The following text discusses machine learning bias.
Algorithmic systems trained on historical data often replicate past discriminatory patterns. Hiring algorithms have shown bias against women when trained on male-dominated hiring histories. More troublingly, such biases may be obscured by algorithmic opacity—the difficulty of understanding how complex models reach decisions. Researchers developing "explainable AI" aim to make algorithmic reasoning transparent, though interpretability often trades off against predictive accuracy.
Which choice best describes the overall structure of the text?
It identifies a problem, explains its aggravating factors, and notes responses with trade-offs.
It provides a complete history of artificial intelligence development.
It argues that all machine learning should be abandoned.
It compares bias in different types of algorithms.
Correct Answer: A
Choice A is the best answer. The text identifies bias, notes opacity as aggravating factor, and describes explainable AI as response with trade-offs (interpretability vs. accuracy).
- Evidence: The text identifies the problem: "replicate past discriminatory patterns." It notes an aggravator: "obscured by algorithmic opacity." It notes response/trade-off: "explainable AI... often trades off against predictive accuracy."
- Reasoning: The structure is Problem -> Complication -> Attempted Solution with Flaw.
- Conclusion: This matches "identifies a problem, explains its aggravating factors, and notes responses with trade-offs."
💡 Strategy: Track the flow: Bias -> Opacity -> Trade-off.
Choice B is incorrect because history isn't provided. Choice C is incorrect because abandonment isn't advocated. Choice D is incorrect because algorithm types aren't compared.