You have access to the training data that was used to train an AI-based system. You can review this information and use it as a guideline when creating your tests. What type of characteristic is this?

Question

Options

• AAutonomy
• BExplorability
• CTransparency
• DAccessibility

• A
  15% (6)
• B
  8% (3)
• C
  72% (28)
• D
  5% (2)

Explanation

AI-based systems can sometimes behave like black boxes, where the internal decision-making process is unclear. Transparency refers to the ability to inspect and understand the training data, algorithms, and decision-making process of the AI system. Transparency ensures that testers and stakeholders can review how an AI system was trained. Access to training data is a key factor in transparency because it allows testers to analyze biases, completeness, and representativeness of the dataset. Transparency is an essential characteristic of explainable AI (XAI). Having access to training data means that testers can investigate how data influences AI behavior. Regulatory and ethical AI guidelines emphasize transparency. Many AI ethics frameworks, such as GDPR and Trustworthy AI guidelines, recommend transparency to ensure fair and explainable AI decision-making.

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