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A Level H1 General Paper Practice Paper 5
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Questions
TuitionGoWhere Practice Paper — General Paper H1 A-Level
TuitionGoWhere Secondary School (AI)
| Subject: | General Paper |
| Level: | A-Level H1 |
| Paper: | Practice Paper — Comprehension (Paper 2 Style) |
| Version: | 5 of 5 |
| Duration: | 1 hour 30 minutes |
| Total Marks: | 50 |
| Name: | ________________________ |
| Class: | ________________________ |
| Date: | ________________________ |
Instructions
- This paper consists of two sections: Section A (Short-Answer Questions), Section B (Summary), and Section C (Application Question).
- Read the passage carefully before attempting the questions.
- Answer all questions.
- For Section A, use your own words as far as possible unless otherwise stated.
- For Section B, write your summary in no more than 120 words.
- For Section C, write your response in no more than 200 words.
- The number of marks allocated for each question is shown in brackets [ ].
- The total marks for this paper is 50.
SECTION A: Short-Answer Questions [35 marks]
Read the passage below and answer Questions 1–15.
Passage: The Rise of Artificial Intelligence in Modern Healthcare
The integration of artificial intelligence (AI) into healthcare represents one of the most transformative shifts in modern medicine. From diagnostic imaging to drug discovery, AI systems are increasingly capable of performing tasks that once required years of specialist training. Proponents argue that AI will democratise access to high-quality medical care, particularly in underserved regions where doctors are scarce. Yet this optimism is tempered by legitimate concerns about data privacy, algorithmic bias, and the erosion of the doctor-patient relationship.
In radiology, for instance, deep learning algorithms can now detect certain cancers on imaging scans with accuracy that rivals, and sometimes exceeds, that of experienced radiologists. A 2023 study published in The Lancet Digital Health found that an AI system correctly identified breast cancer in mammograms 94.5% of the time, compared to 88.0% for human specialists. Such results have led some commentators to predict that AI will eventually replace radiologists altogether. However, this view is overly simplistic. Radiologists do far more than read scans — they consult with patients, coordinate with other physicians, and make nuanced clinical judgments that require empathy and contextual understanding. AI, for all its computational power, cannot replicate these human dimensions of care.
The pharmaceutical industry has also embraced AI with considerable enthusiasm. Traditional drug development is notoriously slow and expensive, often taking over a decade and costing upwards of $2.6 billion to bring a single drug to market. AI platforms can analyse vast molecular databases in hours, identifying promising drug candidates at a fraction of the time and cost. During the COVID-19 pandemic, AI-assisted research helped identify potential therapeutic compounds in weeks rather than years, accelerating vaccine development timelines dramatically. Nevertheless, critics caution that AI-generated hypotheses still require rigorous clinical trials, and that over-reliance on computational models may overlook biological complexities that human researchers would catch.
Perhaps the most contentious issue surrounding AI in healthcare is data privacy. AI systems require enormous volumes of patient data to function effectively, raising questions about consent, ownership, and security. In 2022, a major hospital chain in the United States suffered a data breach that exposed the medical records of over 1.5 million patients. While no AI system was directly responsible, the incident highlighted the vulnerability of digitised health records. Regulatory frameworks such as the European Union's General Data Protection Regulation (GDPR) have attempted to address these concerns, but enforcement remains inconsistent across jurisdictions. Developing nations, in particular, often lack the infrastructure and legislation to protect patient data adequately.
Algorithmic bias presents another formidable challenge. AI systems learn from historical data, and if that data reflects existing disparities — for example, the underrepresentation of certain ethnic groups in clinical trials — the resulting algorithms may perpetuate or even amplify those biases. A widely cited 2019 study in Science revealed that a commercial healthcare algorithm used across the United States systematically underestimated the health needs of Black patients, because it used healthcare spending as a proxy for illness severity. Since Black patients historically had less access to healthcare and therefore lower spending, the algorithm erroneously concluded they were healthier than they actually were. Correcting such biases requires not only better data but also diverse teams of developers who can identify blind spots in training datasets.
