剑桥雅思16Test1Passage3阅读原文翻译 The future of work 未来工作展望
剑桥雅思16阅读第一套题目第三篇文章主要讲述了技术对未来工作的影响。文章一共14段，前半部分讲解技术给人们工作带来的挑战，包括对技术的依赖、工作岗位的减少等。后半部分主要阐述另一种观点，认为技术的影响并不如前面所说的那么坏，只要采取合适的政策就可以解决问题。下面是具体每一段的翻译。
点击查看这篇雅思阅读具体题目的答案解析与其中出现的高频词汇：
雅思阅读真题词汇 剑桥雅思16 Test 1 Passage 3 工作的未来
剑桥雅思16Test1Passage3阅读答案解析 The future of work 技术对未来工作的影响
剑桥雅思16 Test1 Passage3阅读原文翻译
第1段
According to a leading business consultancy, 3-14% of the global workforce will need to switch to a different occupation within the next 10-15 years, and all workers will need to adapt as their occupations evolve alongside increasingly capable machines. Automation – or ’embodied artificial intelligence’ (AI) – is one aspect of the disruptive effects of technology on the labour market.’Disembodied AI’, like the algorithms running in our smartphones, is another.
根据一家一流商业咨询机构的预测，全球3%到15%的劳动力需要在10到15年内更换自己的工作。所有劳动者都需要适应由越来越先进的机器所带来的工作内容的变化。自动化，或者“看得见的人工智能”，是技术对劳动力市场破坏性影响的一个方面。而“看不见的人工智能”，如我们手机中运行的算法，是其影响的另一方面。
第2段
Dr Stella Pachidi from Cambridge Judge Business School believes that some of the most fundamental changes are happening as a result of the ‘algorithmication’ of jobs that are dependent on data rather than on production – the so-called knowledge economy. Algorithms are capable of learning from data to undertake tasks that previously needed human judgement, such as reading legal contracts, analysing medical scans and gathering market intelligence.
剑桥大学贾吉商学院Stella Pachidi博士认为一些最根本的改变是工作内容“算法化”的结果，即工作依赖于数据而非生产-所谓的知识经济。算法可以从数据中学习，进而执行之前需要人类判断的任务，比如阅读法律合同，分析医疗检查结果，并收集市场情报。
第3段
‘In many cases, they can outperform humans,’ says Pachidi, ‘Organisations are attracted to using algorithms because they want to make choices based on what they consider is “perfect information”, as well as to reduce costs and enhance productivity.’
“许多情况下，它们的表现都超过人类”，Pachidi说，“组织机构倾向于使用算法，因为他们想要将决策建立在他们所认为的‘完全信息’上，减少成本，并提升生产效率”。
第4段
‘But these enhancements are not without consequences,’ says Pachidi. ‘If routine cognitive tasks are taken over by AI, how do professions develop their future experts?’ she asks. ‘One way of learning about a job is “legitimate peripheral participation” – a novice stands next to experts and learns by observation. If this isn’t happening, then you need to find new ways to learn.’
“但是，这些提升并非没有代价”，Pachidi说，“如果日常认知任务都由人工智能进行，那么各行各业如何培养自己未来的专家？”她问道。“了解某项工作的一种方法是‘合法的边缘性参与’，即新手站在专家旁，通过观察学习。如果这种方式消失了的话，那么你就得寻找新的学习方法”。
第5段
Another issue is the extent to which the technology influences or even controls the workforce. For over two years, Pachidi monitored a telecommunications company. ‘The way telecoms salespeople work is through personal and frequent contact with clients, this article is from Laokaoya website. using the benefit of experience to assess a situation and reach a decision. However, the company had started using a[n]…algorithm that defined when account managers should contact certain customers about which kinds of campaigns and what to offer them.’
另外一项问题是，技术在多大程度上影响甚至控制员工。Pachidi观察一家电信公司两年多的时间。“电信公司销售人员的工作通过与客户私下而频繁的接触展开，利用他们的经验优势评估状况并促成决定。然而，公司已经开始使用算法决定客户经理应该在什么时候、就哪种活动与产品联系特定的顾客”。
第6段
The algorithm – usually built by external designers – often becomes the keeper of knowledge, she explains. In cases like this, Pachidi believes, a short-sighted view begins to creep into working practices whereby workers learn through the ‘algorithm’s eyes’ and become dependent on its instructions. Alternative explorations – where experimentation and human instinct lead to progress and new ideas -are effectively discouraged.
她解释道，这种通常由外部设计师搭建的算法成为知识的保管员。Pachidi认为，在诸如此类的情况下，一种较为短视的看法开始影响工作实践。员工通过算法的视角进行学习，并依赖于它的指示。替代性探索，即实验与人类直觉催生进步和新观点，遭到打击。
第7段
Pachidi and colleagues even observed people developing strategies to make the algorithm work to their own advantage.’We are seeing cases where workers feed the algorithm with false data to reach their targets,’ she reports.
