Purpose:Develop an AI model to classify sea objects while understanding machine learning, the importance of accurate data, bias in AI systems, and their social impact.

Exercise:

• Step 1: Click here to go to the code.org's Ocean activity page

  1. Help the AI bot identify whether an object in the ocean is trash or a fish.
  2. Help the AI bot identify different sea creatures, including fish.
  3. Help the AI bot categorize features such as a fish’s mouth, dorsal fin, and colour.
  4. Observe how biased concepts can lead to biased or prejudiced data.



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• Step 2: Learn what happens when incorrect data is given to an AI system and how it affects future predictions.

Solutions

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• Link to view the solution for step-1.
• Link to view the solution for step-2.

1. Teachers should explain to the students how to play the game.
2. Sign up for a teacher account and keep it in another tab before using the code.org exercise.
3. Assist students remove any issues and fix them until their code works properly.
4. Can AI learn only if we explicitly train with labelled data or can it learn on its own?
5. What is more important for AI learning: the number of examples or the diversity of examples?