A recent study by Oxford university estimates that nearly half of all jobs in the US are at risk from automation and computers in the next 20 years. While advancing technologies have been endangering jobs since the start of the Industrial Revolution, this time it is not just manual posts: artificial intelligence — the so-called fourth industrial revolution — promises to change the shape of professional work as well.

牛津大学(Oxford University)最近的一项研究估计，美国近一半工作岗位在未来20年面临被自动化和电脑取代的风险。尽管自工业革命以来，先进技术一直在危及人类的工作岗位，但这一次波及的不仅仅是体力工作：人工智能（所谓的第四次工业革命）可能改变专业工作的形态。

For instance, lawtech is already proving adept at sorting and analysing legal documents far faster and more cheaply than junior lawyers can. Similarly, routine tasks in accounting are succumbing to AI at the expense of more junior staff.

例如，法律科技已被证明擅长整理和分析法律文件，其速度远远快于初级律师，而成本低得多。同样，例常的会计工作正让位于人工智能，造成更多初级员工失业。

This change is an opportunity to create new and better jobs. Paul Drechsler, who is president and chair of respectively the CBI employers’ organisation and Teach First, which recruits high-achievers into teaching, is enthusiastic about the future: “The fourth industrial revolution is the best opportunity that this country has had for decades to leapfrog” in terms of productivity and competitiveness. But he cautions that “the change is happening must faster than the education system”.

这种变化是创造新的、更好的工作岗位的机会。分别担任雇主组织英国工商业联合会(CBI)主席和Teach First（先教书吧）-该组织招募各行各业的高级人才去中小学教书-董事长的保罗.德雷舍勒(Paul Drechsler)对未来充满热情：就生产率和竞争力而言，“第四次工业革命是这个国家几十年来遇上的实现跨越式发展的最佳机会”。但他告诫称，“这种变化的速度将远远超过教育体系”。

The next generation will need a new set of skills to survive, let alone thrive, in an AI world. Literacy, numeracy, science and languages are all important, but they share one thing in common: computers are going to be far better than humans at processing these forms of explicit knowledge.

下一代人将需要掌握一套新的技能，才能在人工智能世界生存，更别提施展才华了。读写能力、计算能力、理科知识和外语都很重要，但它们有一个共同点：电脑在处理这些形式的显性知识方面将远远优于人类。

The risk is that the education system will be churning out humans who are no more than second-rate computers, so if the focus of education continues to be on transferring explicit knowledge across the generations, we will be in trouble.

风险在于，教育体系培养出的人比二流电脑强不了多少，因此如果教育的重点继续放在把显性知识传递给下一代上，我们就有麻烦了。

The AI challenge is not just about educating more AI and computer experts, although that is important. It is also about building skills that AI cannot emulate. These are essential human skills such as teamwork, leadership, listening, staying positive, dealing with people and managing crises and conflict.

应对人工智能挑战不仅关乎培养更多人工智能和电脑专家（尽管这很重要），还关乎构建人工智能无法效仿的技能。这些是不可或缺的人类技能，例如团队合作、领导能力、倾听、保持积极心态、与人打交道以及管理危机和冲突。

These are all forms of tacit knowledge, not explicit knowledge. They are know-how skills, not know-what skills. Know-what is easy to transmit across the generations, and is easy to measure. Know-how skills are hard both to transmit and to measure.

这些都是隐性知识（而非显性知识）形式。它们属于诀窍技能，而不是事实技能。事实技能很容易传给下一代，而且容易衡量。诀窍技能很难传递，也很难衡量。

The employability skills gap is already large, and AI will only make it larger. A McKinsey survey found that 40 per cent of employers cited lack of skills to explain entry-level vacancies in their companies. Sixty per cent said that even graduates were not ready for the world of work.

就业能力技能差距已然巨大，而人工智能只会使其更大。麦肯锡(McKinsey)的一项调查发现，40%的雇主在解释公司里初级职位的空缺时，把缺乏技能列为理由。60%的雇主表示，就连高校毕业生也没有为职场做好准备。

The scale of the current response in the UK does not match the challenge. University technical colleges, the brainchild of former education secretary Lord Baker, explicitly address employability, with a focus on developing engineers, technicians and scientists of the future. In the last academic year, just 1,955 18-year olds graduated from these schools; compared to the 770,000 18-year olds in the UK, that is a drop in the ocean.

英国目前的回应力度应对不了挑战。前教育大臣贝克勋爵(Lord Baker)设计的大学技术学院明确针对就业能力，侧重培养未来的工程师、技术员和科学家。在上一个学年里，只有1955名18岁青年从这类学校毕业；相比英国总共77万的18岁人口，这只是九牛一毛。

In a similar vein, “studio schools” started in 2010 with the intent of blending vocational and academic education with work experience. Of the 50 schools started, 16 have already announced plans to close. Both models are sufficiently different from traditional provision that they struggle to gain acceptance.

类似地，“工作室学校”出现在2010年，旨在把职业和学术教育与工作经验结合在一起。在已开办的50所学校中，有16所已宣布计划关闭。这两种模式都与传统学校有显著不同，这使它们难以获得认可。

The required revolution is unlikely to come from creating schools outside the mainstream. It will have to come from within, supporting all pupils, not just those who want a technical career.

我们需要的革命不太可能来自在主流以外创办的学校。它将不得不来自现有学校体制内部，支持所有学生，而不只是那些希望做技术工作的人。

Enabling Enterprise, a charity backed by employers including bank UBS, consultants PwC and supermarket Waitrose, aims to embed employability skills into the curriculum from the earliest years. For instance, five-year olds can learn teamwork with simple routines based on sharing and taking turns. Although the charity says its results look promising, it has reached just 275 schools so far.

投行瑞银(UBS)、咨询公司普华永道(PwC)和超市Waitrose等雇主支持的慈善组织Enabling Enterprise，力求从低龄开始把就业能力技能嵌入教学大纲。例如，5岁儿童可以学习基于分享和轮流的团队合作，以完成简单任务。尽管该慈善组织表示结果看上去大有希望，但它迄今只有275所合作学校。

Evaluation and league tables are a barrier to success — you get what you measure in education as much as you do in business. The schools accountability framework keeps changing, but is always some variation on measuring how well schools transfer know-what skills, especially English and maths. The Progress 8 framework, which assesses student progress in eight subjects, has no direct measure of employability skills.

评估和排行榜是成功的障碍：就像在商业领域一样，在教育领域，你会得到你衡量的东西。学校问责框架持续变化，但始终以衡量学校有多擅长于传授事实技能（特别是英语和数学）为主。评估学生8个科目成绩的Progress 8框架，就不直接衡量就业能力技能。

Tom Ravenscroft, chief executive of Enabling Enterprise, challenges this approach: “We are doubling down on the idea that if we get children to know things and regurgitate them in a certain way in an exam, then we are setting them up for success in life.”

Enabling Enterprise行政总裁汤姆.雷文斯克罗夫特(Tom Ravenscroft)对这种方法提出挑战：“我们正在强化这样一种观念：只要我们让孩子们吸收知识，然后在考试中以某种方式证明自己记住了知识，那么我们就让他们做好了取得人生成功的准备。”

Success depends on equipping the next generation with human skills that even AI cannot emulate: creativity, innovation, resilience, dealing with conflict, ambiguity and uncertainty. We are not ready for this. We have not even started to get ready.

成功取决于让下一代学习甚至连人工智能都无法效仿的人类技能：创造力；创新；弹性；处理冲突、模棱两可和不确定性。我们没有为此做好准备。我们甚至还没有开始做准备。

（来源：爱语吧）