Are Humans Actually More ‘Human’ Than Robots?

导读

这些年最火的话题莫过于“人工智能”,自从阿尔法狗赢了李世石,人们就在不停地猜想未来的世界,会变成什么样子。是不是回到家就有智能机器人做好的饭菜,所有的行程都由人工智能帮你安排好,你乘坐的所有轿车都是自动驾驶,这样的日子似乎离我们并不遥远。与此同时,也有不少人感到恐慌,担心人工智能抢走了工作,害怕程序错误带来的危害,骇客帝国里面的场景,似乎离我们也不遥远。是否应该畏惧科技?人工智能到底有没有危险?通过今天的这篇文章,我们可以好好探讨一下这个话题。

更多剧透

第一步:解决高频单词

empathy /'ɛmpəθi/

n. 感同身受;同感;共鸣

interpersonal /'ɪntɚ'pɝsnl/

adj. 人际的,人与人之间的

prophecy /'prɒfɪsɪ/

n. 预言

relate /rɪ'leɪt/

v. 与…有关

attribute /ə'trɪbjuːt/

v. 把…归因于

exclude /ɪk'sklʊd/

v. 排斥,排除

adhere /əd'hɪə/

v. 遵守,紧贴

notion /'nəʊʃən/

n. 想法

mimic /'mɪmɪk/

模仿,模拟

ease /iːz/

v. 减轻; 减缓

60p

第二步:精读重点段落

(Tips: 双击文中单词可以查释义并加入你的生词本哦)

[1] In a recent report, the Pew Research Center found that Americans are more worried than they are enthusiastic about automation technologies when it comes to tasks that rely on qualities thought to be unique to humans, such as empathy. They’re concerned that, in lacking certain sensibilities, robots are fundamentally limited in their ability to replace humans at those jobs; they don’t, according to the report, trust “technological decision-making.”

  • enthusiastic 热衷的; 热烈的
  • when it comes to 当提到;就……而论
  • rely on 依靠;仰仗;信任
  • empathy 感同身受;同感;共鸣
  • decision-making  决策

[3] But if being “human” means making thoughtful decisions and having strong interpersonal skills, as survey respondents indicated, how “human” are humans? It turns out that the inclination to exalt human qualities might be misguided—and that robots might actually be preferable in certain jobs that count on those qualities. If that’s indeed the case, education and training programs will have to take an honest look at how great humans actually are—lest fears of robots taking over become a self-fulfilling prophecy.

  • interpersonal 人际的;人与人之间的
  • inclination 意向
  • exalt 盛赞
  • count on 指望,依靠
  • lest 唯恐,以防
  • prophecy 预言

[4] Human drivers don’t seem all that “human” when it comes to thoughtful decision-making. Federal fatal-crash data show that despite reductions in the number of deaths due to distracted or drowsy driving, those related to other reckless behaviors—including speeding, alcohol impairment, and not wearing seatbelts—have continued to increase. Roughly 37,000 of last year’s fatal crashes were attributed to poor decision-making.

  • drowsy 昏昏欲睡的
  • related to 有关,相关
  • impairment (身体机能的) 损伤
  • attribute to 归功于

[8] These statistics complicate the notion that robots are inherently inferior when it comes to such tasks. But training and education programs seem to be focusing more on technical skills, like computer literacy ones, and that could make robots all the more grave a threat to employment. Eighty-five percent of respondents in the Pew report were in favor of limiting machines to performing primarily those jobs that are dangerous or unhealthy for humans—namely those in the construction sector, as well as those in realms such as agriculture and forestry. But people across sectors—not just those that rely on rote, physical labor—will see their jobs affected by technology given its ability to mimic human abilities.

  • notion 想法
  • inherently 内在的,固有的
  • inferior 较差的
  • forestry 林业学
  • rote  死记硬背
  • mimic 模仿

[9] Education and training can ease Americans’ worries. In a time of big data and LinkedIn, which has detailed information on which sectors of the economy are growing and shrinking, and which skills employers are looking for, training programs can help some people “upskill,” or learn additional skills critical to an evolving sector. Of course, training won’t be enough; the degree to which policymakers take seriously the threat of automation, and to what extent employers are forced to provide decent-paying jobs, mean that large-scale preparation is not guaranteed.

