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AP English Language: Mixed Skills II (Drill 4)

Drill 4 · Reading · Mixed Skills II

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About This Drill

AP English Language: Mixed Skills II (Drill 4) is a Reading practice drill covering Mixed Skills II. It contains 5 original questions created by Brian Stewart, a Barron's test prep author with over 20 years of tutoring experience.

Mixed Skills II drills feature more challenging passages, historical documents, speeches, and complex argumentative prose. This drill uses a literary critical essay, with questions that ask you to identify the critic's central interpretive claim and evaluate which textual evidence most directly supports it.

Passage

The following text is adapted from a modern essay on the ethics of algorithmic decision-making. The most consequential thing we have done with artificial intelligence is not teach it to play chess, or recognize faces, or generate plausible paragraphs. The most consequential thing we have done is teach it to make decisions about people, about who gets a loan, who is flagged as a flight risk, who is recommended for a job interview, and then describe those decisions as objective. The word objective is doing a great deal of work here, and almost none of it is honest. An algorithmic decision is not objective in the way that a mathematical proof is objective. It is the product of a training process that reflects the data it was trained on, the choices made by engineers about what to optimize for, and the values, often implicit, rarely examined, embedded in the decisions of the humans whose behavior the algorithm has learned to replicate. When an algorithm trained on historical hiring data recommends fewer women for senior roles, it is not discovering a truth about women's qualifications. It is replicating a pattern that human bias produced. The algorithm does not introduce the bias. It launders it. The appeal of algorithmic decision-making is understandable. Human judges are inconsistent. Human interviewers are susceptible to irrelevant factors, attractiveness, accent, the quality of a handshake. The algorithm, at least, is consistent. It will make the same decision in the same circumstances every time. But consistency is not fairness. An algorithm that consistently disadvantages one group is not more fair than a human who inconsistently disadvantages the same group. It is more efficient at the disadvantage. There is a further problem. Human decision-makers can be questioned. A judge can be asked to explain her reasoning. A hiring manager can be challenged on her criteria. The algorithm, in most current deployments, cannot. It produces an output without an explanation, a score, a flag, a recommendation, and the people subject to those outputs often have no meaningful way to contest them. The opacity of algorithmic systems is not an accident of their technical complexity. In many cases, it is a design choice: explainability is expensive, and the costs of unexplainability fall most heavily on the people with the least power to demand it. What we need is not a moratorium on algorithmic decision-making, the efficiency gains are real, and some of the human inconsistencies these systems replace are genuinely harmful. What we need is a reckoning with the word objective: an acknowledgment that algorithmic systems encode values, that those values can be examined and contested, and that the people most affected by these decisions have a right to understand and challenge them.

Questions & Explanations

Question 1. The central claim of the essay is best summarized as

  • A) artificial intelligence systems should be banned from making decisions about individuals until their accuracy can be independently verified.
  • B) algorithmic decision-making is falsely described as objective when it actually encodes human values and biases, and those affected by it deserve transparency and the ability to contest decisions. ✓
  • C) the efficiency gains produced by algorithmic systems outweigh the risks of bias and should be embraced by institutions seeking consistent outcomes.
  • D) human decision-makers are fundamentally more reliable than algorithms because they can explain their own reasoning.

Explanation: Choice B is correct. The author argues that the label 'objective' misrepresents what algorithms do, that they replicate and launder human bias, and that those affected by algorithmic decisions deserve transparency and contestability. Choice A overstates her prescription; she explicitly argues against a moratorium. Choice C inverts her argument; she acknowledges efficiency gains but argues they do not justify the current opacity. Choice D overstates her concession; she acknowledges that human inconsistency is a real problem, not that humans are fundamentally more reliable.

