How to Prepare the Next Generation for Jobs in the AI Economy

在大多數(shù)人眼中，自動(dòng)駕駛汽車、語音助手和其他人工智能技術(shù)都具有革命性的意義。然而對于下一代來說，這些事物將成為司空見慣的事情。人工智能對于他們來說只不過是一個(gè)工具。在很多情況下，人工智能將成為他們的工作助手及其生活中常見的事物。

Most of us regard self-driving cars, voice assistants, and other artificially intelligent technologies as revolutionary. For the next generation, however, these wonders will have always existed. AI for them will be more than a tool; in many cases, AI will be their co-worker and a ubiquitous part of their lives.

要讓下一代學(xué)會(huì)有效地使用人工智能和大數(shù)據(jù)，了解其內(nèi)在的局限性，并打造更好的平臺和更智能的系統(tǒng)，我們現(xiàn)在就應(yīng)采取行動(dòng)。這意味著我們須對小學(xué)教育進(jìn)行一定的調(diào)整，并對早應(yīng)該調(diào)整的中學(xué)計(jì)算機(jī)科學(xué)教育進(jìn)行大刀闊斧的改革。

If the next generation is to use AI and big data effectively – if they’re to understand their inherent limitations, and build even better platforms and intelligent systems — we need to prepare them now. That will mean some adjustments in elementary education and some major, long-overdue upgrades in computer science instruction at the secondary level.

例如，想想孩子們?nèi)缃袢绾闻c人工智能和自動(dòng)技術(shù)進(jìn)行互動(dòng)：人們可以對Siri說“展示穿橙色裙子名人的照片”，然后泰勒·斯威夫特（Taylor Swift）的照片在不到一秒鐘的時(shí)間內(nèi)便出現(xiàn)在手機(jī)上，這看上去像是變魔術(shù)，但很明顯，它跟魔術(shù)沒有關(guān)系。人們在設(shè)計(jì)人工智能系統(tǒng)時(shí)，會(huì)仔細(xì)地將一個(gè)問題分解為若干子問題，并讓這些子問題的解決方案能夠進(jìn)行相互溝通。在上述案例中，人工智能方案將語音截成若干小塊，并發(fā)送至云端，對它們進(jìn)行分析，以確定其可能的意思并將結(jié)果轉(zhuǎn)化為一系列搜索請求。然后云端會(huì)對搜索出來的數(shù)百萬個(gè)可能答案進(jìn)行篩選和排序。借助云端的可擴(kuò)展性，這一過程僅耗費(fèi)十幾毫秒的時(shí)間。

For example, consider how kids are currently interacting with AI and automated technologies: Right now, it might seem magical to tell Siri, “Show me photos of celebrities in orange dresses,” and see a photo of Taylor Swift?pop up on a smartphone less than a second later. But it’s clearly not magic. People design AI systems by carefully decomposing a problem into lots of small problems, and enabling the solutions to the small problems to communicate with each other. In this example, the AI program divides the audio into chunks, sends them into the cloud, analyzes them to determine their probable meaning and translates the result into a set of search queries. Then millions of possible answers to those queries are sorted and ranked. Thanks to the scalability of the cloud, this takes just a few dozen milliseconds.

這并不是什么復(fù)雜的事情，但它需要眾多用于解讀音頻的組件波形分析，辨別裙子的機(jī)器學(xué)習(xí)，信息保護(hù)加密等等。然而，這其中的很多組件都是數(shù)個(gè)應(yīng)用中反復(fù)使用的標(biāo)準(zhǔn)組件，它并不是一個(gè)孤僻的天才在車庫中獨(dú)自估搗出來的作品。發(fā)明這類技術(shù)的人必須有組建團(tuán)隊(duì)、開展團(tuán)隊(duì)合作的能力，并能夠整合由其他團(tuán)隊(duì)開發(fā)的解決方案。這些都是我們需要向下一代傳授的技能。

This isn’t rocket science. But it requires a lot of components – waveform analysis to interpret the audio, machine learning to teach a machine how to recognize a dress, encryption to protect the information, etc. While many are standard components that are used and re-used in any number of applications, it’s not something a solitary genius cooks up in a garage. People who create this type of technology must be able to build teams, work in teams, and integrate solutions created by other teams. These are the skills that we need to be teaching the next generation.

