From Real Exams Exam Paper

A Level H1 General Paper Practice Paper 1

Free Exam-Derived Owl Alpha A Level H1 General Paper Practice Paper 1 practice paper with questions and answers for Singapore students. This page is rendered as a direct URL so the questions and answers can be discovered without pressing in-page buttons.

These static practice materials are generated from the site's syllabus and paper-generation workflow, with source and model context shown so students and parents can evaluate the material before use.

A Level H1 General Paper From Real Exams Generated by Owl Alpha Updated 2026-06-07

Back to Subject Browse Free Exam Papers

Questions

TuitionGoWhere Practice Paper — General Paper H1 A-Level

TuitionGoWhere Secondary School (AI)

Subject: General Paper Level: A-Level H1 Paper: Practice Paper 2 — Comprehension Version: 1 of 5 Duration: 1 hour 30 minutes Total Marks: 50

Name: ___________________________ Class: ___________________________ Date: ___________________________

Instructions

This paper consists of one passage and 20 questions.
Answer all questions.
Write your answers in the spaces provided.
The total marks for this paper is 50.
The time allowed is 1 hour 30 minutes.
Credit will be given for the use of your own words where required.

Read the passage carefully and answer all questions.

The Rise of Artificial Intelligence in Modern Healthcare

The integration of artificial intelligence (AI) into healthcare has been one of the most transformative developments of the twenty-first century. From diagnostic imaging to drug discovery, AI systems are increasingly being deployed in clinical settings, promising to revolutionise how diseases are detected, treated, and managed. Yet, as with all technological revolutions, the rapid adoption of AI in medicine raises profound questions about ethics, accountability, and the future role of human practitioners.

Proponents of AI in healthcare argue that its potential benefits are immense. Machine learning algorithms, trained on vast datasets of medical images, can now detect certain cancers with accuracy that rivals — and in some studies surpasses — that of experienced radiologists. A landmark study published in Nature in 2020 demonstrated that an AI system outperformed six radiologists in reading mammograms, reducing both false positives and false negatives. Advocates point to such findings as evidence that AI could significantly reduce diagnostic errors, which the World Health Organization estimates contribute to approximately 10% of patient deaths globally.

Beyond diagnostics, AI is accelerating the pace of drug development. Traditional pharmaceutical research can take over a decade and cost billions of dollars to bring a single drug to market. AI-driven platforms can screen millions of molecular compounds in silico, identifying promising candidates in a fraction of the time. During the COVID-19 pandemic, AI tools were instrumental in analysing the virus's protein structure, contributing to the unprecedented speed at which vaccines were developed. "We are witnessing a paradigm shift," says Dr. Elena Vasquez, a bioethicist at the National University of Singapore. "The question is no longer whether AI will transform healthcare, but whether we are prepared for the consequences."

However, critics urge caution. One of the most pressing concerns is algorithmic bias. AI systems are only as unbiased as the data on which they are trained. If training datasets underrepresent certain demographic groups — as has been documented in dermatology AI tools trained predominantly on lighter skin tones — the resulting algorithms may perform poorly for those populations. A 2019 study in Science revealed that a widely used commercial algorithm exhibited significant racial bias in predicting healthcare needs, systematically underestimating the severity of illness among Black patients. Such biases, if left unaddressed, risk deepening existing health disparities rather than alleviating them.

The issue of accountability is equally thorny. When an AI system makes an incorrect diagnosis that leads to patient harm, who bears responsibility? The hospital that deployed the system? The developers who designed the algorithm? The clinicians who relied on its output? Current legal frameworks are ill-equipped to handle such questions. Unlike a human doctor, an AI cannot be held liable in any meaningful sense. This creates what scholars have termed an "accountability gap" — a void in which errors occur but no party can be adequately held to account.

Furthermore, there are concerns about the erosion of the doctor-patient relationship. Medicine has long been understood as both a science and an art, requiring not only technical competence but also empathy, intuition, and the ability to communicate with patients as whole persons. Critics worry that an over-reliance on AI could reduce medicine to a purely data-driven exercise, stripping away the human elements that many patients value most. A 2023 survey by the British Medical Association found that 68% of patients expressed concern about AI being used in their care, with many citing a preference for human judgement in matters of life and death.

