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Quantum Computing: What Parents Need to Know for Kids' Future
Quantum computers aren't faster at everything — they excel at specific problems like cryptography and chemistry simulation. Here's an honest explainer for parents and kids.
The headline said “Google Achieves Quantum Supremacy.” The article was from 2019. Seven years later, I still get emails from parents asking: “Should my kid learn quantum computing? Is this actually going to matter in their lifetime?”
The answer is: probably yes, but on a longer timeline than most headlines suggest. And the version that matters for a kid entering college in 2030 is very different from the version that will matter for a career in 2040.
Let me give you the version without the mysticism, because the genuine capabilities are interesting enough without it.
Key Takeaways
- Qubits use superposition and entanglement to represent and process information in ways that classical bits can’t — but this doesn’t mean “computing everything at once”
- Quantum computers have proven advantage over classical computers at specific mathematical tasks — not general computing
- Their most significant near-term impact is cryptography: current encryption relies on problems quantum computers will eventually solve easily
- IBM, Google, IonQ, and others are actively building and improving quantum hardware; the field is real and advancing
- For kids entering careers in 10+ years, cryptography, chemistry simulation, and materials science are the domains where quantum fluency will be most valuable
What Qubits Are (Without the Mysticism)
Classical computers store information in bits — each bit is either 0 or 1. A quantum computer stores information in qubits (quantum bits), which can exist in a superposition of 0 and 1 simultaneously.
Here’s an analogy that’s useful without being wrong: a classical bit is like a coin lying flat — it’s either heads or tails. A qubit is like a spinning coin — it has some probability of being heads and some probability of being tails, and you only find out which when you catch it (measure it). During computation, the qubit can be in both states simultaneously.
The thing that makes this computationally useful is that you can run operations on all possible states at once. For certain problems — specifically, problems that can be expressed as searching through a large space of possibilities — this gives quantum computers enormous theoretical advantages.
Entanglement is the other key property. When two qubits are entangled, measuring one instantly affects what you’ll measure from the other, regardless of distance. This allows quantum computers to coordinate information across qubits in ways that have no classical equivalent, enabling certain algorithms that would be impossible classically.
What “Quantum Supremacy” and “Quantum Advantage” Mean
Google’s 2019 claim of “quantum supremacy” meant their Sycamore quantum processor completed a specific calculation in 200 seconds that would have taken a classical supercomputer 10,000 years (Arute et al., 2019). IBM disputed the exact numbers, but the directional point held: there exists a calculation where quantum hardware is dramatically faster.
The important caveat: that specific calculation was essentially useless. It was a random circuit sampling problem designed to demonstrate quantum advantage, not to solve a real-world problem. “Quantum supremacy on a toy problem” is meaningful as a proof of principle, not a demonstration of practical utility.
“Quantum advantage” is the more useful term — demonstrating that a quantum computer solves a practically useful problem better than classical alternatives. Researchers are actively working toward this; as of 2026, it has been demonstrated in limited research contexts but not yet in broad commercial applications.
What Quantum Computers Are Actually Better At
Quantum computers are not faster at everything. They’re not going to run your web browser faster, process spreadsheets quicker, or make video games run better. Classical computers will remain dominant for those tasks.
Quantum computers have theoretical (and in some cases demonstrated) advantages for:
| Problem Type | Why Quantum Helps | Real-World Application |
|---|---|---|
| Integer factorization | Shor’s algorithm: exponential speedup | Breaking RSA encryption |
| Database search | Grover’s algorithm: quadratic speedup | Some search and optimization |
| Quantum chemistry simulation | Natural fit — models quantum systems | Drug discovery, materials science |
| Optimization (traveling salesman type) | Potential advantages on some formulations | Logistics, finance, scheduling |
| Machine learning (some algorithms) | Potential speedup for specific linear algebra operations | QML research, uncertain practical timeline |
| Sampling from probability distributions | Natural fit for quantum systems | Physics simulation, random number generation |
The most concerning application — for existing infrastructure — is cryptography. Current internet security relies heavily on RSA encryption, which depends on the difficulty of factoring large numbers. Shor’s algorithm, run on a sufficiently large quantum computer, breaks RSA efficiently. The “sufficiently large” part is the sticking point: the quantum computer would need millions of error-corrected logical qubits. Today’s best systems have hundreds to thousands of noisy physical qubits. But the direction of progress is clear.
The US National Institute of Standards and Technology (NIST) completed a multi-year process to standardize quantum-resistant cryptography algorithms in 2024, specifically because the threat to current encryption is taken seriously at a government level (NIST, 2024).
Where the Hardware Actually Is
As of 2026, three main approaches to quantum hardware compete:
Superconducting qubits — IBM and Google’s primary approach. Qubits are circuits cooled to near absolute zero (colder than outer space). IBM’s Eagle processor (127 qubits) and Osprey (433 qubits) are examples. Advantage: faster gate operations. Disadvantage: requires extreme cooling, large physical infrastructure.
Trapped ion qubits — IonQ and Honeywell’s approach. Individual ions are held in electromagnetic traps and manipulated with lasers. Advantage: much lower error rates per qubit, entanglement maintained longer. Disadvantage: slower gate operations than superconducting.