與此同時(shí)，隨著人工智能開始取代工作中的常規(guī)信息和手動(dòng)任務(wù)，我們需要著重培養(yǎng)人力有別于人工智能的特質(zhì)，即創(chuàng)造力、適應(yīng)性和人際交往能力。

Also, with AI taking over routine information and manual tasks in the workplace, we need additional emphasis on qualities that differentiate human workers from AI — creativity, adaptability, and interpersonal skills.

在小學(xué)階段，這意味著我們需要重點(diǎn)開展鼓勵(lì)解決問題的練習(xí)，并教育孩子們?nèi)绾芜M(jìn)行團(tuán)隊(duì)合作。令人感到欣慰的是，八年級對于探究式或項(xiàng)目式的學(xué)習(xí)有著濃厚的興趣，但我們很難知道有多少地區(qū)已開始采取這一方式。

At the elementary level, that means that we need to emphasize exercises that encourage problem solving and teach children how to work cooperatively in teams. Happily, there is a lot of interest in inquiry-based or project-based learning at the K-8 level, though it’s hard to know how many districts are pursuing this approach.

各階段的教育還應(yīng)更加重視道德教育。人工智能技術(shù)一直都面臨著道德上的困境。例如，如何消除自動(dòng)化決策所產(chǎn)生的種族、人種和性別歧視；無人駕駛汽車如何取舍乘車人與行人的生命等等。我們需要思維縝密的相關(guān)人士和程序員來完善這些決策流程。

Ethics also deserves more attention at every educational level. AI technologies face ethical dilemmas all the time — for example, how to exclude racial, ethnic, and gender prejudices from automated decisions; how a self-driving car balances the lives of its occupants with those of pedestrians, etc. — and we need people and programmers who can make well-thought-out contributions to those decision making processes.

我們并不是說要在小學(xué)設(shè)置編碼課程，盡管這樣做也沒有什么問題，尤其是在孩子們喜歡這門課程的情況下。諸如Snap!和Scratch這類語言是很有用的。但是孩子們可以在其教育的后期階段學(xué)習(xí)編碼。然而，在學(xué)習(xí)編程方面無需擔(dān)心這一理念會(huì)讓人產(chǎn)生誤解。隨著世界變得愈發(fā)數(shù)字化，計(jì)算機(jī)科學(xué)在文理科中的重要性不亞于寫作和數(shù)學(xué)。不管孩子們是否會(huì)成為計(jì)算機(jī)科學(xué)家，還是從事任何其他的職業(yè)，編程都有助于他們走得更遠(yuǎn)。這也是我們認(rèn)為為什么要在9年級設(shè)置計(jì)算機(jī)編程基礎(chǔ)課程的原因。

We’re not obsessed about teaching coding at the elementary levels. It’s fine to do so, especially if the kids enjoy it, and languages such as?Snap!?and?Scratch?are useful. But coding is something kids can pick up later on in their education. However, the notion that you don’t need to worry at all about learning to program is misguided. With the world becoming increasingly digital, computer science is as vital in the arts and sciences as writing and math are. Whether a person chooses to become a computer scientist or not, coding is something that will help a person do more in whatever field they choose. That’s why we believe a basic computer programming course should be required at the 9th?grade level.

美國僅有約40%的學(xué)校如今設(shè)立了編程課程，這些課程的品質(zhì)和嚴(yán)謹(jǐn)度參差不齊。參加計(jì)算機(jī)科學(xué)大學(xué)預(yù)修課考試的學(xué)生數(shù)量正在大幅增長，去年參加計(jì)算機(jī)科學(xué)大學(xué)預(yù)修課A考試的學(xué)生為5.8萬名，但是與30.8萬參加微積分大學(xué)預(yù)修課AB考試的人數(shù)相比，這一數(shù)字便會(huì)黯然失色。美國有三分之一的州在學(xué)生畢業(yè)時(shí)甚至都不計(jì)算計(jì)算機(jī)科學(xué)課程的學(xué)分。

Only about 40% of U.S. schools now teach programming?and the quality and rigor of these courses varies widely. The?number of students taking Advanced Placement exams in computer science is growing dramatically, but the 58,000 students taking the?AP Computer Science A (APCS-A) test?last year still?pales in comparison to the 308,000?who took the?AP Calculus AB?test.?A third of our states?don’t even count computer science course credits toward graduation requirements.

