CAT — Philosophy RC
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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.
Choose the one option below that comes closest to being the opposite of "utilitarianism".
The committee adopted a non-egoist framework, ranking policies by their contribution to overall social welfare and treating self-interest as a derivative concern within institutional evaluation.
The authors advocated an absolutist stance, following exceptionless rules regardless of outcomes and evaluating choices by broadest societal benefit.
The council followed a prioritarian approach, assigning greater moral weight to improvements for the worst-off rather than to maximising total welfare across the affected population.
The policy was cast as deontological ethics, selecting the option that delivered the highest total benefit to citizens while presenting duty as a secondary consideration in public decision-making.
The council followed a prioritarian approach, assigning greater moral weight to improvements for the worst-off rather than to maximising total welfare across the affected population.
Utilitarianism is defined in the passage as the principle of maximising overall wellbeing or total happiness across the greatest number. The opposite of this would be a framework that prioritises improvements for the worst-off specifically, rather than maximising aggregate welfare, which is precisely what prioritarianism does.
Why Option A is
Incorrect: This describes ranking policies by their contribution to overall social welfare, which is essentially restating utilitarianism's core principle rather than opposing it.
Why Option B is
Incorrect: Despite using the word "absolutist," this option still evaluates choices by "broadest societal benefit," which mirrors utilitarianism's logic of aggregate benefit rather than opposing it.
Why Option D is
Incorrect: This option, despite labelling itself "deontological," still selects the option with the "highest total benefit," which is utilitarian reasoning, making it inconsistent and not a true opposite.
Why Option C is Correct: This describes assigning greater moral weight to the worst-off rather than maximising total welfare, which directly contrasts with utilitarianism's core aggregative principle, making it the closest opposite.
Key Takeaway: When asked for an opposite, check the underlying logic of each option rather than just the label used, since some options use contrasting terminology but still apply the same reasoning being asked to oppose.
Which one of the options below best summarises the passage?
The passage rejects formal methods in principle. It holds that moral judgement cannot be expressed in disciplined terms and concludes that AI should not serve in courts, medicine, or diplomacy under any conditions.
The passage weighs the appeal of an impersonal AI judge against doubts about moral grasp. It claims codified schemes retain case nuance at scale and uses a physics analogy to predict convergence on a unified framework.
The passage weighs the appeal of an impersonal AI judge against doubts about moral grasp. It warns that codification can erode case-sensitive judgement, allow axiom-led reasoning at scale, and use a physics analogy to model structured plurality.
The passage highlights administrative gains from automation. It treats reproducing human moral judgement as progress and argues that, as computational resources increase, AI can be responsible for decision-making across varied institutional settings.
The passage weighs the appeal of an impersonal AI judge against doubts about moral grasp. It warns that codification can erode case-sensitive judgement, allow axiom-led reasoning at scale, and use a physics analogy to model structured plurality.
The passage weighs the appeal of an AI moral arbiter against deep doubts about whether it can truly grasp morality, warns that formalising ethics risks losing nuance and context, but also shows how AI could reason from fixed ethical starting points, using the physics analogy to illustrate how different theories can coexist without merging into one framework.
Why Option A is
Incorrect: This claims the passage rejects formal methods entirely and concludes AI should never serve in such roles, but the passage actually explores how ethics has been formalised before and how AI might apply fixed starting points, without reaching such an absolute rejection.
Why Option B is
Incorrect: This claims the passage predicts convergence on a unified ethical framework through the physics analogy, but the passage's physics analogy is used to show that theories diverge and coexist, not that they converge into one framework.
Why Option D is
Incorrect: This claims the passage treats reproducing human moral judgment as progress, but the passage explicitly raises concern that AI replicating human decisions might only reproduce human biases and limitations, not improve on them.
Why Option C is Correct: This captures the passage's balanced exploration, weighing AI's appeal against doubts about moral understanding, warning about the risk of losing nuance through codification, and using the physics analogy to illustrate structured plurality rather than convergence.
