A Level H1 General Paper Practice Paper 1

TuitionGoWhere Practice Paper — General Paper H1 A-Level

Answer Key and Marking Scheme

Paper: Practice Paper — Paper 2: Comprehension Total Marks: 50

Section A: Short-Answer Questions [35 marks]

Question 1 [2 marks]

Question: In paragraph 1, the author states that AI systems are "now capable of performing tasks that were once the exclusive domain of trained medical professionals." What does the phrase "exclusive domain" suggest about the role of medical professionals in the past?

Answer: The phrase "exclusive domain" suggests that in the past, only trained medical professionals had the knowledge, skills, and authority to perform certain healthcare tasks. These tasks were not accessible to machines or untrained individuals. The word "exclusive" implies that this was a privileged, restricted area of practice belonging solely to qualified humans.

Marking Scheme:

• 1 mark for identifying that the tasks were performed only by trained professionals.
• 1 mark for explaining the implication of restriction/privilege (i.e., not accessible to others/machines).

Common Mistakes:

• Students may simply lift "trained medical professionals" without explaining what "exclusive domain" implies.
• Students may confuse "exclusive" with "extensive" or fail to convey the sense of restriction.

Question 2 [2 marks]

Question: In paragraph 1, the author uses the word "democratise" to describe the potential impact of AI on healthcare. Explain what the author means by this word in the context of the passage.

Answer: In this context, "democratise" means to make high-quality healthcare accessible to all people, regardless of their geographic location, socioeconomic status, or proximity to medical facilities. The author suggests that AI can level the playing field by bringing expert-level diagnosis and treatment to underserved populations who previously had limited access.

Marking Scheme:

• 1 mark for explaining the general meaning: making something available to everyone.
• 1 mark for contextualising it to healthcare (i.e., access for underserved/remote populations).

Common Mistakes:

• Students may give a political definition of "democratise" unrelated to healthcare access.
• Students may fail to connect the word to the idea of accessibility for underserved populations mentioned in the passage.

Question 3 [2 marks]

Question: In paragraph 2, the author cites a study published in Nature Medicine in 2023. Why does the author include this specific piece of evidence?

Answer: The author includes this evidence to provide concrete, credible data supporting the claim that AI can match or exceed human performance in specific diagnostic tasks. By citing a reputable journal (Nature Medicine) and specific accuracy figures (94.5% vs. 88%), the author strengthens the argument that AI has genuine potential in healthcare and is not merely speculative.

Marking Scheme:

• 1 mark for identifying that the evidence supports the claim about AI's diagnostic accuracy.
• 1 mark for explaining the effect of using a credible source/specific data (i.e., adds credibility, makes the argument persuasive).

Common Mistakes:

• Students may simply restate the statistics without explaining why the author included them.
• Students may fail to mention the persuasive/credibility function of citing a named journal.

Question 4 [3 marks]

Question: In paragraph 2, the author writes that the view that AI will replace radiologists is "overly simplistic." What does the author mean by this phrase, and what evidence does the author provide to support this claim?

Answer: The phrase "overly simplistic" means that the view is too narrow and fails to consider the full complexity of medical practice. The author argues that while AI excels at pattern recognition in specific tasks, it cannot replicate the holistic clinical judgement of human doctors. The evidence provided is that human doctors consider a patient's full history, emotional state, and social circumstances — factors that AI cannot account for.

Marking Scheme:

• 1 mark for explaining "overly simplistic" (too narrow / ignores complexity).
• 1 mark for identifying the limitation of AI (lacks holistic clinical judgement).
• 1 mark for identifying what human doctors do that AI cannot (consider patient history, emotions, social circumstances).

Common Mistakes:

• Students may only explain the phrase without providing the supporting evidence.
• Students may describe what AI can do rather than what it cannot do compared to humans.

Question 5 [2 marks]

Question: In paragraph 3, the author describes the first AI-designed drug entering Phase III clinical trials as a "watershed moment." Explain the author's use of this phrase.

