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The passage below is accompanied by four questions. Based on the passage, choose the best answer for each question. Imagine a world in which artificial intelligence is entrusted with the highest moral responsibilities: sentencing criminals, allocating medical resources, and even mediating conflicts between nations. This might seem like the pinnacle of human progress: an entity unburdened by emotion, prejudice or inconsistency, making ethical decisions with impeccable precision. . . . Yet beneath this vision of an idealised moral arbiter lies a fundamental question: can a machine understand morality as humans do, or is it confined to a simulacrum of ethical reasoning? AI might replicate human decisions without improving on them, carrying forward the same biases, blind spots and cultural distortions from human moral judgment. In trying to emulate us, it might only reproduce our limitations, not transcend them. But there is a deeper concern. Moral judgment draws on intuition, historical awareness and context - qualities that resist formalisation. Ethics may be so embedded in lived experience that any attempt to encode it into formal structures risks flattening its most essential features. If so, AI would not merely reflect human shortcomings; it would strip morality of the very depth that makes ethical reflection possible in the first place. Still, many have tried to formalise ethics, by treating certain moral claims not as conclusions, but as starting points. A classic example comes from utilitarianism, which often takes as a foundational axiom the principle that one should act to maximise overall wellbeing. From this, more specific principles can be derived, for example, that it is right to benefit the greatest number, or that actions should be judged by their consequences for total happiness. As computational resources increase, AI becomes increasingly well-suited to the task of starting from fixed ethical assumptions and reasoning through their implications in complex situations. But what, exactly, does it mean to formalise something like ethics? The question is easier to grasp by looking at fields in which formal systems have long played a central role. Physics, for instance, has relied on formalisation for centuries. There is no single physical theory that explains everything. Instead, we have many physical theories, each designed to describe specific aspects of the Universe: from the behaviour of quarks and electrons to the motion of galaxies. These theories often diverge. Aristotelian physics, for instance, explained falling objects in terms of natural motion toward Earth's centre; Newtonian mechanics replaced this with a universal force of gravity. These explanations are not just different; they are incompatible. Yet both share a common structure: they begin with basic postulates - assumptions about motion, force or mass - and derive increasingly complex consequences. . . . Ethical theories have a similar structure. Like physical theories, they attempt to describe a domain - in this case, the moral landscape. They aim to answer questions about which actions are right or wrong, and why. These theories also diverge and, even when they recommend similar actions, such as giving to charity, they justify them in different ways. Ethical theories also often begin with a small set of foundational principles or claims, from which they reason about more complex moral problems.


The passage compares ethics to physics, where different theories apply to different aspects of a domain and says AI can reason from fixed starting points in complex cases. Which one of the assumptions below must hold for that comparison to guide practice?

Options

A

There is a principled way to decide which ethical framework applies to which class of cases, so the system can select the relevant starting points before deriving a recommendation.

B

Real cases never straddle different areas, so a case always fits exactly one framework without any overlap whatsoever.

C

A single master framework replaces all others after translation into one code, so domain boundaries disappear in application.

D

Once formalised, all ethical frameworks yield the same recommendation in every case, so selection among them is unnecessary.

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Correct Answer :

Option A

There is a principled way to decide which ethical framework applies to which class of cases, so the system can select the relevant starting points before deriving a recommendation.

Solution :

The correct answer is: There is a principled way to decide which ethical framework applies to which class of cases, so the system can select the relevant starting points before deriving a recommendation.

To understand why this is the correct assumption, let us break down the logical reasoning presented in the passage step-by-step.

First, the author establishes how formalisation operates in the realm of physics. The passage explicitly notes that there is "no single physical theory that explains everything." Instead, scientists rely on multiple, often diverging theories that are designed to describe "specific aspects of the Universe" (such as the behavior of quarks versus the motion of galaxies). Despite their differences, these physical theories share a common structure: they start from basic, fixed postulates and logically derive consequences.

Next, the passage draws a direct analogy between physics and ethics, stating: "Ethical theories have a similar structure." This implies that the complex "moral landscape," much like the physical universe, is best navigated using multiple ethical frameworks rather than a single, universal one. Concurrently, the author points out that Artificial Intelligence is "increasingly well-suited to the task of starting from fixed ethical assumptions and reasoning through their implications in complex situations."

If we combine these two ideas—that AI can reason logically from fixed starting points, and that there are multiple ethical theories for different aspects of morality—a practical problem arises. When an AI faces a new, complex moral situation, it has multiple sets of "fixed ethical assumptions" to choose from. Just as a physicist must know whether to apply quantum mechanics or general relativity to a given problem, the AI must know which ethical theory applies to the situation at hand.

Therefore, for this theoretical comparison to actually guide the practical design of an AI, there must be a reliable, structured method to categorize cases and match them to the correct ethical theory. We must assume that there is a "principled way to decide which ethical framework applies to which class of cases." Without this assumption, the AI would have no basis for selecting the relevant starting points to begin its ethical reasoning.

The other options are incorrect because they either contradict the passage or are overly extreme. Assuming that cases "never straddle different areas" is a rigid absolute not supported by the nuanced text. Assuming a "single master framework replaces all others" or that "all ethical frameworks yield the same recommendation" directly contradicts the author's statements that theories diverge and justify actions in different ways.

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