Shadowing Practice: Cambridge Ielts 16 Reading test 1 Passage 3 - Learn English Speaking with Video

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3. The Future of Work According to a leading business consultancy,
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3-14% of the global workforce will need to switch to a different occupation within the next 10-15 years,
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and all workers will need to adapt as their occupations evolve alongside increasingly capable machines.
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Automation, or Embodied Artificial Intelligence, AI, is one aspect of the disruptive effects of technology on the labor market.
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Disembodied L, like the algorithms running in our smartphones, is another.
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Dr. Stella Pacitti from Cambridge Judge Business School believes
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that some of the most fundamental changes are happening as a result of the algorithmication of jobs
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that are dependent on data rather than on production, the so-called knowledge economy.
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Algorithms are capable of learning from data to undertake tasks that previously needed human judgment, such as reading legal contracts,
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analyzing medical scans, and gathering market intelligence.
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In many cases, they can outperform humans, says Pachidi.
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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.
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But these enhancements are not without consequences, says Pachidi.
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If routine cognitive tasks are taken over by AI, how do professions develop their future experts?
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She asks.
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One way of learning about a job is legitimate peripheral participation.
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A novice stands next to experts and learns by observation.
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If this isn't happening, then you need to find new ways to learn.
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Another issue is the extent to which the technology influences or even controls the workforce.
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For over two years, Puccini monitored a telecommunications company.
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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.
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However, the company had started using an algorithm that defined
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when account managers should contact certain customers about which kinds of campaigns and what to offer them.
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The algorithm, usually built by external designers, often becomes the keeper of knowledge, she explains.
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In cases like this, Pachitti believes,
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a short-sighted view begins to creep into working practices whereby workers learn through the algorithm's eyes and become dependent on its instructions.
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Alternative explorations, where experimentation and human instinct lead to progress and new ideas, are effectively discouraged.
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Pachidi and colleagues even observed people developing strategies to make the algorithm work to their own advantage.
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We are seeing cases where workers feed the algorithm with false
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data to reach their targets she reports it's scenarios like these
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that many researchers are working to avoid their objective is to make ai technologies more trustworthy
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and transparent so that organizations
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and individuals understand how ai decisions are made in the meantime
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says pachidi We need to make sure we fully understand the dilemmas that this new world raises regarding expertise, occupational boundaries, and control.
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Economist Professor Hamish Lowe believes that the future of work will involve major transitions across the whole life course for everyone.
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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.
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Instead, he envisages a multi-stage employment life, one where retraining happens across the life course,
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and where multiple jobs and no job happen by choice at different stages.
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On the subject of job losses, Mo believes the predictions are founded on a fallacy, it assumes that the number of jobs is fixed.
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If in 30 years, half of 100 jobs are being carried out by robots,
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that doesn't mean we are left with just 50 jobs for The number of jobs will increase.
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We would expect there to be 150 jobs.
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Dr. Ewan Mitkauhi at Cambridge's Centre for Business Research in King's College London agrees
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that apocalyptic views about the future of work are misguided.
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It's the laws that restrict the supply of capital to the job market, not the advent of new technologies that causes unemployment.
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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.
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it.
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History is clear that change can mean redundancies, but social policies can tackle this through retraining and redeployment.
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He adds, if there is going to be changed to jobs as a result of AI
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and robotics then I'd like to see governments seizing the opportunity to improve policy to enforce good job security.
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We can reprogram the law to prepare for a fairer future of work and leisure.
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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,
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fair incomes and a thriving economic democracy.
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The promises of these new technologies are astounding.
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They deliver humankind the capacity to live in a way that nobody could have once imagined humans.
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Just as the Industrial Revolution brought people past subsistence agriculture and the corporate revolution enabled mass production,
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a third revolution has been pronounced.
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But it will not only be one of technology.
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The next revolution will be social.

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Woordenschat en spreektips bij deze les

Deze spreekles op niveau C1 is gebaseerd op de video “Cambridge Ielts 16 Reading test 1 Passage 3”. Deze woorden komen het vaakst terug: algorithm, pachidi, believes, revolution, technologies. Deze video bevat 59 zinnen en 839 woorden om na te spreken. Het gesproken deel duurt 5:47. De spreker praat in een gelijkmatig tempo van ongeveer 145 woorden per minuut, prettig om te shadowen. Slechts 77% van de woorden hoort bij de 3.000 meest gebruikte Engelse woorden, dus de woordenschat is pittig.

