A recent study by Oxford University estimates that nearly half of all jobs i

游客2023-12-28  22

问题     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. 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.
    This change is an opportunity to create new and better jobs. Paul Drechsler, who is president of the CBI employers’ organisation, 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". 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.
    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. 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. 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.
    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.

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答案     牛津大学最近的一项研究预计,在未来20年中,美国将近一半的工作岗位将极有可能被自动化和计算机所取代。尽管自工业革命以来,科学技术的不断进步一直危及着人类的工作岗位,但人工智能(所谓的第四次工业革命)影响的却不仅是体力工作,还可能会触及某些专业领域的工作模式。例如,经证实,“法律科技”已可以高效整理及分析法律文件,且其速度远高于初级律师,而成本却相对较低。同样,日常财会工作也正逐步让位于人工智能,造成更多低层员工失业。
    不过,此次变革也为开拓新的、更好的工作岗位创造了良机。保罗.德雷克斯勒 (Paul Drechsler)是英国工商业联合会(CBI)雇主组织主席,他对未来满腔热忱:
    就提升生产效率和竞争力而言,“第四次工业革命是我们国家数十年来遇到的、可以实现跨越式发展的绝佳机会”。不过,他也告诫说,“此次变革的速度将远远高于教育体系的发展速度”。仅仅要在人工智能世界生存,下一代人都需要掌握一整套全新的技能,更别提大展其才了。读写能力、数学知识、理工知识和多语能力都很重要,但这些知识和能力的相同之处在于:在处理此类显性知识时,电脑将远胜于人类。
    目前,我们面临的威胁在于,教育体系培育出的人才比次等电脑强不了多少,因此,如果依旧只注重把显性知识传递给下一代,我们就会身陷困境。要应对人工智能的挑战,培养更多人工智能和计算机专家固然重要,但这还不够,还需要培养人工智能无法效仿的能力,例如团队合作能力、领导能力、倾听他人的能力、保持积极心态的能力、与人沟通及应对危机和冲突的能力等,而这些都是人类不可或缺的能力。这些都是隐性知识,而非显性知识。它们属于“专有”技能,而非“表面”技能。“表面”技能可以代代相传。且易于衡量:“专有”技能则很难传授,也难以衡量。
    “个人就业能力”缺陷已然明显。而人工智能只会放大这一缺陷。麦肯锡公司(McKinsey)的一项调查显示,谈及公司里初级职位空缺的原因时,40%的雇主认为能力不足是一大原因:60%的雇主表示,高校毕业生的个人能力与职场需求还有差距。

解析     本文选自《金融时报》(Financial Times),文章第一部分从正反两方面提出人工智能对现有工种的影响。《金融时报》主要报道商业和财经新闻,旨在为读者提供全球性的经济商业信息、经济分析和评论。考题文字主题鲜明,逻辑缜密,首先基于牛津大学的研究以及法律、会计等行业的具体实例,指出在未来20年中,美国有近半数现有工种将受到自动化和计算机的威胁,进而,文章从另一个方面指出,人工智能的快速发展同样创造了新的工作机会。第二部分,基于上文所述人工智能对人类工作带来的影响,进一步分析了今后教育发展的方向和合格人才应具备的基本素养,同时通过数据指出人才短缺这一现实情况。整体而言,考题文本为商务类评论性报道,涉及工业革命和人工智能等背景知识和相关术语,文字表述简洁流畅,逻辑清晰,翻译时需考虑原文风格,做到术语表述精准,逻辑脉络清晰,文字表述自然流畅。
    第一段考查译者的篇章理解和长难句处理能力。第一句从牛津大学近期一项研究出发,点出文章主题,但并未直接使用“人工智能”作为关键词,因此,译者需要结合下文理解automation和computers的词义。第二句句式复杂,包含时间状语从句,同位语成分,需要译者解构、重构信息。另外,本句末尾处shape一词虽为常见词语,却需要译者结合前后文推测并确定词义。值得一提的是,第一段中也包含了“工业革命”这一文化信息,且该文化信息与后文关系密切,这考查的是译者的信息统筹能力。第一段最后提出两个具体例证,句式结构虽不复杂,但有些词语需要考虑斟酌,如adept,junior lawyer,succumb to等词汇和短语的理解和表达。
    第二段笔锋一转,指出人工智能快速发展带来的机遇,考查把握篇章整体逻辑脉络的能力。另外,本段中也考查了概数的处理,如decades抽象名词的处理,如productivity和competitiveness等。该段的难点还在于动词的处理,如survive,process等词。在考查词义选择能力的同时,本段中修辞性表达。leapfrog,high,achiever等词汇的翻译需要译者结合全文语体色彩把握选词。
    第三段中,涉及平行信息处理、词汇理解、词义选择等多个考点。在These are essential human skills such as teamwork,leadership,listening,staying positive,dealing with people and managing crises and conflict一句中,平行铺排的成分包括抽象名词、动名词等,在处理时,译者需考虑文字简洁、逻辑清晰。除此之外,本段中有些词语还需要译者结合上下文理解并恰当选择词义,如chum out,know-what,know-how,tacit,explicit等。
    第四段第一句中The employability skills gap需要译者结合上下文理解意义并恰当表述,同时该句还涉及形容词比较级的处理。另外,最后一句省略了相同结构的信息of employers,需要译者采取增译的手段进行补偿。
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