Question 2. The phrase 'The algorithm does not introduce the bias. It launders it.' in the second paragraph is best understood as

  • A) a concession that algorithms are passive tools that bear no moral responsibility for the outcomes they produce.
  • B) an argument that algorithmic bias is less harmful than human bias because it operates without conscious intent.
  • C) a technical description of how machine-learning models statistically process and redistribute biased training data.
  • D) a rhetorical distinction that holds algorithms morally accountable by showing they amplify and legitimize existing bias rather than merely reflecting it. ✓

Explanation: Choice D is correct. 'Launders' implies that the algorithm does something more than passively reflect bias; it processes it through a system that produces outputs described as objective, giving the bias a veneer of neutrality and legitimacy. This makes the algorithm complicit, not merely passive. Choice A misreads 'launder' as exculpatory; the word implies complicity, not passivity. Choice B is not supported; the author does not argue that unconscious bias is less harmful. Choice C misidentifies the register; the phrase is rhetorical and ethical, not a technical description.

Question 3. The third paragraph's acknowledgment that 'human judges are inconsistent' and 'susceptible to irrelevant factors' primarily serves to

  • A) demonstrate intellectual honesty by conceding the legitimate appeal of algorithmic consistency before showing that consistency alone does not constitute fairness. ✓
  • B) introduce a counterargument from technologists that the author will spend the rest of the essay refuting.
  • C) shift the essay's focus from the ethics of algorithmic bias to the broader problem of human cognitive fallibility.
  • D) suggest that algorithmic decision-making is preferable to human judgment whenever consistency is the primary value at stake.

Explanation: Choice A is correct. The author grants the strongest version of the pro-algorithm argument, human inconsistency is real and harmful, before drawing the crucial distinction: consistency is not fairness. An algorithm that consistently disadvantages a group is more efficient at the disadvantage, not less discriminatory. The concession makes the subsequent argument more credible. Choice B misidentifies the structure; this is not a counterargument the author will refute throughout the essay but a concession she makes and then qualifies. Choice C misidentifies the shift; the paragraph remains focused on algorithmic fairness. Choice D inverts her argument; she is not endorsing algorithmic preference when consistency is valued.

Question 4. The author's claim in the fourth paragraph that algorithmic opacity is 'in many cases a design choice' primarily functions to

  • A) introduce technical evidence about the engineering constraints that make explainability difficult to achieve.
  • B) shift the essay's argument from a critique of algorithmic bias to a broader critique of the technology industry's business practices.
  • C) heighten the moral stakes by suggesting that the lack of transparency is not an unavoidable limitation but a deliberate decision whose costs are borne by the least powerful. ✓
  • D) concede that explainability is technically achievable but economically impractical for most large organizations.

Explanation: Choice C is correct. By framing opacity as a design choice rather than a technical inevitability, the author locates moral responsibility in the institutions that build and deploy these systems. The observation that 'the costs of unexplainability fall most heavily on the people with the least power' further sharpens the ethical charge. Choice A is not supported; no technical evidence about engineering constraints is cited. Choice B overstates the shift; the paragraph remains within the essay's core argument about algorithmic decision-making. Choice D describes a concession the author does not make; she argues opacity is a choice, not a practical limitation.

Question 5. The final paragraph's structure, acknowledging that 'efficiency gains are real' before calling for 'a reckoning with the word objective', mirrors which earlier rhetorical move in the essay?

  • A) The first paragraph's claim that describing algorithmic decisions as objective is dishonest.
  • B) The third paragraph's concession that human inconsistency is a genuine problem before arguing that consistency alone does not constitute fairness. ✓
  • C) The second paragraph's argument that algorithms launder rather than merely introduce human bias.
  • D) The fourth paragraph's claim that algorithmic opacity is a design choice rather than a technical constraint.

Explanation: Choice B is correct. Both the third paragraph and the final paragraph follow the same structure: acknowledge the legitimate appeal or benefit of algorithmic systems (human inconsistency is real; efficiency gains are real) before identifying the critical limitation or demand (consistency ≠ fairness; objectivity must be reckoned with). This parallel structure reinforces the essay's balanced but ultimately critical stance. Choice A identifies the essay's thesis, not a structural parallel. Choice C describes the laundering metaphor, which has a different structure. Choice D describes an argument about opacity whose structure does not parallel the final paragraph's movement.