Key Takeaway: Watch for summary options that overstate the passage's position into an absolute conclusion, when the actual passage maintains a more exploratory, balanced argument.
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?
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.
Real cases never straddle different areas, so a case always fits exactly one framework without any overlap whatsoever.
A single master framework replaces all others after translation into one code, so domain boundaries disappear in application.
Once formalised, all ethical frameworks yield the same recommendation in every case, so selection among them is unnecessary.
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.
For an AI system to reason from fixed ethical starting points the way physics applies different theories to different domains, there must be a reliable, principled way to determine which ethical framework or starting point is appropriate for a given class of cases before any reasoning can proceed.
Why Option B is
Incorrect: This assumes real cases never overlap between frameworks, which is a much stronger and unrealistic assumption than what is needed, the comparison does not require this level of clean separation, only a principled way of selecting an applicable framework.
Why Option C is
Incorrect: This assumes all frameworks eventually merge into one master code, which actually contradicts the physics analogy's point about theories remaining distinct and diverging rather than collapsing into a single system.
Why Option D is
Incorrect: This assumes all frameworks always agree on recommendations, removing any need for selection, which contradicts the passage's explicit point that ethical theories diverge and justify similar actions differently.
Why Option A is Correct: This captures the minimal necessary assumption, that the system needs a principled way to pick the relevant ethical starting point for a given case before applying that framework's reasoning, mirroring how physics applies different theories to different domains.
Key Takeaway: For "must hold" assumption questions, identify the minimal condition genuinely required for the analogy to work, rather than a stronger or unrelated claim that goes beyond what's necessary.
All of the following can reasonably be inferred from the passage EXCEPT:
by analogy with physics, compact postulates can yield broad predictions across incompatible theories and ethics can likewise share structure while continuing to diverge rather than close on a single comprehensive framework.
encoding ethics into fixed structures risks stripping away intuition, history, and context and, if that occurs, the depth that enables reflective judgement disappears. So, machines would mirror our limits rather than exceed them.
the appeal of an AI judge rests on immunity to bribery, partiality, and fatigue; yet the text questions whether procedural cleanliness amounts to moral understanding without lived context and interpretive depth.
with fixed moral starting points and expanding computational resources, the argument forecasts convergence on one ethical system and treats contextual judgement as unnecessary once formal reasoning scales across domains and cultures.
with fixed moral starting points and expanding computational resources, the argument forecasts convergence on one ethical system and treats contextual judgement as unnecessary once formal reasoning scales across domains and cultures.
The passage does not forecast convergence on a single ethical system, in fact it uses the physics analogy specifically to show that theories can remain structurally similar while still diverging and coexisting as distinct frameworks, never merging into one. The passage also never claims contextual judgment becomes unnecessary, it actually raises this as a central concern throughout.
Why Option A is
Incorrect (as a candidate for the exception): This matches the passage's explicit physics analogy, that theories share structure (postulates leading to consequences) while remaining incompatible and divergent, which the passage extends to ethics as well.
Why Option B is
Incorrect (as a candidate for the exception): This matches the passage's stated concern, that encoding ethics into formal structures risks stripping away intuition, history and context, leaving machines to merely mirror human limitations rather than transcend them.
Why Option C is
Incorrect (as a candidate for the exception): This matches the passage's opening framing, the appeal of an AI free from emotion, prejudice or fatigue, set against the deeper question of whether procedural cleanliness equates to true moral understanding.
Why Option D is Correct: This contradicts the passage, which uses the physics analogy to show theories diverge rather than converge, and which raises ongoing concern about losing contextual judgment rather than treating it as something that becomes safely unnecessary.
Key Takeaway: Watch for an inference that reverses the passage's actual argument, claiming convergence and the irrelevance of context when the passage actually argues the opposite, persistent divergence and continued importance of context.
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