Pachidi和她的同事甚至观察到，人们开发出相应的策略，让算法为满足他们自己的利益而工作。“我们观察到如下案例，员工将错误的数据提供给算法以达到自己的目的”，她指出。
第8段
It’s scenarios like these that many researchers are working to avoid. Their objective is to make AI technologies more trustworthy and transparent, so that organisations and individuals understand how AI decisions are made. In the meantime, says Pachidi,’ We need to make sure we fully understand the dilemmas that this new world raises regarding expertise, occupational boundaries and control.’
这正是许多研究者努力避免的情景。他们的目标是让人工智能技术变得更加可信、更加透明，以便组织机构和个人文章来自老烤鸭雅思能够理解人工智能如何做出决策。与此同时，Pachidi说道，“我们需要确保自己充分理解这一新世界在专业技能、职业边界和控制方面发引发的困境”。
第9段
Economist Professor Hamish Low believes that the future of work will involve major transitions across the whole life course for everyone: ‘The traditional trajectory of full-time education followed by full-time work followed by a pensioned retirement is a thing of the past,’ says Low. Instead, he envisages a multistage employment life: one where retraining happens across the life course, and where multiple jobs and no job happen by choice at different stages.
经济学教授Hamish Low认为，未来的工作会给所有人生活的方方面面带来重大转变。“传统的接受全日制教育之后从事全日制工作，随后再领取津贴退休的路径已经是过去时”。他反而展望一种多阶段的职业生活：整个生命过程中都会进行再培训，不同阶段选择从事多种工作或者不工作。
第10段
On the subject of job losses, Low believes the predictions are founded on a fallacy: “It assumes that the number of jobs is fixed. If in 30 years, half of 100 jobs are being carried out by robots, that doesn’t mean we are left with just 50 jobs for humans. The number of jobs will increase: we would expect there to be 150 jobs.’
至于工作流失的问题，Low认为这一预测建立在谬误之上：“它假定工作的数量是固定的。如果在未来30年里，100个工作岗位中有一半由机器人承担，这并不意味着只剩下50个岗位给人类。工作数量会上升。我们能够期望会有150个工作机会”。
第11段
Dr Ewan McGaughey, at Cambridge’s Centre for Business Research and King’s College London, agrees that ‘apocalyptic’ views about the future of work are misguided. ‘It’s the laws that restrict the supply of capital to the job market, not the advent of new technologies that causes unemployment.
剑桥大学商业研究中心与伦敦国王学院的Ewan McGaughey博士同样认为有关未来工作的“末日论”充满误导。“限制求职市场资本供给的法律才是引发失业的原因，而非新技术的出现”。
第12段
His recently published research answers the question of whether automation, AI and robotics will mean a ‘jobless future’ by looking at the causes of unemployment. ‘History is clear that change can mean redundancies. But social policies can tackle this through retraining and redeployment.’
他最近发表的研究通过探询失业的起因回答了自动化，人工智能以及机器人是否会引发“无工作的未来”这一问题。“历史表明，改变可能意味着裁员。但社会政策能够通过再培训以及再分配解决这一问题”。
第13段
He adds: ‘If there is going to be change to jobs as a result of AI and robotics then I’d like to see governments seizing the opportunity to improve policy to enforce good job security. We can “reprogramme” the law to prepare for a fairer future of work and leisure.’ McGaughey’s findings are a call to arms to leaders of organisations, governments and banks to pre-empt the coming changes with bold new policies that guarantee full employment, fair incomes and a thriving economic democracy.
他补充到：“如果人工智能和机器人引发工作上的改变，那么我想看到政府抓住机会提升政策以确保良好的工作安全。我们可以重新编排法律以迎接工作和休闲更为公平的未来”。McGaughey的发现呼吁组织机构、政府和银行的领导制定大胆的新政策，以提前应对即将到来的改变，确保就业率、公平收入、以及繁荣的经济民主。
第14段
‘The promises of these new technologies are astounding. They deliver humankind the capacity to live in a way that nobody could have once imagined,’ he adds. ‘Just as the industrial revolution brought people past subsistence agriculture, and the corporate revolution enabled mass production, a third revolution has been pronounced. But it will not only be one of technology. The next revolution will be social.’
“这些新技术带来的前景让人震惊。他们赋予人类以一种前人无法想象的方式生活的能力”，他补充到，“正如工业革命让人们脱离勉强糊口的农业生活，企业革命让大规模生产成为可能，第三次革命已经出现。但它绝不仅仅是技术革命。下一次革命一定是社会性的”。
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