us with free information, services, and entertainment, and then they resell our attention to advertisers. Yet their true business isn’t merely selling ads. Rather, by capturing our attention they manage to accumulate immense amounts of data about us, which are worth more than any advertising revenue. We aren’t their customers—we are their product.

积累数据的竞赛已经开始,目前领头的是 Google 和 Facebook 等巨头,在中国则是百度和腾讯。
到目前为止,许多这样的公司都扮演着“注意力商人”的角色——它们通过向我们提供免费信息、服务和娱乐来吸引我们的注意力,然后将我们的注意力转售给广告商。
然而,他们真正的业务并不仅仅是销售广告,通过吸引我们的注意力,他们设法积累了大量关于我们的数据,这些数据比任何广告收入都更有价值,我们不是他们的顾客,我们是他们的产品。

Ordinary people will find it very difficult to resist this process. At present, many of us are happy to give away our most valuable asset—our personal data—in exchange for free email services and funny cat videos. But if, later on, ordinary people decide to try to block the flow of data, they are likely to have trouble doing so, especially as they may have come to rely on the network to help them make decisions, and even for their health and physical survival.

普通人会发现很难抗拒这一进程。目前,我们中的许多人都很乐意把我们最宝贵的资产——我们的个人数据——作为交换,换取免费的电子邮件服务和滑稽的撸猫视频,但是,如果普通人之后决定试图阻止数据流动,他们很可能会遇到困难,特别是因为他们可能已经开始依赖网络来帮助他们做出决定,甚至是为了他们的健康和身体生存。

Nationalization of data by governments could offer one solution; it would certainly curb the power of big corporations. But history suggests that we are not necessarily better off in the hands of overmighty governments. So we had better call upon our scientists, our philosophers, our lawyers, and even our poets to turn their attention to this big question: How do you regulate the ownership of data?

由政府将数据国有化可以提供一种解决方案,它肯定会抑制大公司的力量,但历史表明,掌握在过于强大的政府手中我们不一定会更好。
因此,我们最好呼吁我们的科学家、哲学家、律师,甚至我们的诗人,把他们的注意力转向这个大问题:
如何规范数据的所有权?

Currently, humans risk becoming similar to domesticated animals. We have bred docile cows that produce enormous amounts of milk but are otherwise far inferior to their wild ancestors. They are less agile, less curious, and less resourceful. We are now creating tame humans who produce enormous amounts of data and function as efficient chips in a huge data-processing mechanism, but they hardly maximize their human potential. If we are not careful, we will end up with downgraded humans misusing upgraded computers to wreak havoc on themselves and on the world.

目前,人类面临着与驯养动物相似的风险。
我们驯养了温顺的奶牛,这些奶牛产奶量巨大,但在其他方面远不如它们的野生祖先,它们不那么敏捷,不那么好奇,应变能力也低。
我们现在正在创造温顺的人类,他们产生大量的数据,并在巨大的数据处理机制中充当有效芯片,但他们几乎无法最大限度地发挥人类的潜力,如果我们不小心谨慎的话,我们将以降级的人类结束,误用升级的计算机,对自己和世界造成严重破坏。

If you find these prospects alarming—if you dislike the idea of living in a digital dictatorship or some similarly degraded form of society—then the most important contribution you can make is to find ways to prevent too much data from being concentrated in too few hands, and also find ways to keep distributed data processing more efficient than centralized data processing. These will not be easy tasks. But achieving them may be the best safeguard of democracy.

如果你觉得这些前景令人担忧——如果你不喜欢生活在数字独裁或某种类似的社会退化形式中——那么你能做的最重要的贡献就是找到方法,防止过多的数据集中在少数人手中,并找到保持分布式数据处理比集中式数据处理更有效的方法,这不是一件容易的事,但实现这些目标可能是民主的最佳保障。

This article has been adapted from Yuval Noah Harari’s book, 21 Lessons for the 21st Century.

本文改编自尤瓦尔·诺亚·哈拉里的著作《 21世纪的21课》
 
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