Question 1 · Verbal Ability and Reading Comprehension
MCQ
Common Description:
The passage below is accompanied by four questions. Based on the passage, choose the best answer for each question.
Historical analysis AI systems claim neutrality by processing centuries of scientific literature through "unbiased" algorithms. Yet these systems reproduce historical exclusion: an AI trained on 19th-century physics papers systematically undervalues contributions from women and non-Western scientists because their work was rarely published in dominant journals. The designers frame this as a "data problem," but it reveals the data neutrality myth—the illusion that algorithms can transcend the biases embedded in their training corpora.
More insidiously, such AI performs historical revision by retroactively applying modern standards to past contexts. When an AI flags a 1920s paper for "lack of diversity" in its citation network, it ignores how colonial power structures limited access to publishing venues. This creates a double bind: historical work is criticized for reflecting its era's constraints, while modern work citing only "diverse" historical sources appears artificially progressive. True historical understanding requires acknowledging that every dataset is a product of its socio-technical moment—a recognition that technical-social dualism actively suppresses by separating "data" from its human context.
The phrase "double bind" in the second paragraph refers to the situation where:
Historical analysis AI systems claim neutrality by processing centuries of scientific literature through "unbiased" algorithms. Yet these systems reproduce historical exclusion: an AI trained on 19th-century physics papers systematically undervalues contributions from women and non-Western scientists because their work was rarely published in dominant journals. The designers frame this as a "data problem," but it reveals the data neutrality myth—the illusion that algorithms can transcend the biases embedded in their training corpora.
More insidiously, such AI performs historical revision by retroactively applying modern standards to past contexts. When an AI flags a 1920s paper for "lack of diversity" in its citation network, it ignores how colonial power structures limited access to publishing venues. This creates a double bind: historical work is criticized for reflecting its era's constraints, while modern work citing only "diverse" historical sources appears artificially progressive. True historical understanding requires acknowledging that every dataset is a product of its socio-technical moment—a recognition that technical-social dualism actively suppresses by separating "data" from its human context.
The phrase "double bind" in the second paragraph refers to the situation where:
Correct Answer:
B
Step-by-Step Solution
Key idea: This contextual inference question requires unpacking a metaphor through multi-concept synthesis (historical revision + technical-social dualism).
Step 1: Locate the phrase: "double bind" describes criticism of historical work for reflecting era constraints while modern work citing "diverse" sources appears artificially progressive.
Step 2: Identify the contradiction:
- Historical work: Criticized for lacking diversity (but constrained by era)
- Modern work: Praised for diverse citations (but artificially curated)
Step 3: Evaluate options:
- A: Incorrect—AI doesn't promote accuracy; it distorts it.
- B: Correct—researchers face impossible choice: accept historical constraints (criticized) or curate modern citations (artificial).
- C: Partially true but misses the bind (contradictory expectations).
- D: Describes the data neutrality myth, not the double bind.
Step 4: B captures the core contradiction in researcher expectations.
Answer: B