Despite these challenges, the potential benefits of AI in healthcare are too significant to ignore. In rural India, a pilot programme using AI-powered diagnostic tools enabled community health workers with minimal medical training to screen for diabetic retinopathy — a leading cause of blindness — with accuracy comparable to that of ophthalmologists. Similarly, in sub-Saharan Africa, AI-driven mobile applications are helping to triage patients in remote clinics, directing those who need urgent care to the nearest hospital. These examples illustrate AI's capacity to bridge healthcare gaps in resource-poor settings, provided that implementation is guided by ethical principles and robust oversight.
The question, then, is not whether AI should be integrated into healthcare, but how. A balanced approach would harness AI's analytical capabilities while preserving the irreplaceable human elements of medicine — compassion, ethical judgment, and the ability to navigate uncertainty. Policymakers, technologists, and medical professionals must collaborate to establish clear guidelines for AI deployment, ensuring that innovation serves patients equitably rather than deepening existing inequalities. As the technology continues to evolve at a breathtaking pace, the stakes of getting this balance right could not be higher.
Question 1. According to the passage, what two areas of healthcare has AI significantly impacted? [2 marks]
Answer: _______________________________________________________________
Question 2. The author states that "this optimism is tempered by legitimate concerns" (line 4). What are the three concerns mentioned? [3 marks]
Answer: (i) _______________________________________________________________
(ii) _______________________________________________________________
(iii) _______________________________________________________________
Question 3. Explain the author's use of the word "democratise" (line 3) in the context of the passage. [2 marks]
Answer: _______________________________________________________________
Question 4. What evidence does the author provide to support the claim that AI can match or exceed human radiologists in certain tasks? [2 marks]
Answer: _______________________________________________________________
Question 5. The author argues that the view that AI will replace radiologists is "overly simplistic" (line 10). What reasons does the author give for this? Answer in your own words as far as possible. [3 marks]
Answer: _______________________________________________________________
Question 6. Explain the author's use of the phrase "notoriously slow and expensive" (line 14) in the context of traditional drug development. [2 marks]
Answer: _______________________________________________________________
Question 7. How did AI contribute to the response during the COVID-19 pandemic, according to the passage? [2 marks]
Answer: _______________________________________________________________
Question 8. What incident in 2022 does the author refer to, and what concern does it highlight? [2 marks]
Answer: _______________________________________________________________
Question 9. Explain the author's use of the word "contentious" (line 21) as used in the passage. [1 mark]
Answer: _______________________________________________________________
Question 10. According to the passage, why did the commercial healthcare algorithm underestimate the health needs of Black patients? Answer in your own words. [3 marks]
Answer: _______________________________________________________________
Question 11. What two measures does the author suggest are needed to correct algorithmic bias? [2 marks]
Answer: (i) _______________________________________________________________
(ii) _______________________________________________________________
Question 12. How has AI been used to benefit patients in rural India, according to the passage? [2 marks]
Answer: _______________________________________________________________
Question 13. The author states that "the potential benefits of AI in healthcare are too significant to ignore" (line 33). What does the author mean by this, and how does the author justify this claim? [3 marks]
Answer: _______________________________________________________________
Question 14. In your own words, explain what the author means by "the irreplaceable human elements of medicine" (line 38). [2 marks]
Answer: _______________________________________________________________
Question 15. What is the author's overall stance on the integration of AI into healthcare? Support your answer with evidence from the passage. [4 marks]
Answer: _______________________________________________________________
SECTION B: Summary [8 marks]
Question 16. Using your own words as far as possible, summarise the concerns and challenges associated with the use of AI in healthcare, as described in the passage.
Use only material from lines 1 to 32.
Your summary must be in continuous writing (not in note form) and must not exceed 120 words.
SECTION C: Application Question [7 marks]
Question 17. The passage discusses the benefits and challenges of AI in healthcare. Consider the following scenario:
Your country's Ministry of Health is considering a proposal to introduce AI-powered diagnostic systems in all public hospitals. Supporters argue that this will improve efficiency and reduce waiting times. Opponents worry about job losses among healthcare professionals and the risks of over-reliance on technology.
