Singapore, 1984. The Girl and the Machine.

Jasmine was five years old when the machine arrived.

Her father brought home a Macintosh 128K — one of the very first in Singapore. It sat on the desk in the study, its small screen casting a pale glow, making a cheerful sound when it started up.

Most people her father spoke to thought it was not a good idea. Especially for a child.

The concern was not dramatic, just a quiet, general sense that a machine doing things for you would make you think less. That it wasn’t good for the brain.

“If the machine does it for her, she’ll use her brain less. How will she learn to think?”

Her father disagreed. He was a reader of Arthur C. Clarke, a believer in technology, and he had a different idea of what the machine could do for a curious child. He let her near it.

What most Singaporeans don’t know: Apple has had a presence here since July 1981, initially around the Apple II, and later manufacturing Macintosh computers right here in Ang Mo Kio. By 1998, that plant was turning out one Bondi Blue iMac every 15 seconds. The machine that people feared was, in part, made here.

Primary School. The IBM and the Screwdriver.

When Jasmine reached Primary 1, her father moved on to an IBM. She loved Pac-Man.

Eventually, the old Macintosh needed fixing – so one day he picked up a screwdriver and opened it up with Jasmine beside him. They looked inside together. No tutorials, no forums, no hand-holding. Just her dad, a machine, and a manual.

By her teens, she was building her own Windows PCs from parts bought at Sim Lim Square.

Shenton Way, 1985. The Accountant Who Nearly Got Fired for Using a Spreadsheet.

While Jasmine was learning about machines in the study at home, something was playing out in the office towers of the financial district that followed exactly the same pattern.

Microsoft released Excel in 1985. At the company where Jasmine’s father worked, one finance analyst – a careful, methodical man who had spent a decade doing quarterly reconciliations by hand – adopted it the moment it was available.

He completed the next reconciliation in one afternoon. Alone. Work that had previously required three people over four evenings.

The response from his seniors was not congratulation. It was a meeting behind closed doors.

The concern was put plainly: if the machine was doing the accounting, was the finance department still thinking? Would they lose their feel for when a number was wrong? Their instinct for anomaly? Their discipline?

A version of this memo circulated across dozens of banks in Asia between 1985 and 1987:

Within a decade, every person in every bank on Shenton Way was using Excel. The analysts who had resisted were now behind. The ones who had adapted earliest had gone furthest – doing financial modelling, scenario analysis, stress-testing. Work that the manual process had never left them time to attempt.

The spreadsheet had not removed numerical thinking. It had elevated it – from arithmetic drudgery to genuine financial intelligence. The memo was forgotten. Nobody mentioned it at the retirement parties.

The Pattern. It Has Happened Every Single Time.

We are not dealing with a new fear. We are dealing with a very old one, wearing new clothes.

1440 – The Printing Press: Scribes and scholars warned that printed books would spread unverified ideas, flood the market with cheap imitations of real knowledge, and make readers passive recipients rather than active memorisers of text. Memorisation, they said, was how you truly understood something.

1970 – The Calculator: When handheld calculators arrived in classrooms, mathematics teachers across the US, UK, and Singapore formally objected. Students would lose numerical sense, stop understanding the why behind arithmetic, become dependent on a machine. Several school boards banned calculators outright until the 1980s.

1984 — The Macintosh: The Mac’s word processor didn’t write the essay. It freed the writer to think about structure, argument, and language – rather than the physical act of transcription. But to those watching from outside, the clean output looked suspicious. Too easy. Not enough visible struggle.

1985 – Excel: The spreadsheet didn’t remove numerical thinking. It elevated it – from arithmetic drudgery to financial analysis. The accountants who resisted fell behind. The ones who adapted became strategists.

1995 – The Internet: Encyclopaedia Britannica, school librarians, and a great many newspaper columnists warned that Google-before-Google would end the discipline of research. Students would get used to instant answers. Deep reading would die. The university essay would become a cut-and-paste exercise.

