Text Analysis: Science and Technology — Visions of the Future

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📘 Referenzleitfaden: Rhetorische Mittel (zum Nachschlagen)
Rhetorical question — a question asked to make a point rather than to get an answer.
Example: "Isn't it time we asked what success really costs?"
Anecdote — a short personal story used to illustrate a wider point.
Example: "When Maria was twelve, she watched her father work three jobs to pay the rent."
Statistic — a number or piece of data used as evidence.
Example: "Nearly 40% of graduates now say they would take a pay cut for a shorter working week."
Metaphor — describing something as if it were something else, without using "like" or "as".
Example: "The corporate ladder has become a treadmill."
Direct address — speaking straight to the reader using "you" or "your".
Example: "You already know the feeling — that quiet dread on Sunday evening."
Tricolon (list of three) — three parallel words or phrases for rhythm and emphasis.
Example: "They wanted freedom, flexibility, and a reason to get out of bed."
Antithesis / contrast — placing two opposing ideas close together for effect.
Example: "Our parents chased security; we chase meaning."

Übung 1 · Rhetorische Mittel zuordnen

Read the article below. Match each highlighted quotation to the rhetorical/stylistic device it demonstrates.

The Machines We Made to Think: Living With Artificial Intelligence

Fifty years ago, a computer that could hold a conversation belonged firmly to science fiction. Would anyone in 1975 have believed that a machine could one day write poetry, diagnose illness, and argue philosophy — all before breakfast? Today, that machine sits quietly in millions of pockets.

Consider Dr. Amara Okafor, a radiologist in Toronto. Last year, an AI system flagged a tumour on one of her scans that she herself had missed on first review, and she has not looked at a scan the same way since. For her, artificial intelligence is no longer a futuristic curiosity — it is a colleague she did not choose but has come to rely on.

The scale of the shift is difficult to overstate. One recent industry report estimates that AI tools now assist in over 30% of medical diagnoses made in leading hospitals worldwide. What began as an experiment in laboratories has quietly become infrastructure.

Yet for every efficiency gained, a question is raised. We taught machines to see patterns we could not; now we must decide how much of our judgement we are willing to hand over in return. Optimists see a future of longer, healthier lives. Sceptics see a slow erosion of human expertise and accountability.

Both camps agree on one thing: the technology is not coming — it has already arrived. The only real choice left is not whether artificial intelligence will shape our future, but how wisely we choose to shape it back.

Übung 2 · Purpose, Audience & Tone

Answer the following questions about the article's purpose, intended audience, and tone.

📄 Read the article again

Fifty years ago, a computer that could hold a conversation belonged firmly to science fiction. Would anyone in 1975 have believed that a machine could one day write poetry, diagnose illness, and argue philosophy — all before breakfast? Today, that machine sits quietly in millions of pockets.

Consider Dr. Amara Okafor, a radiologist in Toronto. Last year, an AI system flagged a tumour on one of her scans that she herself had missed on first review, and she has not looked at a scan the same way since. For her, artificial intelligence is no longer a futuristic curiosity — it is a colleague she did not choose but has come to rely on.

The scale of the shift is difficult to overstate. One recent industry report estimates that AI tools now assist in over 30% of medical diagnoses made in leading hospitals worldwide. What began as an experiment in laboratories has quietly become infrastructure.

Yet for every efficiency gained, a question is raised. We taught machines to see patterns we could not; now we must decide how much of our judgement we are willing to hand over in return. Optimists see a future of longer, healthier lives. Sceptics see a slow erosion of human expertise and accountability.

Both camps agree on one thing: the technology is not coming — it has already arrived. The only real choice left is not whether artificial intelligence will shape our future, but how wisely we choose to shape it back.

Übung 3 · Wirkung analysieren (Effect Analysis)

For each technique below, choose the answer that best explains its effect on the reader.

📄 Read the article again

Fifty years ago, a computer that could hold a conversation belonged firmly to science fiction. Would anyone in 1975 have believed that a machine could one day write poetry, diagnose illness, and argue philosophy — all before breakfast? Today, that machine sits quietly in millions of pockets.

Consider Dr. Amara Okafor, a radiologist in Toronto. Last year, an AI system flagged a tumour on one of her scans that she herself had missed on first review, and she has not looked at a scan the same way since. For her, artificial intelligence is no longer a futuristic curiosity — it is a colleague she did not choose but has come to rely on.

The scale of the shift is difficult to overstate. One recent industry report estimates that AI tools now assist in over 30% of medical diagnoses made in leading hospitals worldwide. What began as an experiment in laboratories has quietly become infrastructure.

Yet for every efficiency gained, a question is raised. We taught machines to see patterns we could not; now we must decide how much of our judgement we are willing to hand over in return. Optimists see a future of longer, healthier lives. Sceptics see a slow erosion of human expertise and accountability.

Both camps agree on one thing: the technology is not coming — it has already arrived. The only real choice left is not whether artificial intelligence will shape our future, but how wisely we choose to shape it back.

Übung 4 · Aufbau eines Analyseaufsatzes ordnen

Click the paragraph descriptions below in the correct order to build a well-structured analysis essay.

Übung 5 · Vollständige Analyse schreiben

Write a full analysis paragraph (150–200 words) examining how the writer uses language to convey her message.

📄 Read the article again

Fifty years ago, a computer that could hold a conversation belonged firmly to science fiction. Would anyone in 1975 have believed that a machine could one day write poetry, diagnose illness, and argue philosophy — all before breakfast? Today, that machine sits quietly in millions of pockets.

Consider Dr. Amara Okafor, a radiologist in Toronto. Last year, an AI system flagged a tumour on one of her scans that she herself had missed on first review, and she has not looked at a scan the same way since. For her, artificial intelligence is no longer a futuristic curiosity — it is a colleague she did not choose but has come to rely on.

The scale of the shift is difficult to overstate. One recent industry report estimates that AI tools now assist in over 30% of medical diagnoses made in leading hospitals worldwide. What began as an experiment in laboratories has quietly become infrastructure.

Yet for every efficiency gained, a question is raised. We taught machines to see patterns we could not; now we must decide how much of our judgement we are willing to hand over in return. Optimists see a future of longer, healthier lives. Sceptics see a slow erosion of human expertise and accountability.

Both camps agree on one thing: the technology is not coming — it has already arrived. The only real choice left is not whether artificial intelligence will shape our future, but how wisely we choose to shape it back.

Focus: Analyse how the writer uses the case study of Dr. Okafor alongside statistical evidence, and the closing antithesis, to convey her balanced argument about AI's role in the future.
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