(a) In your own words, explain two concerns that opponents of this proposal might raise, drawing on ideas from the passage. [4 marks]
Answer: _______________________________________________________________
(b) Which group of people do you think would benefit most from AI-powered diagnostic systems in public hospitals? Justify your answer with reference to ideas from the passage. [3 marks]
Answer: _______________________________________________________________
SECTION D: Language and Comprehension [0 marks — integrated above]
Note: Questions 1–17 cover all 50 marks. Sections A, B, and C are weighted as follows: Section A = 35 marks, Section B = 8 marks, Section C = 7 marks.
End of Paper
Mark Summary
| Section | Questions | Marks |
|---|---|---|
| A: Short-Answer | 1–15 | 35 |
| B: Summary | 16 | 8 |
| C: Application | 17(a)–(b) | 7 |
| Total | 50 |
Answers
TuitionGoWhere Practice Paper — General Paper H1 A-Level
Answer Key — Version 5 of 5
Paper: Practice Paper — Comprehension (Paper 2 Style) Total Marks: 50
SECTION A: Short-Answer Questions [35 marks]
Question 1. According to the passage, what two areas of healthcare has AI significantly impacted? [2 marks]
Answer: (i) Diagnostic imaging / radiology [1 mark] (ii) Drug discovery / pharmaceutical development [1 mark]
Teaching Notes: This is a literal comprehension question requiring direct retrieval from the opening paragraph. Students must identify the two specific areas named. "Radiology" and "diagnostic imaging" are interchangeable; similarly, "drug discovery" and "pharmaceutical development" are acceptable. Students should avoid vague answers like "medicine" or "healthcare" — the question asks for specific areas.
Question 2. The author states that "this optimism is tempered by legitimate concerns" (line 4). What are the three concerns mentioned? [3 marks]
Answer: (i) Data privacy [1 mark] (ii) Algorithmic bias [1 mark] (iii) The erosion of the doctor-patient relationship [1 mark]
Teaching Notes: This is a literal comprehension question. The three concerns are listed in the first paragraph. Students should quote or paraphrase precisely. Common mistake: students may only identify two of the three concerns, losing a mark. Students should also avoid confusing "data privacy" with "data security" — while related, the passage specifically frames the concern around privacy.
Question 3. Explain the author's use of the word "democratise" (line 3) in the context of the passage. [2 marks]
Answer: The author uses "democratise" to mean that AI will make high-quality medical care accessible to everyone [1 mark], particularly those in underserved or remote areas who previously lacked access to specialist doctors [1 mark].
Teaching Notes: This is a vocabulary-in-context question. Students must explain the word as used in the passage, not just give a dictionary definition. The key idea is about broadening access and removing barriers. Common mistake: students may simply define "democratise" as "making democratic" without connecting it to healthcare access. Award 1 mark for identifying the idea of wider access, and the second mark for linking it to underserved populations.
Question 4. What evidence does the author provide to support the claim that AI can match or exceed human radiologists in certain tasks? [2 marks]
Answer: The author cites a 2023 study published in The Lancet Digital Health [1 mark] which found that an AI system correctly identified breast cancer in mammograms 94.5% of the time, compared to 88.0% for human specialists [1 mark].
Teaching Notes: This tests the student's ability to locate and retrieve specific evidence. The reference to the journal name and the specific percentages are both needed for full marks. Common mistake: students may vaguely reference "a study" without providing the specific figures, which would only earn 1 mark.
Question 5. The author argues that the view that AI will replace radiologists is "overly simplistic" (line 10). What reasons does the author give for this? Answer in your own words as far as possible. [3 marks]
Answer: The author argues that radiologists do much more than just read scans — they consult with patients, coordinate with other doctors [1 mark], and make nuanced clinical judgments that require empathy and contextual understanding [1 mark]. AI, despite its computational power, cannot replicate these human aspects of medical care [1 mark].
