Day 25: Computers: friend or foe
Monday
各位书友，今天我们一起阅读《Zero to One》第十二章MAN AND MACHINE的144-151页。
The future of computing is necessarily full of unknowns. It’s become conventional to see ever-smarter anthropomorphized robot intelligences like Siri and Watson as harbingers of things to come; once computers can answer all our questions, perhaps they’ll ask why they should remain subservient to us at all.
计算机运算的未来充满了未知。像Siri（苹果手机语言助理）和沃森这些预示着未来趋势的越来越高明的机器人智能，越来越普及；一旦计算机能回答我们所有问题，它们或许会问，为什么它们要完全屈从于我们？
思考问题：
COMPUTERS: FRIEND OR FOE?
计算机，朋友或仇敌？
欢迎各位书友留言，文字语音都可以，中文英文均不限。
您的每一条留言对于我们都很重要！*3
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01 COMPLEMENTARY BUSINESSES
人机互补之于企业
Complementarity between computers and humans isn’t just a macro-scale fact. It’s also the path to building a great business.
人类与计算机的互补不仅是宏伟现实，更是创立伟大事业的途径。
I came to understand this from my experience at PayPal. In mid-2000, we faced one huge problem: we were losing upwards of $10 million to credit card fraud every month. Since we were processing hundreds or even thousands of transactions per minute, we couldn’t possibly review each one—no human quality control team could work that fast.
在PayPal的经历使我明白了这一点。2000年年中，我们面临一个巨大难题：每月都因信用卡诈骗损失上千万美元。每分钟处理成百上千笔交易，因此不可能一一检查——任何质量控制团队都达不到这种速度。
So we did what any group of engineers would do: we tried to automate a solution.
因此我们做了任何工程师团队都会做的事情：采用自动化技术找到解决方案。
First, we took what we learned and wrote software to automatically identify and cancel bogus transactions in real time. But it quickly became clear that this approach wouldn’t work either: after an hour or two, the thieves would catch on and change their tactics. We were dealing with an adaptive enemy, and our software couldn’t adapt in response.
首先，利用研究结果，编写自动识别软件，实时取消诈骗交易。但措施并不奏效。因为一两个小时后，窃贼发现后就改变了策略。对手适应性很强，而我们的软件反应缓慢。
The fraudsters’ adaptive evasions fooled our automatic detection algorithms, but we found that they didn’t fool our human analysts as easily. Then we rewrote the software to take a hybrid approach: the computer would flag the most suspicious transactions on a well-designed user interface, and human operators would make the final judgment as to their legitimacy.
诈骗犯虽然躲过了我们的自动检测算法，但我们发现，他们不能轻易骗过人类分析师。随后，我们用混合策略重写了软件：程序将可疑的交易标记在设计好的用户界面上，然后人工审核其合法性。
Thanks to this hybrid system—we named it “Igor,” after the Russian fraudster who bragged that we’d never be able to stop him. The FBI asked us if we’d let them use Igor to help detect financial crime.
多亏了这个混合系统，我们抓住了那个吹嘘自己无人能敌的俄罗斯窃贼，所以我们给这套系统起了个俄罗斯的名字——“Igor”。美国联邦调查局来问我们是否愿意出借Igor，以协助他们侦测金融犯罪。
If humans and computers together could achieve dramatically better results than either could attain alone, what other valuable businesses could be built on this core principle?
人机结合比单打独斗效果显著，那么在此核心基础上可建立什么有价值的事业呢？
America’s two biggest spy agencies take opposite approaches: The Central Intelligence Agency isrun by spies who privilege humans. The National Security Agency is run by generals who prioritize computers. CIA analysts have to wade through so much noise that it’s very difficult to identify the most serious threats. NSA computers can process huge quantities of data, but machines alone cannot authoritatively determine whether someone is plotting a terrorist act.
美国两大最大的情报机构使用的方法截然不同：中央情报局倾向于用人，而国家安全局倾向于使用计算机。中央情报局的分析师要排除的干扰太多，很难识别严重的威胁。国家安全局的计算处理数据的能力很强，但机器自己不能鉴别是否有人在策划恐怖行动。
Palantir aims to transcend these opposing biases: its software analyzes the data the government feeds it—phone records of radical clerics in Yemen or bank accounts linked to terror cell activity, for instance—and flags suspicious activities for a trained analyst to review.