Defenders of AI counter that these fears are overblown. They argue that AI is best understood not as a replacement for doctors, but as a tool that augments human capabilities. By handling routine diagnostic tasks, AI could free up clinicians to spend more time on patient interaction, complex decision-making, and the nuanced aspects of care that machines cannot replicate. "The goal is not to replace the physician," argues Dr. James Tan, a cardiologist and AI researcher at Mount Elizabeth Hospital. "The goal is to give the physician better tools so they can focus on what matters most — the patient."

The economic implications are also significant. AI has the potential to reduce healthcare costs by improving efficiency and reducing unnecessary procedures. In countries with ageing populations and strained healthcare budgets, such savings could be transformative. Singapore, for instance, has invested heavily in AI healthcare initiatives as part of its Smart Nation strategy, recognising that technology will be essential to sustaining quality care as the population ages. Yet critics note that the upfront costs of AI implementation — including infrastructure, training, and ongoing maintenance — are substantial, and that the benefits may accrue disproportionately to wealthier nations and institutions, widening the global health divide.

Ultimately, the future of AI in healthcare will depend on how societies navigate the tension between innovation and caution. Robust regulatory frameworks, transparent algorithms, and inclusive training data are essential prerequisites for equitable AI deployment. Equally important is ongoing dialogue between technologists, clinicians, ethicists, and patients to ensure that AI serves human values rather than undermining them. As Dr. Vasquez observes, "Technology is never neutral. It reflects the priorities and biases of those who create it. Our task is to ensure that AI in healthcare reflects our highest aspirations for justice and compassion."

Section A: Comprehension & Analysis (Questions 1–15)

Answer all questions. Write your answers in the spaces provided.

Question 1 (2 marks)

In paragraph 1, the author states that AI in healthcare "raises profound questions about ethics, accountability, and the future role of human practitioners."

Explain what the author means by the phrase "the future role of human practitioners" in this context. Use your own words as far as possible.

Question 2 (2 marks)

In paragraph 2, the author writes that AI "can now detect certain cancers with accuracy that rivals — and in some studies surpasses — that of experienced radiologists."

Explain the author's use of the word "surpasses" in this context. What effect does this word choice have on the reader's perception of AI?

Question 3 (3 marks)

In paragraph 2, the author cites a study published in Nature in 2020.

(a) What specific finding from this study does the author highlight? (1 mark)

(b) Why does the author include this reference to the Nature study? Explain its purpose in the argument. (2 marks)

Question 4 (2 marks)

In paragraph 3, the author states: "We are witnessing a paradigm shift."

Explain what Dr. Vasquez means by "paradigm shift" in this context. Use your own words as far as possible.

Question 5 (2 marks)

In paragraph 4, the author uses the phrase "algorithmic bias."

Explain what is meant by "algorithmic bias" and provide one example from the passage that illustrates this concept.

Question 6 (3 marks)

In paragraph 4, the author describes how a 2019 study in Science revealed racial bias in a commercial algorithm.

(a) What specific bias was identified in the study? (1 mark)

(b) Explain the potential consequence of this bias as outlined in the passage. (2 marks)

Question 7 (2 marks)

In paragraph 5, the author refers to an "accountability gap."

Explain what the author means by this term. Use your own words as far as possible.

Question 8 (2 marks)

In paragraph 6, the author states that medicine has long been understood as "both a science and an art."

What does the author mean by describing medicine as "an art" in this context?

Question 9 (3 marks)

In paragraph 6, the author cites a 2023 survey by the British Medical Association.

(a) What were the key findings of this survey? (1 mark)

(b) How does the author use this survey to support the argument about AI in healthcare? (2 marks)

Question 10 (2 marks)

In paragraph 7, Dr. James Tan argues that AI is "best understood not as a replacement for doctors, but as a tool that augments human capabilities."

Explain what Dr. Tan means by "augments human capabilities." Use your own words as far as possible.

Question 11 (2 marks)

In paragraph 7, the author states that AI could allow clinicians to "focus on what matters most — the patient."

What does this suggest about the author's view of the relationship between technology and human care?

Question 12 (3 marks)

In paragraph 8, the author discusses the economic implications of AI in healthcare.

Identify two economic benefits and one economic concern mentioned in this paragraph.

Benefit 1: _______________________________________________________________

Benefit 2: _______________________________________________________________

Concern: ________________________________________________________________

Question 13 (2 marks)

In paragraph 8, the author states that Singapore has invested heavily in AI healthcare initiatives as part of its "Smart Nation strategy."

