IELTS Technology Essay Topics + Band 9 Sample

Technology questions reward precise scope: AI and work, screens and children, privacy, remote work, or “easier vs more complicated” life. This page from IELTS AI Tutor by IELTSGRADER gives a technology topic bank, one unique Band 9 sample with examiner-style TR/CC/LR/GRA notes, and a try-it prompt you can score today.

For a strong mid-high model on a different tech prompt, see the Band 7 technology sample. That essay shows solid Band 7 control; this one shows the extra precision that lifts a script toward Band 9.

In this guide

1. High-yield technology topic angles
2. Band 9 sample question
3. Full Band 9 sample essay
4. Examiner-style criterion analysis
5. Band 9 moves you can copy (without copying sentences)
6. Technology collocations that sound natural
7. Try this yourself
8. Frequently asked questions

High-yield technology topic angles

Angle	Typical framing	One precise idea
Labour market	Automation / AI replacing jobs	Displacement in routine roles + demand for complementary skills
Attention & wellbeing	Smartphones / social media	Design for engagement vs user self-regulation
Education tech	Online courses / AI tutors	Access and pacing gains vs weak feedback authenticity
Privacy & data	Surveillance / targeted ads	Convenience trade-off vs informed consent
Remote work	Home vs office	Productivity flexibility vs weaker mentoring and culture
Inequality	Digital divide	Device access is not the same as digital capability

Avoid writing “technology is good and bad.” Choose a mechanism: time saved, skills shifted, attention fragmented, or trust eroded.

Band 9 sample question

Prompt: Artificial intelligence is increasingly used to make decisions in areas such as hiring, banking, and healthcare. Some people think this improves fairness and efficiency. Others worry it creates new risks. Discuss both views and give your own opinion.

Write at least 250 words.

Full Band 9 sample essay

Artificial intelligence now influences who gets shortlisted for jobs, who receives a loan, and which patients are flagged for follow-up care. While algorithmic decision-making can improve consistency and speed, I believe its benefits only outweigh the risks when humans remain accountable for outcomes and when systems are audited for bias.

Advocates emphasise efficiency and reduced human inconsistency. A well-designed model can review thousands of applications with the same criteria, potentially limiting favouritism that appears in rushed human screening. In banking, automated risk checks can flag unusual transactions faster than manual review. In healthcare triage tools, pattern recognition may help clinicians notice early warning signs that a tired staff member might miss. From this angle, AI does not replace judgement so much as standardise first-pass decisions and free experts for complex cases.

Critics focus on opacity and amplified bias. If historical hiring data under-represented certain groups, a model trained on that data can reproduce discrimination at scale — quietly, and with an appearance of objectivity. Errors in credit or medical contexts are not minor inconveniences; they can block housing, employment, or timely treatment. Moreover, when organisations hide behind “the algorithm decided,” individuals lose a clear path to explanation and appeal. Efficiency without contestability is a weak form of fairness.

My view is that AI should be treated as a high-speed assistant, not an unsupervised authority. Fairness improves when models are tested against protected attributes, when decision thresholds are reviewed by domain experts, and when people can challenge automated outcomes with a human second look. Efficiency still matters: automated screening can reduce delays. But the decisive safeguard is accountability — documenting what the system optimises for, who monitors drift, and who is responsible when harm occurs.

In conclusion, AI decision tools can raise consistency and speed in hiring, finance, and healthcare, yet they also concentrate risk when bias and opacity go unchecked. Used with audit trails and human oversight, they are a net gain; used as unexamined substitutes for responsibility, they create new forms of injustice.

(Word count: ~312)

Examiner-style criterion analysis

Criterion	Band	Examiner-style note
Task Response	9	Both views extended with domain examples; opinion states a clear condition (accountability + audit)
Coherence & Cohesion	9	Clean view → view → synthesis; cohesive devices are light and purposeful
Lexical Resource	9	Precise topic lexis (shortlisted, contestability, decision thresholds) used naturally
Grammatical Range & Accuracy	9	Controlled complex structures; punctuation supports clarity

Overall impression for this Task 2 script: Band 9 (illustrative teaching score).

Notice the essay never claims AI is “always fair.” Band 9 Task Response often means conditional positions: benefits under named safeguards.

Band 9 moves you can copy (without copying sentences)

1. Name the domains in the intro — hiring, banking, healthcare — so the paraphrase matches the prompt.
2. Give each side a mechanism — standardisation vs bias-at-scale — not vibes.
3. Define your opinion with an operating rule — assistant + audit + appeal.
4. Keep examples short — one sentence each is enough at this level.

A fifth move that separates mid-band tech essays from high-band ones is refusal to moralise. Examiners do not need “technology is destroying society.” They need a decision rule: when AI helps, when it harms, and what oversight changes the outcome. If your conclusion only restates “there are advantages and disadvantages,” Task Response usually stalls around 6.5–7 even when grammar is clean.

If you are stuck between 7 and 8 on technology essays, you usually need sharper conditions and less generic “in modern society” padding. See also improve Band 7 to 8 and lexical resource Band 6 to 7.

Technology collocations that sound natural

Overused	Stronger options
modern technology	digital systems / algorithmic tools
make life easier	reduce friction / automate routine steps
bad effects	unintended harms / attention costs
depend on phones	rely on connected devices
AI is smart	models detect patterns / systems optimise for…

Pair collocations with a clear argument. Fancy lexis on a vague claim still scores mid-band.

Try this yourself

Prompt: Some people say that children spend too much time on digital devices. What problems does this cause, and what solutions can you suggest?

1. Outline two concrete problems (sleep/attention; weaker offline social practice) and two workable solutions (school phone policies; family device agreements).
2. Write under time pressure.
3. Run your technology essay through the checker and ask whether solutions are specific enough to raise Task Response.
4. Optional second pass: rewrite only your solutions paragraph with measurable actions.

More structure help: problem-solution essay structure · Task 2 checker.

Next steps

Build a technology idea bank around labour, attention, privacy, education tech, and remote work. Model the Band 9 safeguards pattern above, then pressure-test it on a fresh prompt with IELTS AI Tutor. Check pricing for ongoing practice, or signup to start.

Frequently asked questions

Should I mention specific apps or brands?

Usually no. Prefer categories (social platforms, hiring algorithms) unless a generic example needs a familiar type.

Is “discuss both views” always 50/50?

Cover both views fully, but your opinion can clearly prefer one side with conditions — as in the sample.

How is this different from the Band 7 technology sample?

Different prompt and higher precision: conditional opinion, tighter mechanisms, less safe repetition. Compare both: Band 7 technology sample.