  • ease 减轻; 减缓
  • upskill (通过额外的培训)使技能提升
  • decent 像样的,得体的
85p

第三步:攻克必学语法

文章中的第一句就提到了

... Americans are more worried than they are enthusiastic about ...

一看到 than 大家就能想到“比较句”,这也是英语里最常见的一类句型。

关于比较句,首先大家要明确的是:它是一种特殊的并列句。不论是“more/less...than...”里面的“than”,还是“as...as...”里面第二个“as”,词性都是“并列连词”。

其次,如果你在书写比较句的时候,尽量不要省略相应的谓语动词。

Marry is more beautiful than Jenny.(玛丽比珍妮更漂亮)

这样的句子倒是不容易引起误解,但是如果以下这种情况,恐怕就容易让人产生误解了。

I like her more than you.

这说的到底是:我喜欢她,你也喜欢她,但是我比你更喜欢她;还是:我喜欢你,我也喜欢她,但是你俩比起来,我更喜欢她。这真是让人头疼。

如果你把相应的动词补全,就不容易让人产生误解了。比如

I like her more than you do(第一种意思)
I like her more than I like you(第二种意思)

关于比较句,我们还有很多需要注意的重点,想要了解更多,欢迎来听课呦!

100p

加分任务:精读全文

在之前的三步后,你已经完全具备了精读全文的能力。再多花半个小时,让你的学习效果达到120%!

查看/展开全文


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(Tips: 双击文中单词可以查释义并加入你的生词本哦)

Are Humans Actually More ‘Human’ Than Robots?

[1] In a recent report, the Pew Research Center found that Americans are more worried than they are enthusiastic about automation technologies when it comes to tasks that rely on qualities thought to be unique to humans, such as empathy. They’re concerned that, in lacking certain sensibilities, robots are fundamentally limited in their ability to replace humans at those jobs; they don’t, according to the report, trust “technological decision-making.”

  • enthusiastic 热衷的; 热烈的
  • when it comes to 当提到;就……而论
  • rely on 依靠;仰仗;信任
  • empathy 感同身受;同感;共鸣
  • decision-making  决策

[2] This skepticism tends to steer people away from using those technologies. Just under 60 percent of respondents said they wouldn’t ride in a driverless car (in part because they’re worried about ceding control over to machines) or use a robot caregiver (in part because there is no human touch or interaction). Seventy-six percent said they wouldn’t apply for a job that uses a computer program to select applicants, either.

  • steer away from 远离;避开
  • cede  割让; 让出 (领土、主权)
  • caregiver 看护者
  • in part 在某种程度上

[3] But if being “human” means making thoughtful decisions and having strong interpersonal skills, as survey respondents indicated, how “human” are humans? It turns out that the inclination to exalt human qualities might be misguided—and that robots might actually be preferable in certain jobs that count on those qualities. If that’s indeed the case, education and training programs will have to take an honest look at how great humans actually are—lest fears of robots taking over become a self-fulfilling prophecy.

  • interpersonal 人际的;人与人之间的
  • inclination 意向
  • exalt 盛赞
  • count on 指望,依靠
  • lest 唯恐,以防
  • prophecy 预言

[4] Human drivers don’t seem all that “human” when it comes to thoughtful decision-making. Federal fatal-crash data show that despite reductions in the number of deaths due to distracted or drowsy driving, those related to other reckless behaviors—including speeding, alcohol impairment, and not wearing seatbelts—have continued to increase. Roughly 37,000 of last year’s fatal crashes were attributed to poor decision-making.

