Standard 3 stops to get here

Fairness

Ensuring AI systems treat all individuals and groups equitably, without discrimination based on protected attributes.

Your route here

3 stops · basics first
  1. Dataset ✓ understood

    A collection of data examples used for training, validating, or testing machine learning models.

  2. Training Data ✓ understood

    The examples a model learns its weights from, kept separate from the validation and test data used to check how well it generalizes.

  3. Bias in AI ✓ understood

    Systematic errors or unfair outcomes in AI systems, often reflecting biases in training data or model design.

  4. Fairness · you are here ✓ understood

Where it sits

Before this

Bias in AI
Fairness

Leads to

Nothing yet: a destination in its own right.

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