在這一方面，美國已被眾多的發(fā)達(dá)國家遠(yuǎn)遠(yuǎn)地拋在了后面。以色列已明確把計(jì)算機(jī)科學(xué)納入其大學(xué)預(yù)修課程。英國最近也通過了其Computing at School項(xiàng)目取得了不俗的成績。俄羅斯也在大踏步前進(jìn)。奧巴馬總統(tǒng)在2016年國情咨文中宣布了“全民計(jì)算機(jī)科學(xué)行動(dòng)計(jì)劃”，也算是朝著這一正確的方向邁出了遲來的一步。

The U.S. is woefully behind many of our peer nations.?Israel notably has integrated computer science into its pre-college curriculum. The UK has made good progress lately with its?Computing at School program?and?Germany and Russia have leapt ahead as well.?President Obama’s Computer Science for All initiative, announced in his 2016 State of the Union, was a belated step in the right direction.

在高中階段完善計(jì)算機(jī)科學(xué)課程不僅會(huì)讓學(xué)生受益，同時(shí)也有助于計(jì)算機(jī)科學(xué)的發(fā)展，因?yàn)樗軌蚬膭?lì)更多的學(xué)生以及不同學(xué)科的學(xué)生將計(jì)算機(jī)科學(xué)納入職業(yè)選項(xiàng)。盡管去年秋天幾乎近半數(shù)的一年級新生都是女生，但學(xué)習(xí)計(jì)算機(jī)科學(xué)專業(yè)的女性和少數(shù)種族數(shù)量仍未見增長。將智能融入系統(tǒng)，在無處不在的數(shù)據(jù)海洋中發(fā)現(xiàn)獨(dú)特的洞見是一個(gè)急需各行各業(yè)員工參與完成的任務(wù)。

Expanding computer science at the high school level not only benefits the students, but could help the field of computer science by encouraging more students — and a more diverse group of students — to consider computer science as a career. Though we were thrilled last fall when?almost half of our incoming first-year class at Carnegie Mellon?was female, the field of computer science is still?struggling?to increase the number of women and minorities. Engineering intelligence into systems, and finding insights in a ubiquitous sea of data, is a task that cries out for a diverse workforce.

然而，為了取得成功，我們必須改變編程課程的授課方式。我們大都仍在按照20世紀(jì)90年代的思維來教授編程課程，當(dāng)時(shí)，編程的細(xì)節(jié)（像Visual Basic）被視為計(jì)算機(jī)科學(xué)的核心。如果你能夠頑強(qiáng)地通過編程語言細(xì)節(jié)關(guān)，你會(huì)學(xué)到一些東西，然而這仍是個(gè)痛苦的過程，但它不應(yīng)該是這樣。編程是一個(gè)創(chuàng)造性的活動(dòng)，因此，開發(fā)一門有趣、生動(dòng)的編程課程是完全可行的。例如在紐約，“女童子軍”組織啟動(dòng)了一個(gè)項(xiàng)目，教授女孩子使用Javascript來創(chuàng)建和提升視頻效果，這是一項(xiàng)孩子們喜聞樂見的事情，因?yàn)樗苡腥?，而且和他們的生活息息相關(guān)。為什么我們的學(xué)校不照搬這一模式？

To be successful, however, it is critical that we update the way programming is taught. We’re too often teaching programming as if it were still the 90s, when the details of coding (think Visual Basic) were considered the heart of computer science. If you can slog through programming language details, you might learn something, but it’s still a slog — and it shouldn’t be. Coding is a creative activity, so developing a programming course that is fun and exciting is eminently doable. In New York City, for instance,?The Girl Scouts?have a program that teaches girls to use Javascript to create and enhance videos — an activity that kids already?want?to do because it’s fun and relevant to their lives. Why can’t our schools follow suit?

在9年級之后，我們認(rèn)為學(xué)校應(yīng)提供選修課程，例如機(jī)器人學(xué)、計(jì)算數(shù)學(xué)和計(jì)算藝術(shù)，以培養(yǎng)對成為計(jì)算機(jī)科學(xué)家感興趣，并有這方面天賦的學(xué)生，或那些未來需要使用電腦來提升其工作效率的學(xué)生。如今，很少有美國高中在開設(shè)備戰(zhàn)APCS-A考試所需的課程之余還提供其他課程，但我們也有一些非常成功的案例，例如紐約的Stuyvesant高中，以及達(dá)拉斯TAG（天才學(xué)校）這些學(xué)校都擁有敬業(yè)的、來自計(jì)算機(jī)科學(xué)專業(yè)或接受過此類培訓(xùn)的教職人員。

Beyond 9th?grade, we believe schools should provide electives such as robotics, computational math, and computational art to nurture students who have the interest and the talent to become computer scientists, or who will need computers to enhance their work in other fields. Few U.S. high schools now go beyond the core training necessary to prepare for the APCS-A exam, though we have a few stunning success stories — Stuyvesant High School in New York City, Thomas Jefferson High School for Science and Technology in Alexandria, Virginia, and TAG (The School for the Talented and Gifted) in Dallas, among others. These schools all boast committed faculty members who have a background or training in computer science.