  • drowsy 昏昏欲睡的
  • related to 有关,相关
  • impairment (身体机能的) 损伤
  • attribute to 归功于

[5] Humans aren’t necessarily better than robots at caregiving, either. The American Psychological Association in 2012 estimated that 4 million older Americans—or about 10 percent of the country’s elderly population—are victims of physical, psychological, or other forms of abuse and neglect by their caregivers, and that figure excludes undetected cases.

  • exclude 排除,排斥
  • undetected 未被发现的

[6] Nor do they inherently excel at interpersonal skills. Humans incessantly use “strategic emotions”—emotions that don’t necessarily reflect how they actually feel—to achieve social goals, protect themselves from perceived threats, take advantage of people, and adhere to work-environment rules.(短句的排比,很好看) Strategic emotions can help relationships but, if they’re detectable, they can harm them, too.

  • incessant 持续不断地
  • take advantage of 利用,利用(时机等)
  • adhere to 坚持,粘住

[7] As an example, Jonathan Gratch, the director of emotion and virtual human research at the University of Southern California’s Institute for Creative Technologies, pointed to customer-service representatives, who tend to follow a script when speaking with people. Because they rarely express genuine emotions, they aren’t, according to Gratch, “really being human.” In fact, these rules surrounding professional conduct make it easier to program machines to do that sort of work, especially when Siri and cailia are already collecting data on how people talk, such as their intonations and speech patterns. “There’s this digital trace you can treat as data,” he said, referring to the scripts on which customer-service reps rely, “and machines learn to mimic what people do in those tasks.”

  • sort of 有几分,到某种程度
  • intonation 语调; 声调
  • trace 痕迹,踪迹

[8] These statistics complicate the notion that robots are inherently inferior when it comes to such tasks. But training and education programs seem to be focusing more on technical skills, like computer literacy ones, and that could make robots all the more grave a threat to employment. Eighty-five percent of respondents in the Pew report were in favor of limiting machines to performing primarily those jobs that are dangerous or unhealthy for humans—namely those in the construction sector, as well as those in realms such as agriculture and forestry. But people across sectors—not just those that rely on rote, physical labor—will see their jobs affected by technology given its ability to mimic human abilities.

  • notion 想法
  • inherently 内在的,固有的
  • inferior 较差的
  • forestry 林业学
  • rote  死记硬背
  • mimic 模仿

[9] Education and training can ease Americans’ worries. In a time of big data and LinkedIn, which has detailed information on which sectors of the economy are growing and shrinking, and which skills employers are looking for, training programs can help some people “upskill,” or learn additional skills critical to an evolving sector. Of course, training won’t be enough; the degree to which policymakers take seriously the threat of automation, and to what extent employers are forced to provide decent-paying jobs, mean that large-scale preparation is not guaranteed.

  • ease 减轻; 减缓
  • upskill (通过额外的培训)使技能提升
  • decent 像样的,得体的

[10] Yet despite widespread interest in professional development and lifelong learning, Aaron Smith, an associate director at the Pew Research Center and co-author of the report, has found in his previous research that policymakers and workers express different motivations when they talk of the need for training. While there are some politicians who think about automation as a labor challenge, workers across the board are thinking more about globalization, Smith told me. People, he said, are not “necessarily thinking about that training and development as something that will help them fight off the machines.”

200p

empathy /'ɛmpəθi/

n. 感同身受;同感;共鸣

interpersonal /'ɪntɚ'pɝsnl/

adj. 人际的,人与人之间的

prophecy /'prɒfɪsɪ/

n. 预言

relate /rɪ'leɪt/

v. 与…有关

attribute /ə'trɪbjuːt/

v. 把…归因于

exclude /ɪk'sklʊd/

v. 排斥,排除

adhere /əd'hɪə/

v. 遵守,紧贴

notion /'nəʊʃən/

n. 想法

mimic /'mɪmɪk/

模仿,模拟

ease /iːz/

v. 减轻; 减缓

不要一时兴起,就要天天在一起

明天见!


下载音频

Are Humans Actually More ‘Human’ Than Robots?