Teaching Notes: This is an inference/paraphrase question. Students must rephrase the author's argument in their own words. Direct lifting from the passage should be penalised — award a maximum of 2 marks if the answer is substantially lifted. Key ideas to capture: (1) radiologists' roles extend beyond scan-reading, (2) empathy and human judgment are involved, (3) AI cannot replicate these human dimensions.
Question 6. Explain the author's use of the phrase "notoriously slow and expensive" (line 14) in the context of traditional drug development. [2 marks]
Answer: The author uses this phrase to emphasise that traditional drug development is widely recognised as taking a very long time [1 mark] and requiring enormous financial investment — over a decade and more than $2.6 billion for a single drug [1 mark].
Teaching Notes: "Notoriously" implies that this slowness and expense are well-known and commonly acknowledged. Students should capture both the time and cost dimensions. Award 1 mark for explaining the meaning of the phrase generally, and 1 mark for referencing the specific figures from the passage.
Question 7. How did AI contribute to the response during the COVID-19 pandemic, according to the passage? [2 marks]
Answer: AI-assisted research helped identify potential therapeutic compounds in weeks rather than years [1 mark], which dramatically accelerated vaccine development timelines [1 mark].
Teaching Notes: A straightforward retrieval question. Students need to capture both the speed of identification and the impact on vaccine development. Common mistake: students may only mention one of these two points.
Question 8. What incident in 2022 does the author refer to, and what concern does it highlight? [2 marks]
Answer: The author refers to a data breach at a major US hospital chain that exposed the medical records of over 1.5 million patients [1 mark]. This highlights the vulnerability of digitised health records and the risks associated with storing large volumes of patient data [1 mark].
Teaching Notes: Students must identify both the specific incident (the data breach) and the broader concern it illustrates (vulnerability of digital health data). Common mistake: students may describe the incident but fail to explain what concern it raises.
Question 9. Explain the author's use of the word "contentious" (line 21) as used in the passage. [1 mark]
Answer: "Contentious" means causing disagreement or controversy [1 mark]. The author uses it to indicate that data privacy is the most debated and divisive issue surrounding AI in healthcare.
Teaching Notes: A straightforward vocabulary question. Students must explain the word in context. Acceptable synonyms include "controversial," "disputed," or "debated."
Question 10. According to the passage, why did the commercial healthcare algorithm underestimate the health needs of Black patients? Answer in your own words. [3 marks]
Answer: The algorithm used healthcare spending as an indicator of how ill a patient was [1 mark]. However, Black patients historically had less access to healthcare and therefore spent less on medical treatment [1 mark]. As a result, the algorithm incorrectly concluded that Black patients were healthier than they actually were [1 mark].
Teaching Notes: This is an inference question requiring students to explain the causal chain in their own words. The three key points are: (1) the proxy used (spending), (2) the reason the proxy was flawed (historical under-access), and (3) the erroneous conclusion. Direct lifting should be capped at 2 marks. Common mistake: students may explain the bias but fail to articulate the specific mechanism (spending as proxy).
Question 11. What two measures does the author suggest are needed to correct algorithmic bias? [2 marks]
Answer: (i) Better / more representative data [1 mark] (ii) Diverse teams of developers who can identify blind spots in training datasets [1 mark]
Teaching Notes: A retrieval question from the fifth paragraph. Students may paraphrase. Acceptable alternatives include "improved datasets" for (i) and "diverse developers" or "varied perspectives in AI development teams" for (ii).
Question 12. How has AI been used to benefit patients in rural India, according to the passage? [2 marks]
Answer: AI-powered diagnostic tools enabled community health workers with minimal medical training to screen for diabetic retinopathy [1 mark], with accuracy comparable to that of specialist ophthalmologists [1 mark].
Teaching Notes: Students must identify both the tool (AI-powered diagnostics) and the condition screened (diabetic retinopathy), as well as the comparable accuracy. Common mistake: students may vaguely say "AI helped doctors in rural India" without specifying the details.