Why does the author mention Singapore specifically? What purpose does this example serve?

Question 14 (3 marks)

In paragraph 9, Dr. Vasquez states: "Technology is never neutral. It reflects the priorities and biases of those who create it."

Explain the significance of this statement in the context of the passage as a whole. Use your own words as far as possible.

Question 15 (2 marks)

Throughout the passage, the author presents both the benefits and concerns of AI in healthcare.

Does the author lean more towards a positive or negative view of AI in healthcare? Support your answer with one piece of evidence from the passage.

Section B: Summary (Question 16)

Question 16 (8 marks)

Summise the concerns raised in the passage about the use of AI in healthcare.

Use your own words as far as possible. Write your summary in no more than 120 words.

You should use continuous writing (not note form). Marks will be awarded for use of your own words, relevant material, and a well-organised response.

Section C: Application (Questions 17–20)

Read the following scenario and answer Questions 17–20.

Scenario

The Ministry of Health in your country is considering a proposal to implement an AI-powered triage system in all public hospitals. The system would use machine learning algorithms to assess patients' symptoms upon arrival at the emergency department and assign them a priority level for treatment. Proponents argue that this would reduce waiting times and improve efficiency. Opponents argue that the system could misclassify patients from underrepresented communities and reduce the role of experienced nurses in initial patient assessment.

Question 17 (2 marks)

Using ideas from the passage, explain one potential benefit of implementing the AI triage system.

Question 18 (2 marks)

Using ideas from the passage, explain one potential risk of implementing the AI triage system.

Question 19 (2 marks)

The passage discusses the "accountability gap" in relation to AI errors. Explain how this concept might apply to the AI triage system described in the scenario.

Question 20 (1 mark)

Based on the passage, suggest one measure the Ministry of Health could take to address the concerns raised by opponents of the AI triage system.

End of Paper

Section A: Questions 1–15 — 35 marks Section B: Question 16 — 8 marks Section C: Questions 17–20 — 7 marks Total: 50 marks

Answers

TuitionGoWhere Practice Paper — General Paper H1 A-Level

Answer Key — Practice Paper 2, Version 1 of 5

Section A: Comprehension & Analysis (Questions 1–15)

Question 1 (2 marks)

Answer: The phrase "the future role of human practitioners" refers to how doctors, nurses, and other medical professionals will function in a healthcare landscape increasingly dominated by AI. It questions whether human clinicians will remain central to patient care or become secondary to automated systems, and how their responsibilities, skills, and professional identity may change as AI takes over tasks traditionally performed by humans.

Marking Notes:

1 mark for identifying that it concerns how doctors/medical professionals will operate alongside AI.
1 mark for explaining the uncertainty about whether their role will diminish, change, or remain essential.
Students must use their own words. Direct lifting of "future role of human practitioners" without explanation = 0 marks.

Question 2 (2 marks)

Answer: The word "surpasses" means to exceed or do better than. In this context, it means that AI systems have, in some cases, demonstrated greater accuracy in detecting cancers than experienced radiologists. The effect of this word choice is striking and somewhat provocative — it challenges the assumption that human expertise is superior and positions AI as a potentially better alternative, thereby strengthening the pro-AI argument and capturing the reader's attention.

Marking Notes:

1 mark for explaining the meaning of "surpasses" (exceeds/does better than).
1 mark for explaining the rhetorical effect (challenges assumptions, strengthens the pro-AI position, creates impact).
Accept any reasonable explanation of rhetorical effect.

Question 3 (3 marks)

(a) (1 mark)

Answer: The study found that an AI system outperformed six radiologists in reading mammograms, reducing both false positives (incorrectly identifying cancer where none exists) and false negatives (failing to detect cancer that is present).

Marking Notes:

1 mark for identifying that the AI outperformed radiologists in mammogram reading.
Must mention either false positives or false negatives, or the general finding of superior accuracy.

(b) (2 marks)

Answer: The author includes this reference to lend credibility and authority to the argument that AI can be highly effective in healthcare diagnostics. By citing a prestigious peer-reviewed journal (Nature), the author appeals to scientific authority, making the claim more persuasive. It also serves as concrete evidence to support the broader point that AI has immense potential benefits in healthcare.