Belangrijke woorden in deze video

De 15 moeilijkste woorden uit de video, met uitspraak en betekenis:

WoordUitspraakBetekenis
algorithm zelfstandig naamwoord/ˈælɡəɹɪðm̩/algoritme
robotics zelfstandig naamwoord/ɹoʊˈbɑ.tɪks/robotica
automation zelfstandig naamwoord/ˌɔ.təˈmeɪ.ʃən/automatisering
workforce zelfstandig naamwoord/ˈwɝk.foɹs/werkkracht
apocalyptic bijvoeglijk naamwoord/əˈpɒ.kə.lɪp.tɪk/apocalyptisch
astound werkwoord/əˈstaʊnd/verbluffen
consultancy zelfstandig naamwoord/kənˈsʌl.tən.si/adviesbureau, consultancybedrijf
disruptive bijvoeglijk naamwoord/dɪsˈɹʌptɪv/storend, onrustwekkend
fallacy zelfstandig naamwoord/ˈfæl.ə.si/bedrieglijkheid
redundancy zelfstandig naamwoord/ɹɪˈdʌndən(t)si/overtolligheid, redundantie
salesperson zelfstandig naamwoordverkoper, verkoopster
trustworthy bijvoeglijk naamwoord/ˈtɹʌst.wɜː.ði/betrouwbaar
discourage werkwoord/dɪsˈkɝɪd͡ʒ/ontmoedigen
trajectory zelfstandig naamwoord/tɹəˈd͡ʒɛktəɹi/baan, traject
enhancement zelfstandig naamwoord/ɪnˈhæns.mənt/verbetering

Phrasal verbs die je zult horen

WoordUitspraakBetekenis
carry out werkwoord/ˈkæ.ɹi aʊt/uitvoeren
take over werkwoordovernemen

Uitspraak om op te letten

De spreker gebruikt 3 samentrekkingen en verkorte vormen, zoals doesn't, I'd, isn't. Spreek ze kort uit, zoals je ze hoort.

  • De “th”-klanken: algorithm /ˈælɡəɹɪðm̩/, trustworthy /ˈtɹʌst.wɜː.ði/, thrive /θɹajv/
  • De klanken “sh” en “zh”: automation /ˌɔ.təˈmeɪ.ʃən/, experimentation /ɪkˌspɛɹ.ə.mənˈteɪ.ʃən/, telecommunication /ˌtɛləkəˌmjunɪˈkeɪʃən/, occupational /ɑkjuˈpeɪʃənəl/, leisure /ˈlɛʒə(ɹ)/
  • Lange woorden — let op de klemtoon: automation /ˌɔ.təˈmeɪ.ʃən/, apocalyptic /əˈpɒ.kə.lɪp.tɪk/, consultancy /kənˈsʌl.tən.si/, disembodied /dɪsɪmˈbɒdiːd/, experimentation /ɪkˌspɛɹ.ə.mənˈteɪ.ʃən/

Klanken die Nederlandstaligen lastig vinden:

  • Stemhebbende eindmedeklinker — /b/, /d/, /g/, /z/, /v/ niet verscherpen: astound /əˈstaʊnd/, disembodied /dɪsɪmˈbɒdiːd/, disruptive /dɪsˈɹʌptɪv/, envisage /ɛnˈvɪzɪd͡ʒ/, humankind /ˌhjuːmənˈkaɪnd/
  • /æ/ — opener dan de Nederlandse “e”: algorithm /ˈælɡəɹɪðm̩/, fallacy /ˈfæl.ə.si/, enhancement /ɪnˈhæns.mənt/, advent /ˈæd.vɛnt/, analyze /ˈæn.əˌlaɪz/
  • /g/ — een harde plofklank, geen Nederlandse “g”: algorithm /ˈælɡəɹɪðm̩/, misguided /ˌmɪsˈɡaɪdɪd/, colleague /ˈkɒliːɡ/

Zo oefen je met deze video

  1. Luister de hele video één keer zonder te spreken en noteer de woorden die je niet kent.
  2. Spreek zin voor zin na op normale snelheid en herhaal elke zin tot je ritme gelijk is aan dat van de spreker.
  3. Neem jezelf op en vergelijk met het origineel; let daarbij op woorden als algorithm, robotics, automation.

Wat is de Shadowing-techniek?

Shadowing is een wetenschappelijk onderbouwde taalleermethode die oorspronkelijk is ontwikkeld voor professionele tolkentraining en gepopulariseerd door polyglot Dr. Alexander Arguelles. De methode is eenvoudig maar krachtig: je luistert naar native Engelse audio en herhaalt het onmiddellijk hardop — als een schaduw die de spreker volgt met slechts 1–2 seconden vertraging. In tegenstelling tot passief luisteren of grammaticadrills, dwingt shadowing je hersenen en mondspieren om echte spraakpatronen tegelijkertijd te verwerken en te reproduceren. Onderzoek toont aan dat het de uitspraaknauwkeurigheid, intonatie, ritme, verbonden spraak, luisterbegrip en spreekvaardigheid aanzienlijk verbetert — waardoor het een van de meest effectieve methoden is voor IELTS Speaking-voorbereiding en echte Engelse communicatie.

Shadowing-techniek: lees de volledige stap-voor-stap-gids →