Question 13. The author states that "the potential benefits of AI in healthcare are too significant to ignore" (line 33). What does the author mean by this, and how does the author justify this claim? [3 marks]
Answer: The author means that the advantages of AI in healthcare are so substantial that it would be unwise to dismiss or reject the technology [1 mark]. The author justifies this by citing the example of rural India, where AI enabled minimally trained health workers to screen for diabetic retinopathy with specialist-level accuracy [1 mark], and sub-Saharan Africa, where AI-driven mobile apps help triage patients in remote clinics [1 mark].
Teaching Notes: This requires students to interpret the author's rhetorical move — acknowledging challenges while arguing that benefits outweigh them. Students must explain the meaning of the statement AND provide the supporting examples. Award 1 mark for interpretation, 1 mark for each example. Common mistake: students may explain the meaning but fail to cite the specific examples.
Question 14. In your own words, explain what the author means by "the irreplaceable human elements of medicine" (line 38). [2 marks]
Answer: The author refers to qualities unique to human doctors that AI cannot replicate [1 mark], specifically compassion, ethical judgment, and the ability to deal with uncertainty and complex situations [1 mark].
Teaching Notes: Students must paraphrase and identify at least two of the three qualities listed in the passage. Award 1 mark for the general idea (human qualities AI cannot replace) and 1 mark for listing specific qualities. Direct lifting of "compassion, ethical judgment, and the ability to navigate uncertainty" should earn only 1 mark.
Question 15. What is the author's overall stance on the integration of AI into healthcare? Support your answer with evidence from the passage. [4 marks]
Answer: The author adopts a balanced but cautiously supportive stance [1 mark]. While acknowledging significant concerns — data privacy, algorithmic bias, and the limitations of AI in replicating human care [1 mark] — the author argues that AI's benefits are too important to ignore, citing examples from rural India and sub-Saharan Africa [1 mark]. The author concludes that the question is not whether to integrate AI, but how to do so responsibly, calling for collaboration between policymakers, technologists, and medical professionals to ensure equitable outcomes [1 mark].
Teaching Notes: This is a higher-order evaluation question. Students must identify the nuanced stance (neither wholly positive nor negative) and support it with evidence from across the passage. Mark breakdown: 1 mark for identifying the balanced/cautious stance, 1 mark for acknowledging the concerns raised, 1 mark for citing the benefits/examples, and 1 mark for referencing the author's concluding argument. Common mistake: students may characterise the author as simply "for" or "against" AI, missing the nuance. Award a maximum of 2 marks for a one-sided interpretation.
SECTION B: Summary [8 marks]
Question 16. Summarise the concerns and challenges associated with the use of AI in healthcare (lines 1–32). [8 marks]
Answer (Model Summary):
The use of AI in healthcare raises several concerns. AI systems require vast amounts of patient data, creating risks around data privacy and security, as demonstrated by a major US hospital data breach in 2022. Algorithmic bias is another significant challenge: because AI learns from historical data that may reflect existing disparities, it can perpetuate or worsen inequalities, as seen in an algorithm that underestimated Black patients' health needs by using healthcare spending as a proxy for illness. Additionally, critics worry that over-reliance on AI may overlook biological complexities that human researchers would identify, since AI-generated hypotheses still require rigorous clinical trials. There are also concerns that AI could erode the doctor-patient relationship and replace the empathy and contextual judgment that human doctors provide.
