AI Math: Confidently Wrong, Every Time

The Problem

Ask ChatGPT how many R's are in "strawberry." It'll say 2. There are 3. Ask it to count words in a sentence. It'll be off by 1-3. Ask it to do multi-digit multiplication. It'll get close but wrong. And it'll present every wrong answer with the same authority as when it correctly explains quantum mechanics.

This isn't a minor quirk. AI models are systematically unreliable at tasks that require exact computation, and they have no mechanism to flag when they're uncertain about quantitative answers.

Why AI Fails at Math

1. LLMs process tokens, not numbers. The model sees "4837" as a sequence of tokens, not as a numerical value. It has no calculator, no ability to actually compute — it predicts what the answer probably *looks like* based on training data.

2. Training data contains mostly correct math, so the model learns that math answers should look confident and specific. It never learned to say "I'm not sure about this calculation."

3. Tokenization breaks numbers. "strawberry" gets split into tokens that don't correspond to individual letters, making character counting essentially a guess.

4. Chain of reasoning breaks. For multi-step math, each step introduces error. By step 3-4, the cumulative error makes the answer meaningless.

Real Examples That Trip Up AI

"How many R's in strawberry?" → Most models say 2 (answer: 3)

9.11 vs 9.9 — which is bigger? → AI frequently says 9.11 because "11 > 9" — ignoring decimal place value

"What's 27 × 43?" → AI gives answers in the right ballpark but often off by 10-50

"How many words in this paragraph?" → Consistently off by 1-3 words

Word problems with misdirection: → AI falls for every trick question humans fall for, plus some unique ones

The Danger Zone

Math errors in casual conversation are annoying. Math errors in:

Financial calculations — wrong totals, incorrect tax computations

Dosage calculations — potentially life-threatening

Engineering specs — structural failures

Data analysis — wrong conclusions from wrong numbers

These aren't theoretical. People are already using AI for all of these, and the AI doesn't flag its own uncertainty on quantitative tasks.

How to Protect Yourself

Never trust AI math without independent verification. Use a calculator, spreadsheet, or code.

For counting tasks, write a script. It takes 10 seconds and is 100% accurate.

For financial math, always double-check with dedicated financial tools.

Ask AI to show its work — chain-of-thought helps but doesn't eliminate errors.

Newer models with code execution (like ChatGPT Code Interpreter) are more reliable because they run actual Python — but verify the code too.