Answer: A "watershed moment" refers to a turning point or pivotal event that marks the beginning of a new era. By using this phrase, the author emphasises that the entry of an AI-designed drug into Phase III trials represents a historic milestone for the pharmaceutical industry — the first time AI has progressed a drug to such an advanced stage of development, signalling a fundamental shift in how drugs are discovered.

Marking Scheme:

• 1 mark for explaining the meaning of "watershed moment" (turning point / pivotal milestone).
• 1 mark for contextualising it to the significance for the pharmaceutical industry.

Common Mistakes:

• Students may not know the meaning of "watershed" and guess incorrectly.
• Students may explain the meaning but fail to connect it to the context of drug development.

Question 6 [2 marks]

Question: In paragraph 3, the author states that "biological systems are far more complex than any algorithm can fully model." What does this suggest about the limitations of AI in drug discovery?

Answer: This suggests that AI, no matter how advanced, has inherent limitations in drug discovery because it cannot fully capture the complexity of the human body's biochemical interactions. While AI can identify promising drug candidates, it may miss critical factors that only emerge in real biological systems, which is why many AI-identified compounds still fail in clinical trials.

Marking Scheme:

• 1 mark for identifying that AI cannot fully model/comprehend biological complexity.
• 1 mark for explaining the consequence (compounds may fail in trials; AI has limits).

Common Mistakes:

• Students may simply restate the quote without explaining its implication.
• Students may fail to connect the limitation to the failure of compounds in clinical trials.

Question 7 [2 marks]

Question: In paragraph 4, the author describes AI-powered screening tools in sub-Saharan Africa as "a lifeline." What does this metaphor suggest about the impact of AI in developing regions?

Answer: The metaphor "a lifeline" suggests that AI-powered screening tools are essential and potentially life-saving for communities in developing regions. Just as a lifeline rescues someone from danger, these tools provide critical medical screening to populations that would otherwise have little or no access to such services, thereby preventing avoidable deaths and diseases like blindness from diabetic retinopathy.

Marking Scheme:

• 1 mark for explaining the metaphor (something essential / life-saving).
• 1 mark for connecting it to the context (underserved communities with no alternative access).

Common Mistakes:

• Students may explain the metaphor generically without linking it to the healthcare context.
• Students may not mention the idea of these communities having no alternative.

Question 8 [2 marks]

Question: In paragraph 5, the author mentions a hospital chain that "shared anonymised patient records with a technology company without explicit patient consent." What concern does this incident illustrate?

Answer: This incident illustrates the concern about data privacy and the lack of adequate regulatory frameworks governing the use of patient data. It shows that even when data is anonymised, the sharing of personal health information without patients' explicit consent violates their privacy rights and erodes trust in healthcare institutions.

Marking Scheme:

• 1 mark for identifying the concern about data privacy / patient consent.
• 1 mark for explaining the broader implication (regulatory gaps / erosion of trust).

Common Mistakes:

• Students may only describe the incident without identifying the underlying concern.
• Students may fail to mention the regulatory gap highlighted by the author.

Question 9 [2 marks]

Question: In paragraph 6, the author states that algorithmic bias "is not merely a technical glitch; it is a matter of equity." Explain the author's use of the word "equity" in this context.

Answer: In this context, "equity" refers to fairness and justice in healthcare outcomes across different demographic groups. The author is arguing that when AI systems perform less accurately for certain populations (e.g., those with darker skin tones), it is not just a technical problem but a fundamental issue of unfairness — it means that some groups receive inferior healthcare, which deepens existing social inequalities.

Marking Scheme:

• 1 mark for defining "equity" as fairness / justice across groups.
• 1 mark for connecting it to the consequence (deepening health disparities / unequal care).

Common Mistakes:

• Students may confuse "equity" with "equality" without explaining the distinction in context.
• Students may not connect the term to the specific issue of demographic bias in AI.

Question 10 [2 marks]

Question: In paragraph 7, the author refers to "a dangerous grey area" in relation to accountability for AI errors. What does the author mean by this phrase?