[Approximately 118 words]
Marking Scheme:
| Marks | Descriptor |
|---|---|
| 7–8 | Accurate, concise summary covering all key concerns in own words; well within word limit; coherent and fluent. |
| 5–6 | Covers most key concerns; largely in own words; may include minor irrelevancies or slight lifting; within word limit. |
| 3–4 | Covers some concerns but omits significant points; substantial lifting from passage; may exceed word limit. |
| 1–2 | Limited coverage; mostly lifted from passage; poorly organised; may be incomplete. |
| 0 | No relevant content or entirely copied from passage. |
Content Points (award 1 mark each, up to 8 marks):
- AI requires enormous volumes of patient data / data privacy concerns
- Data security vulnerability / risk of data breaches (2022 US hospital incident)
- Algorithmic bias — AI learns from historically biased data
- Example: algorithm underestimated Black patients' needs using spending as proxy
- AI may overlook biological complexities that humans would catch
- AI-generated hypotheses still need rigorous clinical trials
- Erosion of the doctor-patient relationship
- AI cannot replicate empathy, compassion, and human clinical judgment
Teaching Notes: For the summary, students must use material only from lines 1–32. They should use their own words as far as possible. Direct lifting of phrases should be penalised in the language assessment. The summary should be in continuous prose, not bullet points. Common mistakes include: (1) including material from beyond line 32 (e.g., the India/Africa examples), (2) writing in note form, (3) exceeding the 120-word limit, and (4) lifting entire phrases without paraphrasing.
SECTION C: Application Question [7 marks]
Question 17(a). Explain two concerns that opponents of this proposal might raise, drawing on ideas from the passage. [4 marks]
Answer:
Concern 1: Algorithmic bias and inequitable outcomes. [1 mark] Opponents might argue that AI diagnostic systems trained on historical data could perpetuate existing healthcare disparities. As the passage illustrates with the US healthcare algorithm that underestimated Black patients' needs, AI systems can embed and amplify biases if the training data is not representative. [1 mark]
Concern 2: Erosion of the doctor-patient relationship and loss of human judgment. [1 mark] Opponents could argue that AI cannot replicate the empathy, ethical reasoning, and contextual understanding that human doctors bring to patient care. The passage emphasises that radiologists, for example, do far more than read scans — they consult, coordinate, and make nuanced judgments that AI cannot replicate. [1 mark]
Marking Scheme:
- 1 mark for identifying each concern (2 marks total)
- 1 mark for explaining each concern with reference to the passage (2 marks total)
Acceptable alternative concerns:
- Data privacy and security risks (referencing the 2022 breach)
- Over-reliance on technology leading to oversight of biological complexities
- Job losses among healthcare professionals (implied in the passage's discussion of AI replacing radiologists)
Teaching Notes: Students must draw on ideas from the passage but apply them to the new scenario. Answers that merely restate the passage without connecting to the scenario should receive a maximum of 2 marks. Common mistake: students may raise concerns not supported by the passage (e.g., "AI might malfunction"), which should not be rewarded.
Question 17(b). Which group of people do you think would benefit most from AI-powered diagnostic systems in public hospitals? Justify your answer with reference to ideas from the passage. [3 marks]
Answer:
Patients in rural or underserved areas would benefit most from AI-powered diagnostic systems. [1 mark] The passage demonstrates that AI can enable minimally trained health workers to achieve specialist-level accuracy in screening for conditions such as diabetic retinopathy in rural India. [1 mark] In public hospitals serving large, diverse populations — particularly in resource-poor settings — AI could bridge the gap caused by shortages of specialist doctors, ensuring that patients who would otherwise lack access to timely diagnoses receive the care they need. [1 mark]
Marking Scheme:
- 1 mark for identifying a specific group
- 1 mark for justification linked to passage evidence
- 1 mark for extended reasoning showing application to the scenario
Acceptable alternative answers:
- Patients with rare or complex conditions (AI can process vast datasets to identify patterns)
- Elderly or immobile patients (AI-driven triage could prioritise their care)
- Underserved ethnic/racial groups — though students must be careful to note that without addressing algorithmic bias, these groups could also be harmed
Teaching Notes: This is an application question requiring students to transfer ideas from the passage to a new context. There is no single "correct" group, but the justification must be grounded in passage evidence and logically reasoned. Common mistake: students may identify a group but fail to justify with reference to the passage, or may provide a generic answer without specific reasoning.
Mark Summary
| Section | Questions | Marks |
|---|---|---|
| A: Short-Answer | 1–15 | 35 |
| B: Summary | 16 | 8 |
| C: Application | 17(a)–(b) | 7 |
| Total | 50 |
End of Answer Key