[1] In a recent report, the Pew Research Center found that Americans are more worried than they are enthusiastic about automation technologies when it comes to tasks that rely on qualities thought to be unique to humans, such as empathy. They’re concerned that, in lacking certain sensibilities, robots are fundamentally limited in their ability to replace humans at those jobs; they don’t, according to the report, trust “technological decision-making.”

[2] This skepticism tends to steer people away from using those technologies. Just under 60 percent of respondents said they wouldn’t ride in a driverless car (in part because they’re worried about ceding control over to machines) or use a robot caregiver (in part because there is no human touch or interaction). Seventy-six percent said they wouldn’t apply for a job that uses a computer program to select applicants, either.

[3] But if being “human” means making thoughtful decisions and having strong interpersonal skills, as survey respondents indicated, how “human” are humans? It turns out that the inclination to exalt human qualities might be misguided—and that robots might actually be preferable in certain jobs that count on those qualities. If that’s indeed the case, education and training programs will have to take an honest look at how great humans actually are—lest fears of robots taking over become a self-fulfilling prophecy.

[4] Human drivers don’t seem all that “human” when it comes to thoughtful decision-making. Federal fatal-crash data show that despite reductions in the number of deaths due to distracted or drowsy driving, those related to other reckless behaviors—including speeding, alcohol impairment, and not wearing seatbelts—have continued to increase. Roughly 37,000 of last year’s fatal crashes were attributed to poor decision-making. 

[5] Humans aren’t necessarily better than robots at caregiving, either. The American Psychological Association in 2012 estimated that 4 million older Americans—or about 10 percent of the country’s elderly population—are victims of physical, psychological, or other forms of abuse and neglect by their caregivers, and that figure excludes undetected cases.

[6] Nor do they inherently excel at interpersonal skills. Humans incessantly use “strategic emotions”—emotions that don’t necessarily reflect how they actually feel—to achieve social goals, protect themselves from perceived threats, take advantage of people, and adhere to work-environment rules. Strategic emotions can help relationships but, if they’re detectable, they can harm them, too.

[7] As an example, Jonathan Gratch, the director of emotion and virtual human research at the University of Southern California’s Institute for Creative Technologies, pointed to customer-service representatives, who tend to follow a script when speaking with people. Because they rarely express genuine emotions, they aren’t, according to Gratch, “really being human.” In fact, these rules surrounding professional conduct make it easier to program machines to do that sort of work, especially when Siri and cailia are already collecting data on how people talk, such as their intonations and speech patterns. “There’s this digital trace you can treat as data,” he said, referring to the scripts on which customer-service reps rely, “and machines learn to mimic what people do in those tasks.”

[8] These statistics complicate the notion that robots are inherently inferior when it comes to such tasks. But training and education programs seem to be focusing more on technical skills, like computer literacy ones, and that could make robots all the more grave a threat to employment. Eighty-five percent of respondents in the Pew report were in favor of limiting machines to performing primarily those jobs that are dangerous or unhealthy for humans—namely those in the construction sector, as well as those in realms such as agriculture and forestry. But people across sectors—not just those that rely on rote, physical labor—will see their jobs affected by technology given its ability to mimic human abilities.

[9] Education and training can ease Americans’ worries. In a time of big data and LinkedIn, which has detailed information on which sectors of the economy are growing and shrinking, and which skills employers are looking for, training programs can help some people “upskill,” or learn additional skills critical to an evolving sector. Of course, training won’t be enough; the degree to which policymakers take seriously the threat of automation, and to what extent employers are forced to provide decent-paying jobs, mean that large-scale preparation is not guaranteed.

[10] Yet despite widespread interest in professional development and lifelong learning, Aaron Smith, an associate director at the Pew Research Center and co-author of the report, has found in his previous research that policymakers and workers express different motivations when they talk of the need for training. While there are some politicians who think about automation as a labor challenge, workers across the board are thinking more about globalization, Smith told me. People, he said, are not “necessarily thinking about that training and development as something that will help them fight off the machines.”

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