Answer: The phrase "a dangerous grey area" refers to the lack of clear legal and ethical frameworks for determining who is responsible when an AI system causes patient harm. Because it is unclear whether the hospital, the developers, or the regulators should be held accountable, this ambiguity creates a risky situation where patients may be harmed without any party being properly answerable.

Marking Scheme:

• 1 mark for identifying the lack of clarity in accountability / legal frameworks.
• 1 mark for explaining why it is "dangerous" (patients harmed without recourse; no one held responsible).

Common Mistakes:

• Students may describe the grey area without explaining why it is dangerous.
• Students may list who could be responsible without explaining the ambiguity.

Question 11 [2 marks]

Question: In paragraph 8, the author asks whether AI will "erode the humanistic dimensions of medicine." What does the author mean by "humanistic dimensions"?

Answer: The "humanistic dimensions" of medicine refer to the aspects of healthcare that go beyond technical diagnosis and treatment — namely, the empathy, trust, emotional support, and personal connection between doctor and patient. The author is concerned that over-reliance on AI could reduce healthcare to a purely mechanical process, stripping away the compassionate and relational elements that are central to healing.

Marking Scheme:

• 1 mark for identifying the non-technical aspects (empathy, trust, personal connection).
• 1 mark for explaining the concern (healthcare becoming mechanical / losing human warmth).

Common Mistakes:

• Students may give a vague answer like "the human side" without specifying what that entails.
• Students may fail to connect the term to the doctor-patient relationship.

Question 12 [2 marks]

Question: In the final paragraph, the author writes that "the future of AI in healthcare will be shaped not only by technological advances but by the choices we make as a society." What two factors does the author suggest will determine the future of AI in healthcare?

Answer: The two factors are: (1) technological advances (i.e., improvements in AI capabilities and systems), and (2) societal choices (i.e., decisions about regulation, equity, and the role of human judgement in medicine).

Marking Scheme:

• 1 mark for each factor identified (1 mark for technological advances, 1 mark for societal choices).

Common Mistakes:

• Students may only identify one factor.
• Students may paraphrase vaguely without clearly distinguishing the two factors.

Question 13 [4 marks]

Question: Throughout the passage, the author presents both the benefits and risks of AI in healthcare. Identify one benefit and one risk mentioned in the passage, and briefly explain how the author develops each point.

Answer:

Benefit (example): AI can improve diagnostic accuracy and accessibility. The author develops this by citing specific evidence — the Nature Medicine study showing AI's 94.5% accuracy in detecting breast cancer, and the sub-Saharan Africa pilot programme achieving a 91% detection rate for diabetic retinopathy. These concrete examples demonstrate AI's practical value.

Risk (example): Algorithmic bias can worsen health disparities. The author develops this by explaining that AI training datasets often underrepresent certain demographic groups (e.g., darker-skinned patients), leading to less accurate diagnoses for those populations. The author frames this not as a technical issue but as a matter of equity, elevating the significance of the risk.

Marking Scheme:

• 1 mark for identifying a valid benefit with brief explanation of how the author develops it.
• 1 mark for identifying a valid risk with brief explanation of how the author develops it.
• 1 mark for referencing specific evidence from the passage for the benefit.
• 1 mark for referencing specific evidence from the passage for the risk.

Acceptable answers include:

• Benefits: improved diagnostics, faster drug development, increased access in rural/developing areas, reduced costs.
• Risks: data privacy breaches, algorithmic bias, accountability gaps, loss of humanistic care.

Common Mistakes:

• Students may identify a benefit or risk without explaining how the author develops the point.
• Students may make general statements without referencing specific evidence from the passage.

Question 14 [4 marks]

Question: How does the author structure the passage to present a balanced argument about AI in healthcare? Refer to specific paragraphs in your answer.

