跟读练习: Cambridge Ielts 16 Reading test 1 Passage 3 - 通过视频学习英语口语

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3. The Future of Work 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 labor market.

Disembodied L, like the algorithms running in our smartphones, is another.

Dr. Stella Pacitti 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 judgment, such as reading legal contracts,

analyzing medical scans, and gathering market intelligence.

In many cases, they can outperform humans, says Pachidi.

Organizations are attracted to using algorithms because they want to make choices based on what they consider as perfect information, as well as to reduce costs and enhance productivity.

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.

Another issue is the extent to which the technology influences or even controls the workforce.

For over two years, Puccini monitored a telecommunications company.

The way telecom salespeople work is through personal and frequent contact with clients, using the benefit of experience to assess a situation and reach a decision.

However, the company had started using an algorithm that defined

when account managers should contact certain customers about which kinds of campaigns and what to offer them.

The algorithm, usually built by external designers, often becomes the keeper of knowledge, she explains.

In cases like this, Pachitti 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.

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 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 organizations

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.

Economist Professor Hamish Lowe 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 pension retirement is a thing of the past, says Lowe.

Instead, he envisages a multi-stage employment life, one where retraining happens across the life course,

and where multiple jobs and no job happen by choice at different stages.

On the subject of job losses, Mo 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 The number of jobs will increase.

We would expect there to be 150 jobs.

Dr. Ewan Mitkauhi at Cambridge's Centre for Business Research in 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.

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.

it.

History is clear that change can mean redundancies, but social policies can tackle this through retraining and redeployment.

He adds, if there is going to be changed 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 reprogram the law to prepare for a fairer future of work and leisure.

McGauhe's findings are a call to arms to leaders of organizations, governments and banks to preempt for coming changes with bold new policies that guarantee full employment,

fair incomes and a thriving economic democracy.

The promises of these new technologies are astounding.

They deliver humankind the capacity to live in a way that nobody could have once imagined humans.

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.

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本课的词汇与口语要点

这节 C1 级别的口语课以视频“Cambridge Ielts 16 Reading test 1 Passage 3”为素材。视频中反复出现的词有：algorithm, pachidi, believes, revolution, technologies。这段视频共有 59 个句子、839 个单词可供跟读。讲话部分时长为 5:47。说话人语速平稳，每分钟约 145 个词，很适合跟读。只有 77% 的单词属于英语最常用的 3,000 词，词汇难度较高。

视频中的重点词汇

视频中最难的 15 个单词，附发音和释义：

单词	发音	释义
algorithm 名词	/ˈælɡəɹɪðm̩/	算法, 演算法
robotics 名词	/ɹoʊˈbɑ.tɪks/	機器人學 /机器人学
automation 名词	/ˌɔ.təˈmeɪ.ʃən/	自動化 /自动化
workforce 名词	/ˈwɝk.foɹs/	勞動力 /劳动力, 員工 /员工
astound 动词	/əˈstaʊnd/	使驚奇 /使惊奇
disruptive 形容词	/dɪsˈɹʌptɪv/	分裂性的, 扰动的
experimentation 名词	/ɪkˌspɛɹ.ə.mənˈteɪ.ʃən/	實驗 /实验
fallacy 名词	/ˈfæl.ə.si/	謬誤 /谬误
preempt 动词	/ˌpɹiːˈɛmpt/	搶占, 搶先 /抢先
redeployment 名词		重新部署, 調動 /调动
redundancy 名词	/ɹɪˈdʌndən(t)si/	冗余
salesperson 名词		售貨員 /售货员, 推銷員 /推销员
telecommunication 名词	/ˌtɛləkəˌmjunɪˈkeɪʃən/	電訊 /电讯, 電信 /电信
trustworthy 形容词	/ˈtɹʌst.wɜː.ði/	可信, 可靠
discourage 动词	/dɪsˈkɝɪd͡ʒ/	令人愁悶 /令人愁闷, 使沮喪 /使沮丧

视频中出现的短语动词

单词	发音	释义
carry out 动词	/ˈkæ.ɹi aʊt/	進行 /进行
take over 动词		接管, 接手

需要注意的发音

说话人用了 3 次缩略和弱读形式，例如 doesn't, I'd, isn't。请按听到的简短形式来说。

“th” 音: algorithm /ˈælɡəɹɪðm̩/, trustworthy /ˈtɹʌst.wɜː.ði/, thrive /θɹajv/
“sh” 和 “zh” 音: automation /ˌɔ.təˈmeɪ.ʃən/, experimentation /ɪkˌspɛɹ.ə.mənˈteɪ.ʃən/, telecommunication /ˌtɛləkəˌmjunɪˈkeɪʃən/, occupational /ɑkjuˈpeɪʃənəl/, leisure /ˈlɛʒə(ɹ)/
长单词——注意重音位置: automation /ˌɔ.təˈmeɪ.ʃən/, apocalyptic /əˈpɒ.kə.lɪp.tɪk/, consultancy /kənˈsʌl.tən.si/, disembodied /dɪsɪmˈbɒdiːd/, experimentation /ɪkˌspɛɹ.ə.mənˈteɪ.ʃən/

中文母语者容易读错的音：

/v/ — 不要读成 /w/，上齿轻触下唇: disruptive /dɪsˈɹʌptɪv/, envisage /ɛnˈvɪzɪd͡ʒ/, novice /ˈnɑvɪs/, advent /ˈæd.vɛnt/, thrive /θɹajv/
词尾辅音 — 要读清楚，后面不要加元音: robotics /ɹoʊˈbɑ.tɪks/, workforce /ˈwɝk.foɹs/, apocalyptic /əˈpɒ.kə.lɪp.tɪk/, astound /əˈstaʊnd/, disembodied /dɪsɪmˈbɒdiːd/
/r/ 和 /l/ 的区别: algorithm /ˈælɡəɹɪðm̩/, peripheral /pəˈɹɪf(ə)ɹ(ə)l/, leisure /ˈlɛʒə(ɹ)/

如何用这段视频练习

先完整听一遍视频，不要开口，记下不认识的单词。
用正常速度逐句跟读，每句重复到你的节奏与说话人一致为止。
录下自己的声音并与原声对比，特别注意 algorithm, robotics, automation 这类单词。

什么是跟读法？

跟读法 (Shadowing) 是一种有科学依据的语言学习技巧，最初开发用于专业口译员的培训，并由多语言者Alexander Arguelles博士普及。这个方法简单而强大：您在听英语母语原声的同时立即大声重复——就像是一个延迟1-2秒紧跟说话者的影子。与被动听力或语法练习不同，跟读法强迫您的大脑和口腔肌肉同时处理并模仿真实的讲话模式。研究表明它能显着提高发音准确性，语调，节奏，连读，听力理解和口语流利度——使其成为雅思口语备考和真实英语交流最有效的方法之一。

影子跟读法: 阅读完整分步指南 →

跟读练习: Cambridge Ielts 16 Reading test 1 Passage 3 - 通过视频学习英语口语

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