The phenomenon of discriminatory AI results caused by biased training data is known as what?

The phenomenon of discriminatory AI results caused by biased training data is known as what?

• A. Bias in AI
• B. Fairness in AI
• C. Transparency in AI
• D. Privacy in AI

Answer: (A)

Discriminatory results in AI occur when the data used to train the model contains biases or stereotypes, and the model learns those patterns, producing unfair predictions for certain groups. This phenomenon is called bias in AI. It highlights how data quality and representation directly shape model behavior. Fairness in AI is about reducing those biases and ensuring equitable treatment across groups. Transparency in AI refers to making how the model works and why it makes certain decisions understandable. Privacy in AI focuses on protecting individuals’ data used in training and deployment. So, the term that best names the described issue is bias in AI.

Discriminatory results in AI occur when the data used to train the model contains biases or stereotypes, and the model learns those patterns, producing unfair predictions for certain groups. This phenomenon is called bias in AI. It highlights how data quality and representation directly shape model behavior.

Fairness in AI is about reducing those biases and ensuring equitable treatment across groups. Transparency in AI refers to making how the model works and why it makes certain decisions understandable. Privacy in AI focuses on protecting individuals’ data used in training and deployment.

So, the term that best names the described issue is bias in AI.