Answer: The author structures the passage by alternating between the benefits and risks of AI in healthcare, creating a balanced and measured argument. Paragraphs 1–4 primarily present the benefits and potential of AI: paragraph 1 introduces the transformative potential, paragraph 2 discusses diagnostic accuracy, paragraph 3 covers drug development, and paragraph 4 highlights accessibility in developing regions. Paragraphs 5–8 then systematically address the risks and challenges: data privacy (paragraph 5), algorithmic bias (paragraph 6), accountability (paragraph 7), and the loss of humanistic care (paragraph 8). The passage concludes in paragraph 9 with a forward-looking statement that synthesises both sides, emphasising that the future depends on both technology and societal choices. This structure allows the reader to appreciate AI's potential while remaining aware of its significant challenges.

Marking Scheme:

• 1 mark for identifying the alternating/benefit-risk structure.
• 1 mark for referencing specific paragraphs that present benefits (any from paras 1–4).
• 1 mark for referencing specific paragraphs that present risks (any from paras 5–8).
• 1 mark for explaining how the conclusion synthesises both sides.

Common Mistakes:

• Students may describe the structure without referencing specific paragraphs.
• Students may only discuss benefits or only risks, failing to address the balance.

Question 15 [3 marks]

Question: The author begins paragraph 1 with a general statement about the pace of AI integration and ends the passage with a forward-looking statement about societal choices. How does this framing contribute to the overall purpose of the passage?

Answer: The opening statement about the rapid pace of AI integration immediately establishes the significance and urgency of the topic, capturing the reader's attention and signalling that this is a development that cannot be ignored. The closing statement about societal choices shifts the focus from technology alone to human agency, reinforcing the passage's purpose of encouraging critical reflection rather than passive acceptance. Together, this framing creates a narrative arc that moves from describing a technological phenomenon to urging readers to think carefully about how it should be governed. This contributes to the passage's overall purpose of presenting a balanced, thought-provoking analysis that neither celebrates nor condemns AI, but calls for informed and responsible decision-making.

Marking Scheme:

• 1 mark for explaining the effect of the opening (establishes significance/urgency).
• 1 mark for explaining the effect of the closing (shifts to human agency/critical reflection).
• 1 mark for explaining how the framing contributes to the overall purpose (balanced analysis, calls for responsible decision-making).

Common Mistakes:

• Students may describe the content of the opening and closing without explaining their rhetorical effect.
• Students may fail to connect the framing to the passage's overall purpose.

Section B: Summary Question [8 marks]

Question 16 [8 marks]

Question: Summarise the risks and challenges associated with the use of AI in healthcare, as outlined in the passage. Use your own words as far as possible. Write your summary in no more than 120 words.

Content Points (any 8 valid points for 1 mark each):

1. AI systems require vast amounts of patient data, raising concerns about data privacy and confidentiality.
2. Patient data may be shared without explicit consent, as seen in the case of a US hospital chain.
3. Existing regulatory frameworks have not kept pace with technological innovation, creating legal gaps.
4. Algorithmic bias occurs when training datasets are not representative of diverse populations.
5. AI diagnostic tools may be less accurate for certain demographic groups (e.g., darker-skinned patients).
6. This bias can perpetuate or worsen existing health disparities.
7. There is a lack of clarity about accountability when AI systems cause patient harm.
8. It is unclear whether hospitals, developers, or regulators should bear responsibility.
9. Over-reliance on AI may erode the empathetic, human connection between doctor and patient.
10. Healthcare could become a purely algorithmic process, losing the trust and warmth essential to healing.

Marking Scheme:

• Content: Up to 8 marks — 1 mark for each valid point summarised in the student's own words (maximum 8 points from the list above).
• Language: Integrated into content marks — points that are directly lifted from the passage should not be awarded marks. Students must demonstrate paraphrasing.
• Word limit: Answers exceeding 120 words should be penalised. The summary should stop being marked once the word limit is exceeded.