Photonic qubits — companies like PsiQuantum are building systems using photons (light particles). Advantage: room temperature operation possible, inherently low decoherence. Disadvantage: single-photon detection is technically challenging; commercially viable systems are further out.
All of these are NISQ (Noisy Intermediate-Scale Quantum) devices — they have significant error rates that limit the depth of computations possible. Fault-tolerant quantum computing — the real target — requires quantum error correction, which needs roughly 1,000 physical qubits to encode each reliable logical qubit. A fault-tolerant system capable of breaking RSA would need millions of physical qubits. Most experts place this 10–20+ years away.
How to Teach Your Kid About Quantum Computing
Ages 5–8: The Coin Flip Game
Flip a coin multiple times. While it’s in the air, “it’s both heads and tails at the same time — we don’t know until it lands.” That’s superposition. “If two coins are ‘magic friends’ and one lands on heads, the other always lands on tails even in another room” — that’s entanglement (oversimplified but captures the essential surprise). Explain: scientists are using these strange quantum properties to build new kinds of computers.
Ages 9–12: The Maze Metaphor
A classical computer solves a maze by trying paths one at a time (or many simultaneously, if parallel). A quantum computer can try all paths simultaneously — and the “wrong” paths cancel out through interference, leaving only the correct path. This is the intuition behind quantum interference. Watch the IBM Quantum Experience demonstration videos together — IBM has public quantum hardware that anyone can program (quantum-computing.ibm.com). Kids can even run simple quantum circuits on real IBM hardware for free.
Ages 13+: Real Quantum Programming
IBM’s Qiskit is a free Python library for quantum computing. The IBM Quantum Learning platform has tutorials that teach quantum programming from scratch, and the actual quantum computers are accessible for free up to certain limits. A motivated teenager can run their first actual quantum program on real quantum hardware in an afternoon. The “Hello World” of quantum computing — creating and measuring a Bell state (two entangled qubits) — is accessible with basic Python knowledge.
The question to ask: “If quantum computers will eventually break current internet passwords — what’s being done to prepare for that?”
What to Watch For Over the Next 3 Months
Month 1: Watch for IBM’s annual quantum hardware roadmap update. IBM releases detailed technical roadmaps; comparing year-over-year progress is a reliable way to track the field.
Month 2: Look for NIST post-quantum cryptography news. The US government’s plan to transition internet security to quantum-resistant algorithms is the real near-term quantum story with direct impact on everyday technology.
Month 3: If your teen is interested in computer science, suggest they try the IBM Quantum Learning modules. Even a basic introduction to quantum gates builds the vocabulary they’ll need if this field advances during their career.
Frequently Asked Questions
Will quantum computers make current passwords and encryption useless?
Eventually, yes — for encryption based on factoring (RSA) and discrete logarithm problems. But current quantum computers are nowhere near capable of breaking real-world encryption. The timeline for this threat is 10–20+ years, and the security community is already developing and deploying quantum-resistant alternatives. Your passwords are safe for now.
Should my kid study quantum computing?
At the k-12 level, studying the concepts is worthwhile as background knowledge. Serious quantum computing work requires strong foundations in linear algebra, probability, and quantum mechanics — typically college-level. Kids interested in the field should focus on mathematics and classical programming first; the quantum layer builds on those foundations.
Is quantum computing the same as AI?
No. They’re different technologies, though there’s research on combining them (quantum machine learning). Classical computers run current AI systems. Quantum computers are better suited for specific mathematical problems like simulation and optimization. Calling quantum computing “AI” is a common misconception in popular press.
What careers will involve quantum computing?
Research roles (academia and national labs), quantum hardware engineering, quantum software development, cryptography and security (both breaking and defending), pharmaceutical research (drug simulation), and materials science. These are specialized, technically demanding roles. The talent shortage is real — people with quantum computing knowledge are in high demand at companies like IBM, Google, IonQ, and their research partners.
About the author Ricky Flores is the founder of HiWave Makers and an electrical engineer with 15+ years of experience building consumer technology at Apple, Samsung, and Texas Instruments. He writes about how kids learn to build, think, and create in a tech-saturated world. Read more at hiwavemakers.com.
Sources
- Arute, F., Arya, K., Babbush, R., et al. (2019). “Quantum Supremacy Using a Programmable Superconducting Processor.” Nature, 574, pp. 505–510. https://doi.org/10.1038/s41586-019-1666-5
- NIST. (2024). “Post-Quantum Cryptography Standardization.” https://csrc.nist.gov/projects/post-quantum-cryptography
- Preskill, J. (2018). “Quantum Computing in the NISQ Era and Beyond.” Quantum, 2, p. 79. https://doi.org/10.22331/q-2018-08-06-79
- IBM Research. (2023). “IBM Quantum Development Roadmap.” https://www.ibm.com/quantum/roadmap
- National Academies of Sciences. (2019). Quantum Computing: Progress and Prospects. National Academies Press. https://doi.org/10.17226/25196
- Shor, P. W. (1994). “Algorithms for Quantum Computation: Discrete Logarithms and Factoring.” FOCS 1994. https://doi.org/10.1109/SFCS.1994.365700