Marking Notes:

1 mark for identifying the purpose of lending credibility/authority to the argument.
1 mark for explaining how the prestigious source (Nature) strengthens the persuasiveness of the claim.
Accept alternative valid purposes (e.g., providing concrete evidence, supporting the proponents' case).

Question 4 (2 marks)

Answer: By "paradigm shift," Dr. Vasquez means a fundamental and dramatic change in the way healthcare is practised. It suggests that AI is not merely an incremental improvement but a transformative force that is fundamentally altering the methods, assumptions, and structures of medical practice. The shift is so significant that the old model of healthcare is being replaced by a new one in which AI plays a central role.

Marking Notes:

1 mark for explaining "paradigm shift" as a fundamental/dramatic change.
1 mark for contextualising it within healthcare (transforming how medicine is practised).
Must use own words. Simply restating "paraphrase shift" = 0 marks.

Question 5 (2 marks)

Answer: "Algorithmic bias" refers to systematic errors or unfairness in AI systems that arise from the data on which they are trained. If the training data is unrepresentative or reflects existing prejudices, the AI will produce biased outcomes. An example from the passage is dermatology AI tools that were trained predominantly on images of lighter skin tones, causing them to perform poorly when diagnosing conditions in patients with darker skin.

Marking Notes:

1 mark for defining algorithmic bias (systematic errors from unrepresentative/flawed training data).
1 mark for providing the dermatology example or the Science study example about racial bias in healthcare needs prediction.
Either example from the passage is acceptable.

Question 6 (3 marks)

(a) (1 mark)

Answer: The study found that the commercial algorithm exhibited significant racial bias by systematically underestimating the severity of illness among Black patients when predicting their healthcare needs.

Marking Notes:

1 mark for identifying that the algorithm underestimated illness severity in Black patients.

(b) (2 marks)

Answer: The potential consequence is that such biases could worsen existing health disparities rather than reduce them. If AI systems consistently underestimate the healthcare needs of certain racial groups, those patients may receive less attention, fewer resources, or delayed treatment, leading to poorer health outcomes for already disadvantaged populations. This would deepen inequality in healthcare rather than promoting equity.

Marking Notes:

1 mark for identifying that health disparities would worsen/deepen.
1 mark for explaining the mechanism (underrepresented groups receive poorer care/delayed treatment).
Must go beyond simply restating the passage.

Question 7 (2 marks)

Answer: The "accountability gap" refers to the situation where an AI system causes harm (e.g., a misdiagnosis) but no individual or organisation can be clearly held responsible. Unlike a human doctor who can be sued or disciplined, an AI cannot bear legal or moral responsibility. This creates a void in which errors occur but there is no clear party — whether the hospital, the developers, or the clinicians — who can be adequately held accountable.

Marking Notes:

1 mark for identifying that it refers to a lack of clear responsibility when AI causes harm.
1 mark for explaining why this gap exists (AI cannot be held liable; legal frameworks are inadequate).
Must use own words.

Question 8 (2 marks)

Answer: By describing medicine as "an art," the author means that medical practice involves qualities that go beyond technical knowledge and scientific procedure. These include empathy (the ability to understand and share patients' feelings), intuition (the capacity to make judgements based on experience and instinct rather than purely on data), and effective communication with patients as whole persons with emotional and psychological needs. It suggests that the human, relational aspects of medicine are just as important as the scientific ones.

Marking Notes:

1 mark for identifying that it refers to non-technical aspects of medicine.
1 mark for providing specific qualities (empathy, intuition, communication, human connection).
Any two relevant qualities are acceptable for the second mark.

Question 9 (3 marks)

(a) (1 mark)

Answer: The survey found that 68% of patients expressed concern about AI being used in their healthcare, with many stating they preferred human judgement in matters of life and death.

Marking Notes:

1 mark for identifying the 68% figure and the nature of the concern.

(b) (2 marks)

Answer: The author uses this survey to demonstrate that public sentiment is wary of AI in healthcare, which supports the argument that the adoption of AI faces significant resistance from patients themselves. It adds weight to the concerns raised by critics who argue that AI could erode the doctor-patient relationship. By showing that a majority of patients are uncomfortable with AI, the author suggests that successful implementation will require addressing public trust and preferences, not just technical challenges.

Marking Notes:

1 mark for identifying that it shows public resistance/concern about AI.
1 mark for explaining how this supports the critics' argument or the broader point about the need to consider patient perspectives.

