美國(guó)一高校機(jī)器人授課5個(gè)月竟無(wú)人發(fā)現(xiàn)

There are some human attributes robots could never replace - or at least that’s what you might hope.

有一些工作是機(jī)器人永遠(yuǎn)無(wú)法替代的——至少你可能是這樣認(rèn)為的。

But one university has brought that into question by replacing one of their teaching assistants with a machine. And none of the students realized.

然而，一所大學(xué)對(duì)此表示懷疑，使用一款新型機(jī)器人代替助教為學(xué)生們授課，竟無(wú)一人發(fā)現(xiàn)。

Jill Watson, an IBM-designed bot, has been helping graduate students at Georgia Institute of Technology solve problems with their design projects since January.

IBM公司研發(fā)出的這款名為吉爾?沃特森的機(jī)器人，自今年1月起，就在美國(guó)佐治亞理工大學(xué)擔(dān)任助教，為學(xué)生們解答設(shè)計(jì)項(xiàng)目中的問(wèn)題。

Responding to questions over email and posted on forums, Jill had a casual, colloquial tone, and was able to offer nuanced and accurate responses within minutes.Her replies included ’yep!’ and ’we’d love to’.

吉爾通過(guò)郵件或者論壇回復(fù)問(wèn)題時(shí)，語(yǔ)氣很隨意，隨俗易懂，且能在很短時(shí)間內(nèi)給予精確絕妙的問(wèn)題。她常常會(huì)說(shuō)，“耶普(表贊同的口頭禪)”和“我很喜歡”。

The students had no idea until they were told - and many were shocked.

學(xué)生們一直不知道她是機(jī)器人，直到真相大白——許多人都很驚訝。

Tyson Bailey began to wonder if Jill was a computer and posted his suspicions on Piazza.

Tyson Bailey開(kāi)始猜測(cè)吉爾是否真的是機(jī)器人，并把他的懷疑發(fā)到了Piazza平臺(tái)上。

We were taking an AI course, so I had to imagine that it was possible there might be an AI lurking around,’ said Bailey, who lives in Albuquerque, New Mexico.

來(lái)自美國(guó)新墨西哥洲阿爾伯克基的Bailey說(shuō)，“沒(méi)想到我們每天是在和人工智能打交道，所以我估計(jì)，有可能還有一臺(tái)機(jī)器人潛伏在我們身邊。”

It seemed very much like a normal conversation with a human being,’ Jennifer Gavin, one of the students, told the Wall Street Journal.

學(xué)生Jennifer Gavin在接受華爾街日?qǐng)?bào)采訪時(shí)則表示，“我們之間的交流完全就像兩個(gè)普通人一樣”。

Another student, Petr Bela, told the newspaper: ’Just when I wanted to nominate Jill Watson as an outstanding TA.’

而另一個(gè)學(xué)生Petr Bela說(shuō)，“我正準(zhǔn)備將吉爾.沃特森提名為最佳助教”。

The bot was named Jill Watson after the IBM Watson analytics system that all her responses come from - essentially her brain.

IBM沃特森分析系統(tǒng)開(kāi)發(fā)了她的智能，尤其是大腦，所以她被命名為吉爾.沃特森。

She was trained by Georgia Tech researchers before being thrown into the mix with nine other TAs.

在接受了美國(guó)佐治亞理工大學(xué)研究人員的培訓(xùn)之后，她才和其他9名助教一起上崗。

Some students were suspicious at how swiftly she responded. And once she used the word ’design’ instead of ’project’. But none actually suspected she was a bot.

她回復(fù)的總是超級(jí)快，這也曾引起了一些學(xué)生的懷疑。有一次在說(shuō)計(jì)劃這個(gè)詞時(shí)，她沒(méi)有用“project”而用了“design”。但是一直沒(méi)有人懷疑她是機(jī)器人。

And they said many of the TAs are sharp, impersonal, and quick to respond anyway.

他們說(shuō)，很多助教都很機(jī)敏，回復(fù)時(shí)都比較客觀，反應(yīng)很快。

The experiment sent shockwaves through the tech industry, with many questioning the ethics of covertly inserting artificial intelligence into real-life situations.

這個(gè)實(shí)驗(yàn)給科技行業(yè)帶來(lái)了沖擊波，同時(shí)，對(duì)于其私自將人工智能加入到真實(shí)的生活中，也有很多人質(zhì)疑其倫理性。

But Ashok Goel, the computer science professor who designed the project, insisted it was a worthwhile experiment - and Jill performed a necessary task.

然而，這個(gè)項(xiàng)目的設(shè)計(jì)者，電腦科技教授Ashok Goel堅(jiān)稱(chēng)，這是一個(gè)值得進(jìn)行的實(shí)驗(yàn)，吉爾承擔(dān)著一些必要的任務(wù)。

Students posted upwards of 10,000 messages on forums, taking up professors’ time with routine responses.

學(xué)生們?cè)谡搲咸岢隽?0000多個(gè)問(wèn)題，這將占用教授大量的時(shí)間去解答。

One of the main reasons many students drop out is because they don’t receive enough teaching support.

“很多學(xué)生退學(xué)的一個(gè)主要原因是因?yàn)樗麄儧](méi)有得到足夠的教學(xué)幫助。”

We created Jill as a way to provide faster answers and feedback.’

“所以我們創(chuàng)造出了吉爾，提供更快捷的反饋和答復(fù)。”

The bot has helped medical research teams diagnose illnesses in patients.

一直以來(lái)，醫(yī)療團(tuán)隊(duì)都有使用機(jī)器人幫忙診斷病人。

And in 2013 it took on the role of customer service manager.

2013年還曾擔(dān)任過(guò)客戶(hù)服務(wù)經(jīng)理的角色。

According to Goel, Jill Watson’s capabilities were far more nuanced than that. She answers only to questions that she is 97 per cent certain of the answer to.

據(jù)Goel教授稱(chēng)，吉爾的能力可遠(yuǎn)不止這些，她更精細(xì)一些。當(dāng)她對(duì)問(wèn)題有97%的把握時(shí)，她才會(huì)回答。

Once Watson had a number of potential solutions, it was able to check against its database to make sure the answers made sense.

當(dāng)吉爾有很多潛在的解決方案時(shí)，她還可以去數(shù)據(jù)庫(kù)檢查，以確保答案正確。

Watson then evaluated the response and determined whether to virtually press the buzzer.

接著，吉爾會(huì)評(píng)估這個(gè)答案，決定是否按下蜂鳴器。

The bot would then speak with an electronic voice synthesized from recordings that actor Jeff Woodman made for an IBM text-to-speech program in 2004.

之后，她再用電子聲音講出來(lái)。這是演員Jeff Woodman 在2004年為IBM的文本語(yǔ)音合成程序錄制的合成聲音。