EigoPro 準1級 読解 — Automation and the Future of Work

Few economic anxieties are as durable as the fear that machines will render human labour obsolete. Each wave of technological change—the mechanical loom, the assembly line, the personal computer—has provoked confident predictions of mass unemployment, and each time those predictions have proved spectacularly wrong. The reason is what economists call the "lump of labour fallacy": the mistaken belief that there is a fixed quantity of work in the world, so that any task handed to a machine is a job permanently lost to a human. In reality, automation has historically destroyed particular jobs while creating others, often in numbers and varieties no one foresaw. Yet the present moment may differ in kind, not merely in degree. Earlier machines automated routine physical and clerical tasks, displacing workers who could, in principle, retrain for cognitive roles. Artificial intelligence now encroaches on precisely those cognitive roles—drafting contracts, diagnosing illness, writing code—that were once thought to be safe harbours. If the very tasks to which displaced workers might have fled are themselves automated, the comforting historical pattern could break down. Optimists counter that AI is more likely to augment professionals than to replace them, raising the productivity of doctors and lawyers rather than eliminating them outright. Whatever the ultimate balance, the transition itself is unlikely to be painless. The new jobs may demand skills the displaced do not possess, may appear in cities the displaced cannot afford, and may arrive years after the old jobs vanish. Aggregate statistics showing net employment growth offer cold comfort to a fifty-year-old whose trade has evaporated. The pertinent policy question, then, is not whether machines will leave us with nothing to do, but whether societies will manage the upheaval with foresight or merely react to it after the damage is done.

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この単元の問題を3問、解説つきで公開しています

準1級 · 読解 · 全5問

問 1

What is the main idea of the passage?

  • Automation has historically not caused mass unemployment, but managing the disruption it brings is now the central challenge.
  • Artificial intelligence is certain to cause permanent mass unemployment among professionals.
  • Governments have already solved the problem of workers displaced by new technology.
  • Past fears about machines destroying jobs were always entirely irrational and groundless.
Phrase

the pertinent policy question ... is not whether machines will leave us with nothing to do, but whether societies will manage the upheaval with foresight

準1級読解労働経済主旨把握
⚡ひとことで

歴史的に自動化は大量失業を招かなかったが、今は『移行をどう乗り切るか』が核心。

選択肢の解説Choice Analysis

「Automation has historically not caused mass unemployment, but managing the disruption it brings is now the central challenge.」

正解

本文は (1) 機械が職を奪うという恐れは『労働総量の誤謬』に基づき、歴史的に外れてきた→ (2) しかし AI は逃げ場だった認知労働まで侵食しうる→ (3) いずれにせよ移行は痛みを伴い、問題は『社会が先見性をもって混乱を管理できるか』だと結論する。よって『自動化は歴史的に大量失業を招かなかったが、その混乱の管理が今や核心的課題だ』が主旨。

  • 「Artificial intelligence is quite certain to cause a permanent mass unemployment among all the professionals.」

    = AIが恒久的大量失業を必ず招く ━ 本文は AI が認知労働を侵食しうると述べるが optimists の反論も併記し『必ず』とは断定していない。

  • 「All of the past fears about machines destroying jobs were always entirely irrational and quite groundless.」

    = 過去の恐れは常に完全に非合理で根拠がなかった ━ 本文は今回は『程度ではなく種類が違うかもしれない』と過去の恐れに一定の正当性を認めており、全否定はしていない。

  • 「Governments everywhere have already solved the whole problem of the workers displaced by any new technology.」

    = 政府は既に問題を解決した ━ 本文は混乱を管理できるかが未解決の policy question だと述べており、解決済みとは正反対。

▦Collocation
パターン意味例
render ~ obsolete~を時代遅れにするMachines render human labour obsolete.
prove ~ wrong~が間違いだと判明するThe predictions proved wrong.
manage the upheaval混乱を乗り切るmanage the upheaval with foresight
with foresight先見性をもってreact with foresight, not after the fact
the pertinent question肝心な問いThe pertinent question is how, not whether.
❝例文

  • New technology has repeatedly proved the doom

    mongers wrong. — 新技術は破滅論者を繰り返し間違いだと証明してきた。

  • The pertinent question is how to manage the transition.

    肝心な問いは移行をどう管理するかだ。

  • Societies must act with foresight, not after the damage is done.

    社会は損害が出てからではなく先見性をもって動かねばならない。

💡Tip · 覚えるコツ

主旨設問は最終段の『問題は A ではなく B だ (not whether ... but whether ...)』という対比構文を探すと核心が一発で取れる。

問 2

According to the passage, what is the "lump of labour fallacy"?