Question 10 (2 marks)

Answer: By "augments human capabilities," Dr. Tan means that AI enhances and improves what doctors can do rather than replacing them. It suggests that AI acts as a supplementary tool — handling routine or data-intensive tasks — so that doctors can perform their jobs more effectively and focus on areas where human skills are most needed, such as patient interaction and complex decision-making.

Marking Notes:

1 mark for explaining "augments" as enhances/supplements/improves.
1 mark for contextualising it (AI assists doctors rather than replacing them; handles routine tasks so doctors can focus on complex care).

Question 11 (2 marks)

Answer: This suggests that the author views technology as a means to an end rather than an end in itself. The author believes AI should serve to enhance human care by freeing clinicians from routine tasks, allowing them to devote more attention and time to the interpersonal aspects of medicine. The implication is that technology is most valuable when it supports and strengthens the human elements of healthcare rather than replacing them.

Marking Notes:

1 mark for identifying that technology should serve/enhance human care.
1 mark for explaining the relationship (AI handles routine tasks → doctors focus on patients).

Question 12 (3 marks)

Answer:

Benefit 1: AI can reduce healthcare costs by improving efficiency and reducing unnecessary procedures.

Benefit 2: AI can help countries with ageing populations and strained healthcare budgets sustain quality care by generating significant savings.

Concern: The upfront costs of AI implementation (infrastructure, training, maintenance) are substantial, and the benefits may disproportionately favour wealthier nations and institutions, widening the global health divide.

Marking Notes:

1 mark for each correct response (3 marks total).
Benefits and concern must be from paragraph 8.
Students must use their own words to some extent; direct lifting may receive reduced credit.

Question 13 (2 marks)

Answer: The author mentions Singapore to provide a concrete, real-world example of a country that is actively investing in AI healthcare. This serves to illustrate that the economic and demographic arguments for AI in healthcare are not merely theoretical — they are already being acted upon by forward-thinking nations. It also grounds the discussion in a specific context (an ageing population with a Smart Nation strategy), making the argument more tangible and relevant, particularly for readers in Singapore or similar developed nations.

Marking Notes:

1 mark for identifying that it provides a concrete/real-world example.
1 mark for explaining the purpose (illustrates that AI adoption is already happening; grounds the argument in a specific context).

Question 14 (3 marks)

Answer: Dr. Vasquez's statement is significant because it encapsulates one of the central themes of the passage: that AI is not an objective or neutral tool, but rather a product of human design that carries the values, priorities, and biases of its creators. In the context of the passage, this statement ties together the concerns about algorithmic bias (paragraph 4), the accountability gap (paragraph 5), and the need for inclusive training data and transparent regulation (paragraph 9). It serves as a reminder that the ethical challenges of AI in healthcare are not merely technical problems to be solved, but reflections of deeper societal choices about justice, equity, and compassion. The statement reinforces the passage's overall message that careful governance and inclusive design are essential.

Marking Notes:

1 mark for explaining the meaning of the statement (AI reflects creators' biases/priorities).
1 mark for connecting it to specific concerns in the passage (algorithmic bias, accountability, need for regulation).
1 mark for explaining its broader significance (ties together the passage's themes; reinforces the need for ethical governance).
Award partial credit for incomplete but valid responses.

Question 15 (2 marks)

Answer: The author maintains a balanced view, presenting both the benefits and concerns of AI in healthcare in roughly equal measure. The passage dedicates paragraphs 2–3 to the potential benefits (diagnostic accuracy, drug development) and paragraphs 4–6 to the concerns (bias, accountability, erosion of human care). The concluding paragraph calls for balanced governance rather than outright rejection or uncritical acceptance. Evidence of this balance can be seen in the author's use of phrases like "proponents argue" and "critics urge caution," which give equal voice to both sides.

Alternative acceptable answer: The author leans slightly towards a cautious/measured view, as the final paragraph emphasises the need for "robust regulatory frameworks" and "inclusive training data," suggesting that the author believes the concerns must be addressed before AI can be fully embraced.

Marking Notes:

1 mark for stating a clear position (balanced, positive, or negative).
1 mark for providing relevant evidence from the passage to support the position.
Accept "balanced" or "cautious" as valid positions, provided they are supported with evidence.

