Which of the following is not a source of Artificial Intelligence bias?

Question

UnlockIAS · Accepted Answer

Correct — D, Ability. The widely-recognized sources of bias in AI systems are: Data (biased or unrepresentative training data), Algorithm (biased model design or optimization choices), and People (human bias introduced by developers, labelers, or users). 'Ability' is not part of this standard taxonomy of AI-bias sources.

Why the other options are wrong — (a) Biased, incomplete, or unrepresentative training data is one of the most common sources of AI bias — e.g., under-representing certain groups.  (b) The way a model is designed, weighted, or optimized can itself introduce systematic bias, independent of the data used.  (c) The humans who collect, label, and interpret data — and who use the AI's output — can introduce their own conscious or unconscious biases.

Concept: AI bias refers to a systematic, unfair skew in an AI system's outputs. It is commonly traced to three sources: biased training Data, biased Algorithm design, and biased People (the developers, labelers, or users involved in building and operating the system). Recognizing all three is central to designing fairer, more accountable AI.

State PCS 2022 Q50 — Science & Technology PYQ with Answer

State PCS 2022 Q50 — Science & Technology PYQ with Answer