手把手带你读一篇《纽约客》谈人工智能的文章

在第1部分中，作者描绘了这样一幅画面：当人工智能强大到可以超越到人类之后，它们未必会感谢人类发明了它们。我们一开始培养人工智能是为了方便人们的生活，然而如果机器超越了人类呢？

来看看文章第1部分的精选句子吧：

A central tension in the field, one that muddies the timeline, is how “the Singularity”—the point when technology becomes so masterly it takes over for good—will arrive.  这句话大概说的是：在人工智能领域，有一个中心的争议点，就是那个“奇点”——科技将永久性地掌控一切的时刻——将会怎么到来。

The worrywarts’ fears, grounded in how intelligence and power seek their own increase, are icily specific. Once an A.I. surpasses us, there’s no reason to believe it will feel grateful to us for inventing it—particularly if we haven’t figured out how to imbue it with empathy. Why should an entity that could be equally present in a thousand locations at once, possessed of a kind of Starbucks consciousness, cherish any particular tenderness for beings who on bad days can barely roll out of bed? 人们对于坏结果的担忧是很具体的：一旦AI超越了人类，它并不会感激和欣赏人类——强大的AI可以同时存在于一千个地方，而脆弱的人类则可能因为心情不好而不想起床工作。

As we bask in the late-winter sun of our sovereignty, we relish A.I. snafus. The time Microsoft’s chatbot Tay was trained by Twitter users to parrot racist bilge. The time Facebook’s virtual assistant, M, noticed two friends discussing a novel that featured exsanguinate corpses and promptly suggested they make dinner plans. The time Google, unable to prevent Google Photos’ recognition engine from identifying black people as gorillas, banned the service from identifying gorillas. Smugness is probably not the smartest response to such failures. 现实中我们可以看见，人工智能时常搞砸事情。2016年3月份，微软开发的Twitter聊天机器人Tay，被用户调教成了一个会发表种族主义和煽动性言论的恶棍；Facebook开发的虚拟助手M，在两位用户讨论涉及尸体的小说情节的时候，冷不丁提醒他们需要准备晚餐的日程；Google的图片识别算法，甚至将黑色人种识别为大猩猩。但是，这些糗事并不是人类沾沾自喜的理由，因为超人工智能将有寻找创造性的解法。

现在去试试阅读第1部分吧！读得比较慢也没关系，毕竟是一个学习的过程。

在第2部分，作者认为即便现在的人工智还有不可避免的缺陷，但它已经是生活中不可或缺的一部分了，无论我们有没有意识到。辩证地来说，人类和机器的关系是相辅相成的。

来看看文章第2部分的精选句子吧：

Artificial intelligence has grown so ubiquitous—owing to advances in chip design, processing power, and big-data hosting—that we rarely notice it. We take it for granted when Siri schedules our appointments and when Facebook tags our photos and subverts our democracy. Computers are already proficient at picking stocks, translating speech, and diagnosing cancer, and their reach has begun to extend beyond calculation and taxonomy. A Yahoo!-sponsored language-processing system detects sarcasm, the poker program Libratus beats experts at Texas hold ’em, and algorithms write music, make paintings, crack jokes, and create new scenarios for “The Flintstones.” ……AlphaGo demonstrated a command of pattern recognition and prediction, keystones of intelligence. You might even say it demonstrated creativity. 人们还是习惯了在人工智能包围的生活中。我们呼喊Siri帮我们做事情，用软件帮我们分析股市，翻译外语，诊断癌症等等，机器的能力早已超越了算数和分类。直到AlphaGo赢得了比赛，人们才意识到，AlphaGo所展现的认知和预测能力，在某种程度上已经可以等同于人类的“创造力”了。

In 1988, the roboticist Hans Moravec observed, in what has become known as Moravec’s paradox, that tasks we find difficult are child’s play for a computer, and vice-versa: “It is comparatively easy to make computers exhibit adult-level performance in solving problems on intelligence tests or playing checkers, and difficult or impossible to give them the skills of a one-year-old when it comes to perception and mobility.” 人工智能看上去如此先进，那它是否处处都做得好呢？ 作者介绍了莫拉维克悖论（Moravec’s paradox），来阐述人类智慧和人工智能在同等难度问题处理上的差异。人工智能看似能在短暂时间做出高端的精密计算，但人类的直觉和无意识的技能，却不是人工智能一时半会儿能够掌握的。比如说一岁小孩可以在分秒中判断一幅图片并作出相应的反应，而让机器做出判断，则需要通过及其复杂的程序。

Although robots have since improved at seeing and walking, the paradox still governs: robotic hand control. Some argue that the relationship between human and machine intelligence should be understood as synergistic rather than competitive. In “Human + Machine: Reimagining Work in the Age of AI,” Paul R. Daugherty and H. James Wilson, I.T. execs at Accenture, proclaim that working alongside A.I. “cobots” will augment human potential. Dismissing all the “Robocalypse” studies that predict robots will take away as many as eight hundred million jobs by 2030, they cheerily title one chapter “Say Hello to Your New Front-Office Bots.” Cutting-edge skills like “holistic melding” and “responsible normalizing” will qualify humans for exciting new jobs such as “explainability strategist” or “data hygienist.” Even artsy types will have a role to play, as customer-service bots “will need to be designed, updated, and managed. Experts in unexpected disciplines such as human conversation, dialogue, humor, poetry, and empathy will need to lead the charge.” 鉴于人工智能目前还有诸多短板，有人提出，也许未来人类与人工智能的关系不一定是相互压制的，而是相互促进的。诸如“机器将会取代人类工作”的言论，说不定也会变成“机器能够更好促进人类工作”这样的想法。

现在去试试阅读第2部分吧！

既然我们会依赖机器，那怎么测试机器的智能性呢？第3部分作者介绍了一个传统的方法：图灵测试（Turing Test）。在图灵测试中，一个人通过装置向两个被测试者（人和机器）随意提问，根据被测试者的回答，如果那个人不能确认被测试者是人还是机器，则被认为机器具有人工智能。不过，仅用这个方法来验证人工智能，还需要斟酌一番。