Section B: Summary (Question 16)

Question 16 (8 marks)

Model Summary:

The passage raises several concerns about AI in healthcare. Firstly, algorithmic bias is a significant issue: AI systems trained on unrepresentative data may perform poorly for underrepresented groups, as seen in dermatology tools that struggled with darker skin tones and a commercial algorithm that underestimated illness severity in Black patients, potentially worsening health disparities. Secondly, there is an accountability gap — when AI causes harm, it is unclear who should be held responsible, as current legal frameworks cannot adequately address this. Thirdly, critics worry that over-reliance on AI could erode the doctor-patient relationship by reducing medicine to a data-driven exercise and stripping away empathy and human judgement, which many patients value. Finally, the high costs of AI implementation may widen the global health divide, as wealthier nations benefit disproportionately.

(Word count: 138 — accept slightly over if content is strong; penalise if significantly over 120)

Marking Scheme:

Criterion	Marks
Content — relevant concerns identified and paraphrased	5
Use of own words (not lifting)	2
Organisation and coherence (continuous writing, within word limit)	1

Content Points (1 mark each, max 5):

Algorithmic bias from unrepresentative training data.
Specific example: dermatology tools performing poorly on darker skin / racial bias in healthcare needs algorithm.
Consequence: worsening health disparities / deepening inequality.
Accountability gap — no clear party responsible when AI causes harm.
Erosion of doctor-patient relationship / loss of empathy and human judgement.
Patient preference for human judgement (BMA survey).
High implementation costs widening the global health divide.

Award marks for any 5 of the 7 content points above.

Common Mistakes:

Lifting directly from the passage instead of paraphrasing.
Including benefits of AI rather than focusing on concerns.
Exceeding the 120-word limit.
Writing in note form instead of continuous prose.

Section C: Application (Questions 17–20)

Question 17 (2 marks)

Answer: One potential benefit is that the AI triage system could significantly reduce waiting times in emergency departments by quickly and accurately assessing patients' symptoms and assigning priority levels. This aligns with the passage's argument that AI improves efficiency in healthcare by handling routine tasks — in this case, the initial assessment — faster and potentially more accurately than manual processes, allowing hospitals to manage patient flow more effectively.

Marking Notes:

1 mark for identifying a valid benefit (reduced waiting times, improved efficiency, faster assessment).
1 mark for linking it to ideas from the passage (AI improves efficiency, handles routine tasks).

Question 18 (2 marks)

Answer: One potential risk is algorithmic bias. If the AI triage system is trained on data that underrepresents certain communities, it may misclassify patients from those groups — assigning them a lower priority than they actually need. This mirrors the passage's concern about the Science study, where the algorithm underestimated illness severity in Black patients, potentially leading to delayed or inadequate treatment for vulnerable populations.

Marking Notes:

1 mark for identifying a valid risk (algorithmic bias, misclassification, reduced role of nurses).
1 mark for linking it to ideas from the passage (algorithmic bias, underrepresented data, health disparities).

Question 19 (2 marks)

Answer: The "accountability gap" would apply to the AI triage system in the following way: if the system incorrectly classifies a patient's priority level — for example, assigning a low priority to a patient who actually has a life-threatening condition — and that patient suffers harm as a result, it would be unclear who is responsible. The hospital that deployed the system, the developers who created the algorithm, and the clinicians who relied on its output could all deflect blame. Current legal frameworks do not clearly assign liability for AI-driven decisions, creating a dangerous void in which patients may suffer without recourse.

Marking Notes:

1 mark for explaining the accountability gap in the context of the scenario.
1 mark for providing a specific example of how it might apply (misclassification leading to harm with no clear responsible party).

Question 20 (1 mark)

Answer: The Ministry of Health could ensure that the AI system is trained on diverse and inclusive datasets that adequately represent all demographic groups in the population, to minimise algorithmic bias. Alternatively, the Ministry could establish clear regulatory frameworks that define accountability when AI systems make errors, ensuring that patients have recourse if harmed.

Marking Notes:

1 mark for suggesting a valid measure drawn from the passage's recommendations.
Acceptable answers include: inclusive training data, transparent algorithms, regulatory frameworks, ongoing dialogue between stakeholders, maintaining human oversight.

End of Answer Key

Section A: Questions 1–15 — 35 marks Section B: Question 16 — 8 marks Section C: Questions 17–20 — 7 marks Total: 50 marks