  • The belief that machines can never perform cognitive tasks as well as humans can.
  • The idea that new technology creates more jobs than it ever destroys.
  • The false assumption that the total amount of work is fixed, so a task given to a machine is a job lost forever.
  • The proven economic law that automation always reduces the number of available jobs.
Phrase

the mistaken belief that there is a fixed quantity of work in the world

準1級読解労働経済詳細把握
⚡ひとことで

労働総量の誤謬=世界の仕事量は一定という誤った思い込み→機械に渡した仕事は永久に失われると考える。

選択肢の解説Choice Analysis

「The false assumption that the total amount of work is fixed, so a task given to a machine is a job lost forever.」

正解

第1段で lump of labour fallacy を the mistaken belief that there is a fixed quantity of work in the world, so that any task handed to a machine is a job permanently lost to a human と定義している。これを言い換えた『仕事の総量が一定で、機械に与えた仕事は永久に失われるという誤った思い込み』が正解。

  • 「The proven economic law that all automation always reduces the total number of the available jobs.」

    = 自動化が常に職を減らすという証明された経済法則 ━ 本文はこれを『誤謬 (fallacy)』『誤った思い込み (mistaken belief)』と呼んでおり、証明された法則ではない。

  • 「The belief that machines can never perform any cognitive task nearly as well as human beings can.」

    = 機械は認知課題を決してこなせない ━ labour 総量の話であって認知能力の話ではない。論点がずれている。

  • 「The idea that any new technology always creates a great many more jobs than it could ever destroy.」

    = 新技術は破壊する以上の職を生む ━ 本文は雇用が純増する場合に触れるが、これは fallacy の定義そのものではない。

▦Collocation
パターン意味例
the lump of labour fallacy労働総量の誤謬Economists call this the lump of labour fallacy.
a fixed quantity of ~一定量の~a fixed quantity of work
hand a task to ~仕事を~に渡すa task handed to a machine
permanently lost永久に失われるa job permanently lost to a human
the mistaken belief that ...~という誤った思い込みthe mistaken belief that work is fixed
❝例文

  • The lump of labour fallacy assumes work is finite.

    労働総量の誤謬は仕事が有限だと仮定する。

  • Any task handed to a machine need not be a job lost.

    機械に渡した仕事が失職を意味するとは限らない。

  • Economists dismiss the belief as a well

    known fallacy. — 経済学者はその思い込みを有名な誤謬として退ける。

💡Tip · 覚えるコツ

定義を問う detail 設問は本文中の『: 』やコロン直後・that 節の言い換えが正解。形容詞 mistaken/false が定義に含まれる点を見落とさない。

問 3

Why does the author suggest the present moment may be different from earlier waves of automation?

  • Doctors and lawyers have already been completely replaced by artificial intelligence.
  • AI automates only routine physical and clerical tasks, leaving no cognitive work for humans.
  • Earlier machines were never able to displace any workers from their jobs.
  • AI is automating the cognitive roles to which displaced workers used to retreat, threatening the usual escape route.
Phrase

Artificial intelligence now encroaches on precisely those cognitive roles ... that were once thought to be safe harbours

準1級読解労働経済詳細把握
⚡ひとことで

AIは、かつて逃げ込めた認知労働そのものを侵食し、歴史的な逃げ道を断ちうる。

選択肢の解説Choice Analysis

「AI is automating the cognitive roles to which displaced workers used to retreat, threatening the usual escape route.」

正解

第2段で『以前の機械は定型的な肉体・事務労働を自動化し、労働者は認知的職へ再訓練できた』が『AI はまさにその認知的職を侵食する』と述べ、If the very tasks to which displaced workers might have fled are themselves automated, the comforting historical pattern could break down と続ける。よって『AI が、押し出された労働者が逃げ込んでいた認知労働を自動化し、通常の逃げ道を脅かす』が正解。

  • 「AI automates only the routine physical and clerical tasks, leaving no cognitive work at all for humans.」

    = AIは定型的な肉体・事務労働のみを自動化する ━ それは『以前の機械』の説明。AI はむしろ認知労働を侵食すると本文は述べる。

  • 「The earlier machines were never once able to displace any of the workers at all from any of their jobs.」

    = 以前の機械は労働者を全く押し出せなかった ━ 本文は以前の機械が労働者を displace したと明言しており正反対。

  • 「Doctors and lawyers everywhere have by now already been completely replaced by artificial intelligence.」

    = 医師と弁護士は既に完全に置換された ━ optimists は AI が専門家を replace せず augment すると述べており、完全置換は本文にない。

▦Collocation
パターン意味例
encroach on ~~を侵食するAI encroaches on cognitive roles.
safe harbour安全な避難先roles thought to be safe harbours
flee to ~~へ逃げ込むtasks workers might have fled to
break down崩れるthe historical pattern could break down
augment rather than replace置換でなく補強するAI may augment professionals rather than replace them.
❝例文

  • AI now encroaches on roles once thought to be safe.

    AIは今や安全とされた職を侵食しつつある。

  • Workers could once flee to cognitive jobs.

    労働者はかつて認知的職へ逃げ込めた。

  • Optimists say AI will augment doctors, not replace them.

    楽観論者はAIが医師を置換せず補強すると言う。

💡Tip · 覚えるコツ

『なぜ今回は違うか』型は対比 (Earlier ... now ...) を探す。誤答は前後の主語をすり替える (以前の機械の説明をAIに貼る) 型が頻出。

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