Now – AI: You have heard this one recently. Perhaps in a school WhatsApp group. Perhaps from a well-meaning parent at a meet-the-teacher session. It is the same argument. It has the same emotional shape. And it is, in the same way as before, not entirely wrong about the risk – but completely wrong about the remedy.

AI Is Not Passive. It Is the Opposite of TikTok.

The fear usually conflates two very different things: AI as a shortcut (a child pastes a question, copies an answer, learns nothing) versus AI as a thinking partner (a child works through a problem, asks follow-ups, verifies, refines, and arrives somewhere they could not have reached alone).

Scrolling a feed is passive. The brain receives without effort. Using an AI tool well is closer to having a tutor available at 11pm – one who never gets impatient and never makes you feel stupid for not knowing something.

Here is what the evidence actually says:

AI requires active engagement. To get a useful answer, a child must articulate the question clearly. That is a genuine cognitive skill – one that even most adults struggle with. Vague prompts produce vague answers. The feedback is immediate and honest.

It teaches higher-order thinking. AI can be wrong. Children learn this quickly. Fact-checking an AI answer, cross-referencing, pushing back – this is analytical reasoning in practice, not in theory.

The calculator didn’t kill maths. It shifted what maths meant. AI is doing the same. Rote recall is becoming less valuable. Synthesis, judgment, and creative problem-framing are becoming more valuable. Schools that adapt will produce graduates who thrive.

Digital literacy is survival. The World Economic Forum has been consistent: AI fluency is among the most critical skills for the coming decade. A child shielded from AI today is like a child banned from learning to type in 1995.

It helps the students who need it most. Shy students, anxious students, students who won’t raise their hand in class – AI gives them a judgment-free space to ask questions, go at their own pace, and get feedback without shame. The research on this is increasingly strong.

The risk is misuse, not use. Unsupervised, undirected AI can be harmful. The answer is better guidance – not zero AI. A structured classroom with a trained teacher is exactly the right environment to build healthy habits.

When Parents Push Back, They Push Against MOE Itself.

Singapore’s Ministry of Education has formally encouraged AI integration in schools as part of preparing students for the future economy. When parents pressure teachers – through WhatsApp groups, parent-teacher meetings, or formal feedback – to avoid using AI tools in the classroom, they are not just disagreeing with a single teacher’s method.

They are working against national education policy.

Teachers are caught in an uncomfortable position: they are being asked to modernise their pedagogy and introduce AI, but then face parent complaints and group-chat pressure. Doing the professionally right thing starts to feel risky. That is demoralising, and it is unsustainable.

What parents can do instead of pushing back: ask teachers how AI is being used – process transparency is entirely reasonable. Talk to their children about using AI as a thinking aid, not a shortcut. Trust that MOE has thought carefully about age-appropriate use and safeguards.

What Happened to Jasmine.

Jasmine went on to study aerospace engineering in the UK, graduating in the top 10 of her cohort. The concern that the Mac would make her think less was not borne out.

In 2016, she co-founded Empire Code – now Empire AI – alongside Felicia Chua, who grew up in education: her mother spent 40 years teaching in MOE schools.

That combination of technology and pedagogy shaped how Empire AI was built: thinking ahead, but always grounded in how children actually learn.

Together, they have sat across from hundreds of Singapore parents over the years and heard the same concern in different forms: about coding, about screens, about the internet, and now about AI. The concern is always recognisable. It is the same one people raised about the Mac in 1984.

The students at Empire AI whose parents are having this conversation right now are learning to prompt, to question, to verify, to build. Their teachers are guiding them. The environment is structured and purposeful.

The machine didn’t do their thinking for them. It taught them to think one step further.

The Risk Is Never the Tool. The Risk Is the Tool Without Guidance.

Every generation has had its Mac moment. This one is ours. The question was never whether to let children near the machine – it was always who would teach them to use it well.

For further commentary, click to watch our video, “AI and Our Kids: Are We Raising a Generation That Can’t Think?”

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