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Set 10: Rhetorical Synthesis (Intermediate)

Explanation

Answer: B

PASSAGE

A student is writing about algorithmic bias. The student wants to trace how bias enters AI systems and manifests in their outputs. Notes: - Training data often reflects historical discrimination patterns. - Human labelers bring their own biases to data annotation. - Optimization goals may inadvertently encode biased outcomes. - Biased algorithms perpetuate discrimination in hiring, lending, and criminal justice.

Which choice most effectively uses information from the notes to accomplish the student's goal?

A. AI systems rely on large datasets to learn patterns and make predictions.
B. Algorithmic bias enters through training data reflecting historical discrimination, human labelers introducing their biases, and optimization goals encoding unfair outcomes—ultimately manifesting as perpetuated discrimination in critical decisions like hiring, lending, and criminal justice.✓ Correct
C. Algorithmic bias has affected decisions in hiring, lending, and criminal justice.
D. Researchers are developing methods to detect and mitigate algorithmic bias.

Detailed Answer Explanation

This question asks you to effectively combine information to achieve a goal. The goal is to TRACE how bias ENTERS and MANIFESTS. Training data, labelers, optimization (entry points) → hiring/lending/justice (manifestation). The correct synthesis will use relevant details from the notes in a logical, purposeful way. Focus on what the question asks you to accomplish, then choose the answer that best achieves that goal using the provided information. Effective synthesis requires selecting and combining the most relevant information to achieve a specific purpose. Not all provided notes may be equally useful. Focus on what best accomplishes the stated goal while maintaining logical coherence.

Key Evidence:

• "trace how bias enters AI systems and manifests"

• "Training data often reflects historical discrimination"

• "Human labelers bring their own biases"

• "Optimization goals may inadvertently encode"

• "perpetuate discrimination"

Why others are wrong: C (Shows manifestation but doesn't trace entry points.), D (Not in notes; discusses solutions, not bias pathway.), A (Describes AI learning but not bias pathways.).

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