帕兰提尔致力于克服这两种缺陷：运用帕兰提尔的软件分析政府提供的数据（比如，也门极端主义教士的通话记录、与恐怖活动关联的银行账户），然后表示出可疑活动，供训练有素的分析师审核。
02 The Ideology of Computer Science
对计算机科学的认识
Why do so many people miss the power of complementarity?
为什么如此多的人忽视与计算机互补的力量？
The buzzword that epitomizes a bias toward substitution is “big data.” Today’s companies have an insatiable appetite for data, mistakenly believing that more data always creates more value. But big data is usually dumb data.
体现机器会取代人类的倾向的流行语是“大数据”。如今的公司对数据情有独钟，它们错误地认为数据越多，能创造的价值就越多。但大数据通常都是沉默的资料。
We have let ourselves become enchanted by big data only because we exoticize technology. We’re impressed with small feats accomplished by computers alone, but we ignore big achievements from complementarity because the human contribution makes them less uncanny. Watson, Deep Blue, and ever-better machine learning algorithms are cool. But the most valuable companies in the future won’t ask what problems can be solved with computers alone. Instead, they’ll ask: how can computers help humans solve hard problems?
我们痴迷于大数据仅仅是因为觉得科技很奇特。我们为计算机单独取得的一些小成就而惊叹，却忽视了人类在计算机的辅助下取得的巨大进步，因为人类的参与淡化了其神秘性。沃森、深蓝电脑和越来越厉害的算法虽然很酷，但未来最有价值的公司肯定不是靠计算机单独解决问题，而是关注计算机如何才能帮助人类解决问题。
03 EVER-SMARTER COMPUTERS: FRIEND OR FOE?
聪明的计算机：是敌，还是友
Even if strong AI is a real possibility rather than an imponderable mystery, it won’t happen anytime soon: replacement by computers is a worry for the 22nd century.
即使强大的人工智能不是不可预测的谜团，而有真是存在的可能，那个时代也不会很快到来：被计算机取代是22世纪人类该担忧的问题。
The logical endpoint to this substitutionist thinking is called “strong AI”: computers that eclipse humans on every important dimension. Of course, the Luddites are terrified by the possibility. It even makes the futurists a little uneasy; it’s not clear whether strong AI would save humanity or doom it. Technology is supposed to increase our mastery over nature and reduce the role of chance in our lives; building smarter-than-human computers could actually bring chance back with a vengeance. Strong AI is like a cosmic lottery ticket: if we win, we get utopia; if we lose, Skynet substitutes us out of existence.
替代派思维的逻辑终点是“强大的人工智能”：计算机使得人类在每个重要领域黯然失色，当然，勒德分子被这种可能性吓坏了。这甚至让未来学家也心神不宁，因为还不确定强大的人工智能会拯救人类还是会毁灭人类。技术应该增加人类对自然的控制力，减少人类生活中的偶然性；建造智慧过人的计算机一定是利弊参半。强大的人工智能就像宇宙彩票：我们赢了，得到理想国；我们输了，被天网（Skynet）取代。
Indefinite fears about the far future shouldn’t stop us from making definite plans today. Luddites claim that we shouldn’t build the computers that might replace people someday; crazed futurists argue that we should. These two positions are mutually exclusive but they are not exhaustive: there is room in between for sane people to build a vastly better world in the decades ahead. As we find new ways to use computers, they won’t just get better at the kinds of things people already do; they’ll help us to do what was previously unimaginable.
对遥远未来的不确定的恐惧不应阻止我们现在制订明确的计划。勒德分子认为我们不应该制造未来可能取代人类的计算机，狂热的未来科学家则持相反的观点。这两种观点相互排斥，未来几十年，理智的人可以建设美好的世界。我们在计算机使用上的创新，不仅能够帮助人类做好已有工作，还能帮助人类做到之前不可想象的事情。
本月共读《Zero to One》英文版
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☞ 领读达人：刘亚南，英语共读负责人，85后
☞ 主播：熊叔，别人说我英语讲得像母语，是个美国人，我笑~谁说不出国门就学不会地道美语?，别人说我拥有TESOL国际教师资格证~，我笑~自己只是个教书的逗比小光头罢了。
☞ 设计：刘莹
☞ 编校：陈珺洁