外刊晨读
2018 年 年 5 月 月 15 日
Artificial Intelligence in Business
商业中的人工智能
GrAIt Expectations
远大前程
LIE DETECTORS ARE not widely used in business, but Ping An, a Chinese
insurance company, thinks it can spot dishonesty. The company lets customers apply
for loans through its app. Prospective borrowers answer questions about their income
and plans for repayment by video, which monitors around 50 tiny facial expressions
to determine whether they are telling the truth. The program, enabled by artificial
intelligence (AI), helps pinpoint customers who require further scrutiny.
The path ahead is exhilarating but perilous. Around 85% of companies think AI will
offer a competitive advantage, but only one in 20 is “extensively” employing it today,
according to a report by MIT’s Sloan Management Review and the Boston Consulting
Group. Large companies and industries, such as finance, that generate a lot of data,
tend to be ahead and often build their own AI-enhanced systems. But many firms will
choose to work with the growing array of independent AI vendors, including cloud
providers, consultants and startups.
This is not just a corporate race but an international one, too, especially between
America and China. Chinese firms have an early edge, not least because the
government keeps a vast database of faces that can help train facial-recognition
algorithms; and privacy is less of a concern than in the West.
There will be plenty of opportunities to stumble. One difficult issue for companies
will be timing. Roy Bahat of Bloomberg Beta, a venture-capital firm, draws a
parallel between now and the first dotcom boom of the late 1990s: “Companies are
flailing to figure out what to spend money on.” If they invest huge sums in AI early
on, they run the risk of overcommitting themselves or paying large amounts for
worthless startups, as many did in the early days of the internet. But if they wait too
long, they may leave themselves open to disruption from upstarts, as well as from
rivals that were quicker to harness technology.
Mar 31st, 2018
The Economist《经济学人》
译文
测谎仪并未在企业中广泛应用，但中国平安保险公司相信自己能探测谎言。
这家公司让客户通过它的一款应用程序来申请贷款。未来的贷款人在视频中回答
有关收入和还款计划的问题。视频会监测他们的大概 50 个细微面部表情，判断
他们是否在说真话。这套人工智能（AI）驱动的程序帮助筛查出需要进一步审核
的客户。
前路令人振奋却也危险重重。根据麻省理工学院的《斯隆管理评论》和波士
顿咨询集团联合撰写的报告，约 85％的企业认为 AI 将带来竞争优势，但只有 5％
的公司正在“广泛”地使用它。生成大量数据的大企业和金融等行业往往走在前
头，常常建立自己的 AI 增强系统。但许多企业会选择与队伍不断扩大的独立 AI
供应商合作，包括云供应商、咨询公司和创业公司等。
这不仅是一项企业竞赛，也是一场国际竞逐——尤其在中美之间。中国企业
有一个先发优势，这主要是因为中国政府拥有一个庞大的人脸数据库，可以用来
训练面部识别算法。而且，与西方相比，中国人对隐私也不那么关切。
跌跤的机会很多。企业面临的难题之一是对时机的把握。风险投资公司
Bloomberg Beta 的罗伊•巴哈特（Roy Bahat）把眼下的状况比作上世纪 90 年代末
的首个互联网泡沫期：“对于该往哪儿投钱，企业无所适从。”如果它们早早地在
AI 上投入巨资，就要冒着对一文不值的创业公司过度依赖或为之浪费大笔金钱
的风险，就像互联网早期许多公司的经历那样。但如果它们等得太久，又有可能
把自己置于被市场新贵颠覆的境地，还可能被更快掌握了新技术的竞争对手冲击。
背景介绍
Dotcom Boom 是指 1995 年至 2000 年期间出现的巨大互联网投资泡沫，在
此期间各种互联网初创公司市值飙涨，人们对“.com”和“e 字母打头”的公司
疯狂投资，以获取巨额利益，这在当时成为可能。股价的飙升和买家炒作的结合，
以及风险投资的广泛利用，使得这些企业摒弃了标准的商业模式，大部分缺乏切
实可行的计划和管理能力。直到约 2000，2001 年，许多公司都面临破产，互联
网行业的繁荣也就宣告终结。
单词
spot [spɒt]
vt. 认出，发现
例：
If you spot any mistakes in the book just mark them out.
如果你发现书中有错误，请标出来。
monitor [ˈmɒnɪtər]
vt. 监控，监测
例：
The CIA had been closely monitoring their activities.
中央情报局密切地监视着他们的活动。
pinpoint [ˈpɪnpɔɪnt]
vt. 准确指出，确定
例：
He was able to pinpoint the precise location of the village.
他能准确找出那个村庄的位置。
scrutiny [ˈskruːtəni]
n. 审查
例：
But it takes collective scrutiny and acceptance to transform a discovery claim into a
mature discovery.
但是将一项发现的申明转变为一项成熟的发现是需要集体的审查和接受的。
（2012 年考研英语一阅读理解 Part A Text 3）
exhilarating [ɪɡˈzɪləreɪtɪŋ]
adj. 令人兴奋的
例：
My first bungee jumping was an exhilarating experience.
我第一次蹦极的经历很令人兴奋。
perilous [ˈperələs]
adj. 非常危险的
例：
It was a perilous journey.
那是一次冒险的旅程。
array [əˈreɪ]
n. 一系列，一批，大量
例：
There was a vast array of colours to choose from.
有各种各样的颜色可供选择。
vendor [ˈvendər]
n. 供应商，厂商
例：
The company has signed a partnership agreement with Chinese software vendor.
这个公司与中国的一家软件供应商签署了一份合作协议。
algorithm [ˈælɡərɪðəm]
n. 算法
例：
An algorithm is a list of steps to follow in order to solve a problem.
算法是用来解决特定问题的一系列步骤。
stumble [ˈstʌmbl]
vi. 绊倒
例：
She stumbled over a log.
她被一块木头绊了一跤。
draw a parallel
作对比
例：
It would be easy to draw a parallel between the two cultures.
将这两种文化作个比较很容易就会发现二者的相似之处。
boom [buːm]
n. 繁荣
例：
He made a fortune during the property boom.
在房地产繁荣时期他赚了大钱。
flail [fleɪl]
vi. & vt. 挥动，胡乱摆动
例：
His arms were flailing in the air.
他的双臂在空中胡乱挥舞着。
disruption [dɪsˈrʌpʃn]
n. 毁坏
例：
But today, a disruption to family fortunes can no longer be made up with extra
income from an otherwise-stay-at-home partner.
但如今，家庭财富的破坏再也不能由其他家庭成员的额外收入来弥补了。（2007
年考研英语阅读理解 Part A Text 3）
harness [ˈhɑːrnɪs]
vt. 利用，控制
例：
They are very interested in harnessing new sources of power.
他们对开发利用新能源非常感兴趣。
长难句
If they invest huge sums in AI early on, they run the risk of overcommitting
themselves or paying large amounts for worthless startups, as many did in the early
days of the internet.