Sample Summary (for reference):

The use of AI in healthcare presents several risks. The technology requires enormous quantities of patient data, raising privacy concerns, especially when data is shared without consent. Regulatory frameworks have failed to keep up with these developments. Additionally, algorithmic bias is a significant challenge: AI systems trained on unrepresentative data may be less accurate for certain groups, worsening health inequalities. Accountability is also unclear — when AI causes harm, it is uncertain who should be held responsible. Finally, the increasing use of AI may diminish the empathetic relationship between doctor and patient, reducing healthcare to a mechanical process devoid of human warmth. (98 words)

Common Mistakes:

• Students may include benefits of AI rather than focusing only on risks and challenges.
• Students may lift phrases directly from the passage instead of paraphrasing.
• Students may exceed the 120-word limit.
• Students may include their own opinions or examples not found in the passage.

Section C: Application Question [7 marks]

Question 17 [7 marks]

Question: As a policy advisor, write a response to the Ministry of Health in which you:

(a) Explain two potential benefits of deploying AI diagnostic systems in public hospitals, using evidence from the passage. [3 marks]

Answer:

Benefit 1: Improved diagnostic accuracy and efficiency. The passage cites a 2023 study in Nature Medicine showing that AI correctly identified breast cancer in mammograms 94.5% of the time, compared to 88% for human specialists. This evidence suggests that AI diagnostic systems could enhance the accuracy of diagnoses in public hospitals, potentially catching conditions that human doctors might miss and reducing misdiagnoses.

Benefit 2: Increased accessibility, particularly for underserved populations. The passage describes how an AI-powered mobile application in sub-Saharan Africa achieved a 91% detection rate for diabetic retinopathy, providing screening to communities that would otherwise have no access. Similarly, deploying AI in public hospitals could extend diagnostic capabilities to underserved areas within the country, reducing waiting times and improving equity of access.

Marking Scheme (part a):

• 1 mark for identifying Benefit 1 (improved accuracy/efficiency).
• 1 mark for supporting Benefit 1 with evidence from the passage.
• 1 mark for identifying Benefit 2 (increased accessibility) with evidence from the passage.

(b) Discuss two concerns that should be addressed before the proposal is implemented, using evidence from the passage. [4 marks]

Answer:

Concern 1: Data privacy and security. The passage highlights a case where a major US hospital chain shared anonymised patient records with a technology company without explicit patient consent, leading to public outrage and legal action. Before deploying AI diagnostic systems, the Ministry must establish robust data protection regulations to ensure that patient data is collected, stored, and used with informed consent and adequate security measures. Without such safeguards, public trust in the healthcare system could be severely damaged.

Concern 2: Algorithmic bias and equity. The passage notes that some AI diagnostic tools are significantly less accurate for patients with darker skin tones because their training data was predominantly drawn from lighter-skinned populations. If the AI systems deployed in public hospitals are trained on unrepresentative data, they could produce less accurate diagnoses for certain demographic groups, worsening existing health disparities. The Ministry must ensure that training datasets are diverse and representative of the country's population, and that AI systems are rigorously tested across all demographic groups before deployment.

Marking Scheme (part b):

• 1 mark for identifying Concern 1 (data privacy) with explanation.
• 1 mark for supporting Concern 1 with evidence from the passage.
• 1 mark for identifying Concern 2 (algorithmic bias) with explanation.
• 1 mark for supporting Concern 2 with evidence from the passage.

Additional marking notes for part (b):

• Answers that discuss other valid concerns from the passage (e.g., accountability for AI errors, loss of humanistic care, job displacement) should also be accepted if supported with evidence and reasoning.
• Students should demonstrate the ability to apply passage concepts to the specific scenario, not merely restate passage content.

Common Mistakes:

• Students may discuss benefits or concerns without referencing evidence from the passage.
• Students may provide generic answers that could apply to any technology, rather than specifically addressing AI in healthcare.
• Students may introduce their own examples not found in the passage — while not penalised, the question specifically asks for evidence from the passage.

End of Answer Key

Section A Total: 35 marks Section B Total: 8 marks Section C Total: 7 marks Grand Total: 50 marks