我們還敦促高中數(shù)學(xué)部門減少對連續(xù)數(shù)學(xué)的關(guān)注，包括高級微積分，而是去更多地關(guān)注直接與計(jì)算機(jī)科學(xué)有關(guān)的數(shù)學(xué)，例如統(tǒng)計(jì)學(xué)、概率學(xué)、圖論和邏輯。這些將成為明日數(shù)據(jù)驅(qū)動(dòng)型勞動(dòng)力最實(shí)用的技能。

We also urge high school math departments to place less emphasis on continuous math, including advanced calculus, and more on the math that is directly relevant to computer science, such as statistics, probability, graph theory and logic. Those will be the most useful skills for tomorrow’s data-driven workforce.

主要的障礙在于，學(xué)校嚴(yán)重缺乏擁有計(jì)算機(jī)科學(xué)背景的教師。美國的科技公司可以在這一方面給予很大的幫助。例如，微軟發(fā)起了TEALS項(xiàng)目。在這一項(xiàng)目中，高中教師每周跟隨計(jì)算機(jī)專業(yè)人士學(xué)習(xí)數(shù)小時(shí)。然而，要教授上百萬名學(xué)生，我們需要數(shù)萬名的教師。今后，我們有必要進(jìn)一步加大這一方面的力度。在學(xué)術(shù)方面，得州大學(xué)在奧斯丁的UTech項(xiàng)目便提供了一種STEM教師的培訓(xùn)模式，目前已擴(kuò)張至21個(gè)州的44所大學(xué)以及哥倫比亞特區(qū)。

A major hurdle is that our schools face?a severe shortage of teachers?who are trained in computer science. This is where U.S. tech companies could help immensely. Microsoft, for instance, sponsors the?TEALS program, which pairs computer professionals with high school teachers for a few hours a week. But we need thousands of educators teaching millions of students. Even greater commitments will be necessary going forward. On the academic side, The University of Texas at Austin’s?UTeach program?is a model for preparing STEM teachers and has expanded to 44 universities in 21 states and the District of Columbia.

我們還需要投入更多的精力。在科學(xué)和數(shù)學(xué)方面，我們需要相關(guān)的政府標(biāo)準(zhǔn)，推動(dòng)12年級的計(jì)算機(jī)科學(xué)教育，并開發(fā)教科書、課程，以及在全國范圍內(nèi)提供訓(xùn)練有素、符合上述標(biāo)準(zhǔn)的計(jì)算機(jī)科學(xué)教師骨干力量。計(jì)算機(jī)科學(xué)教師協(xié)會(huì)一直是這一領(lǐng)域的領(lǐng)導(dǎo)者，它制定了一套標(biāo)準(zhǔn)框架和一系列臨時(shí)標(biāo)準(zhǔn)。

Much more is needed. As with science and math, we need governmental?standards driving K-12 computer science education, along with textbooks, courses and ultimately a highly trained national cadre of computer science teachers that are tied to those standards. The Computer Science Teachers Association has been a leader in this area,?promulgating a standards framework?and an interim set of standards.

從長期來看，了解下一代人如何理解以及與大數(shù)據(jù)和人工智能互動(dòng)是一筆能夠讓所有人都獲益的投資。

Investing in how the next generation understand and interacts with big data and AI is an investment that will pay off in the long run for all of us.

時(shí)青靖 | 編輯

大衛(wèi)·克斯比(David Kosbie),安德魯·摩爾(Andrew W. Moore),馬克·斯特里克(Mark Stehlik) ｜文

大衛(wèi)·克斯比是卡耐基梅隆大學(xué)計(jì)算機(jī)科學(xué)學(xué)院的副教學(xué)教授。安德魯·摩爾是卡耐基梅隆大學(xué)計(jì)算機(jī)科學(xué)學(xué)院的院長。馬克·斯特里克是卡耐基梅隆大學(xué)計(jì)算機(jī)科學(xué)學(xué)院的外聯(lián)事務(wù)副院長。