我的报道比机器人写得好
One day last week at 9.29am I hunched nervously over my keyboard and prepared to do battle with an entity called Emma. We were each primed to write about the official UK employment data at 9.30am and file our stories to my editor. I was sure Emma would be quicker than me, but I really hoped I would be better.
最近，一天早晨9点29分，我弓着身子紧张地盯着键盘，准备与一台名为爱玛(Emma)的机器一决雌雄。我们都准备在9点30分撰写一篇有关英国官方就业数据的文章，然后把文章递交给我的编辑。我确定爱玛会比我速度快，但我真的希望我会写得更好。
Her creator, a start-up called Stealth, calls her an “autonomous artificial intelligence” designed to deliver professional services such as research and analysis. Since it is fashionable to predict that AI will supplant white-collar workers including journalists, I wanted to put it to the test.
她的创造者、名为Stealth的初创企业把她称作“自主人工智能”，旨在提供研究和分析等专业服务。如今，预测人工智能将取代白领员工（包括记者在）是件时髦的事，所以我希望测试一下。
Emma was indeed quick: she filed in 12 minutes to my 35. Her copy was also better than I expected. Her facts were right and she even included relevant context such as the possibility of Brexit (although she was of the dubious opinion that it would be a “tailwind” for the UK economy). But to my relief, she lacked the most important journalistic skill of all: the ability to distinguish the newsworthy from the dull. While she correctly pointed out the jobless rate was unchanged, she overlooked that the number of jobseekers had risen for the first time in almost a year.
爱玛确实速度很快：她12分钟就提交了，我用了35分钟。而且她的文笔比我预期的要好。她列举的事实正确，甚至包括了相关背景，例如英国退欧(Brexit)的可能性（不过，她认为这将“推动”英国经济的观点让人存疑）。但让我感到安慰的是，她缺乏最重要的新闻从业人员技能：从枯燥资料中提取有新闻价值的内容的能力。尽管她准确指出了失业率未变，但她忽视了求职者数量出现近一年来首次增加。
In truth, most people who work on artificial intelligence admit it is not going to make humans obsolete any time soon. It is simply not intelligent enough yet. What is beginning to happen, though, is more subtle but no less important. The lines are beginning to blur between work done by humans and that done by machines.
实际上，从事人工智能开发工作的多数人承认，它不会很快淘汰人类。它就是还不够聪明。现在开始发生的情况较为微妙，但也很重要。人类和机器执行的工作之间的界限开始变得模糊起来。
For some workers, this could be a boon. I could imagine a scenario where an entity like Emma could do rudimentary reports on repetitive data releases, then send them to a human editor to newsify and beautify. The Associated Press already uses a program called Automated Insights to write simple corporate results stories. In these cases, humans have the advantage: machines not obliterating them but taking over the boring bits of their jobs so they can spend more time on the creative or valuable parts.
对于一些工作者而言，这可能是件好事。我可以假设这样一幅场景：类似爱玛的一台机器可以就重复性的数据发布编写报道初稿，然后发送给人类编辑做成新闻并修饰语句。美联社(Associated Press)已经在使用一个名为Automated Insights的程序撰写简单的公司业绩报道。在这些情况下，人类具有优势：机器没有淘汰人类，而是取代了人类工作中乏味的部分，使人类能把更多时间花在有创意或有价值的工作上。
But not all humans are moving up the value chain. There are some boring tasks at which machines are very bad. An army of low-paid people are quietly doing them instead.
但并非所有人都在向价值链上方移动。有一些枯燥的工作，机器做得非常糟糕。很多低薪人员在默默地承接这些工作。
Take the workers on Amazon’s Mechanical Turk, a site run by the online retailer where “requesters” pay “Turkers” to do simple microtasks that are tricky for machines but easy (if dull) for humans: transcribing audio clips; tagging photos with relevant keywords; copying photocopied receipts into spreadsheets. Amazon calls these “human intelligence tasks”, or HITs, and they tend to pay a few cents apiece. The name Mechanical Turk comes from a fake chess-playing machine from the 18th century: while it looked like an automaton, a person was secretly hiding inside.
以亚马逊(Amazon)土耳其机器人(Mechanical Turk)的工作者为例，这是该在线零售商经营的一个网站，让“请求者”付费给“土耳其工人”(Turkers)执行一些简单的小任务，这些任务对于机器来说很难，但对人类而言却相当容易（只是些枯燥）：把录音整理成文字记录；为照片贴上相关关键词作为标签；把复印的收据录入电子表格。亚马逊称之为“人类智能任务”，往往每个任务付费几美分。Mechanical Turk的名字来源于18世纪一台虚假的下棋机器：这台机器看上去是自动化，其实有真人藏在机器内部。
Pinterest is a good example of a company that uses sites like this. One developer explains in a recent blog how it uses “crowdworkers” to evaluate the appropriateness of the “trending searches” generated by its computers. Humans are still better at making these judgments than machines. “We’ve built ‘artificial’ artificial intelligence,” she concluded.
Pinterest就是一个公司利用这类网站的很好例子。一位开发员在最近一篇博文中解释了如何利用“众包工作者”评估电脑生成的“趋势搜索”是否合适。人类仍比机器更擅长做出这些评判。她得出结论称：“我们打造了‘人为’的人工智能。”
Some of the new chatbot and AI services also have people hiding inside: “humans pretending to be robots pretending to be humans”, as Bloomberg put it in a recent exposé. These people often review and edit AI-generated responses before they are sent.
正如彭博(Bloomberg)最近在一篇披露内幕的报道中所言，一些新的聊天机器人和人工智能服务也有人类藏在里面：“人类假装是机器人，再由机器人假装人类”。这些人往往会在由人工智能生成的回复被发送之前对其进行编审。
What about Emma? Is there a human lurking behind her? Shaunak Khire, co-founder of Stealth, says Emma has a team of human “trainers” but insists the output is all her own.
爱玛呢？有人藏在她身后吗？Stealth联合创始人Shaunak Khire表示，爱玛拥有一个由人类“教练”组成的团队，但他坚称，她是完全独立完成工作的。
It is always going to be hard for laypeople using these services to know for sure.
使用这些服务的外行人要确定这点总是很难。
Jeff Bigham, assistant professor at Carnegie Mellon University’s Human-Computer Interaction Institute, works as an adviser to Emma’s creators. He wants to find ways to make crowdwork less mindless and more fulfilling; for example, by making it a means to acquire skills. He asks himself: “What would make me proud to have my daughter grow up to be a crowdworker?” Even then, it is not clear how long this sort of work will last.
卡内基梅隆大学(Carnegie Mellon University)人机交互研究所(Human-Computer Interaction Institute)助理教授杰夫•比格姆(Jeff Bigham)是爱玛创造者的顾问。他希望找到让众包工作不那么机械而更有成就感的方法；比如让它成为一种获取技能的方式。他问自己：“有什么能让我因为自己的女儿长大后成为一名众包工作者而感到骄傲呢？”尽管那样，我们不清楚这类工作会持续多久。
He explains that when humans perform tasks that machines cannot yet do, they create an exhaust of “training data” from which AI can learn. In other words, all those crowdworkers and chatbot editors are working steadily towards their own obsolescence.
他解释道，当人类执行机器尚无法执行的任务时，他们会产生海量“培训数据”，人工智能可从中学习。换句话说，所有这些众包工作者和聊天机器人编辑天天在为淘汰自己工作着。
Should you welcome or fear the rise of intelligent machines? That depends on whether they will be working for you, or you will be working for them.
你是应该欢迎还是担心智能机器的崛起呢？这取决于他们将为你工作还是你将为他们工作。
