---
title: "AI Mistakes and Limitations"
description: "AI uses mathematical rules and data to make predictions. Missing or mistaken training examples and unclear inputs can contribute to errors. Explore mistakes and ways to check predictions."
canonical: https://lightmysky.com/learn/computing/ai-mistakes-and-limitations-mt_bPFToj0OhZ
source: https://lightmysky.com/learn/computing/ai-mistakes-and-limitations-mt_bPFToj0OhZ.md
retrieved: 2026-11-12
---

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# AI Mistakes and Limitations

AI uses mathematical rules and data to make predictions. Missing or mistaken training examples and unclear inputs can contribute to errors. Explore mistakes and ways to check predictions.

Subject: Computing · Area: Artificial Intelligence · Ages 7 to 9
Page: https://lightmysky.com/learn/computing/ai-mistakes-and-limitations-mt_bPFToj0OhZ

## Ready when they can

- Give an example of AI making a mistake, such as mishearing speech or changing typed text incorrectly
- Explain how missing examples or mistaken labels in training data can contribute to AI errors
- Describe how AI uses mathematical rules and data to make predictions

## Lesson: When AI Gets It Wrong

You have learned how a picture sorter trains on examples. AI uses mathematical rules and data to make predictions. A voice helper predicts words from sounds. Autocorrect can suggest changes to typed words. A recommendation tool can use earlier choices as clues. Each can make mistakes.

**Example.** Imagine a sorter calling a muffin a puppy. Both might look brown and round in a photo. Missing training examples could also matter. A sorter shown mostly retrievers may struggle with poodles. These are possible explanations. A mistaken guess alone does not tell us exactly what caused it.

*(drawing: This made-up test used 10 new photos. Eight guesses matched their known labels and two did not.)*

Missing examples and mistaken labels can teach misleading patterns. Blurry photos or unclear sounds can cause trouble too. Useful training examples can help, but do not promise perfect answers. Check guesses on new examples against known answers. Look for when mistakes happen before deciding what to change.

**Recap.** AI uses maths and data to predict. Training problems and unclear inputs can cause mistakes. Check guesses on new examples.

*Lesson, questions and flashcards written for this dataset. The photo examples and test results are invented teaching examples.*

## Practice

8 questions on this page, each with its working shown.

## Needs first

- [Machine Learning Basics](https://lightmysky.com/learn/computing/machine-learning-basics-mt_K6qtan847r)

## Opens up

- [Bias in AI Systems](https://lightmysky.com/learn/computing/bias-in-ai-systems-mt__BbOjiY5A5)
- [Learning with an AI without handing over the thinking](https://lightmysky.com/learn/learning-to-learn/learning-with-an-ai-without-handing-over-the-thinking-mt_cw3agzDhxN)
- [Deepfakes and AI-Generated Content](https://lightmysky.com/learn/computing/deepfakes-and-ai-generated-content-mt_tzMr83pS8v)