The IELTS Reading section can be particularly challenging due to the variety of topics it covers. One such topic that has gained popularity due to its relevance is the social implications of AI in healthcare decision-making. Not only is this topic timely and frequently discussed, but it also aligns with the increasing inclusion of modern technology and its societal impacts in the IELTS Reading texts. Understanding the depth of this subject and familiarizing oneself with related questions can improve your chances of scoring well. Let’s dig into a full-length practice reading exercise on this topic.
Practice Reading Passage and Questions
Reading Passage: The Social Implications of AI in Healthcare Decision-Making
Artificial Intelligence (AI) has been making significant inroads in various sectors, most notably in healthcare. From diagnosing diseases to personalizing treatment plans, AI’s role in healthcare decision-making has increased manifold. However, with its rise come important social implications that warrant careful consideration.
One of the most significant concerns centers around the ethical dimensions of AI in healthcare. The deployment of AI algorithms in making healthcare decisions necessitates high levels of trust and transparency. Algorithms should be meticulously developed and continuously reviewed to minimize biases that could exacerbate social inequalities. For instance, an AI system trained predominantly on data from a specific ethnic group could yield skewed results when used on a more diverse population, thus exacerbating health disparities.
Moreover, the integration of AI in healthcare raises questions of accountability. When AI systems are involved in diagnosing conditions or recommending treatments, determining liability in cases of errors becomes complex. Traditionally, such accountability would fall on medical professionals. However, with AI, the lines of accountability can become blurred. This necessitates the creation of clear frameworks that delineate roles and responsibilities.
AI’s role in healthcare also impacts patient-doctor relationships. The trust patients place in their healthcare providers could be under threat if they believe decisions are being made by impersonal algorithms rather than human professionals. While AI can assist in delivering accurate and efficient diagnoses, it is essential that the human touch remains integral. This dual reliance can ensure that AI acts as an augmentative tool rather than a replacement.
Additionally, there are concerns regarding data privacy and security. The vast amounts of data required to train AI systems include sensitive patient information. The potential misuse or hacking of this data could have severe ramifications for patient confidentiality. Therefore, robust cybersecurity measures must be implemented to safeguard against such threats.
In conclusion, while AI has the potential to revolutionize healthcare, its social implications cannot be ignored. Clear guidelines, ongoing monitoring, and a balance between AI capabilities and human oversight are crucial in ensuring that AI serves as a beneficial adjunct to healthcare delivery.
Questions
Multiple Choice
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What is one of the primary ethical concerns mentioned regarding AI in healthcare?
- A) Cost of implementation
- B) Lack of available data
- C) Potential biases in algorithms
- D) Speed of diagnostics
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How does AI impact patient-doctor relationships according to the passage?
- A) It completely takes over patient care.
- B) It undermines patient trust.
- C) It eliminates the need for doctors.
- D) It enhances personal interaction.
Identifying Information (True/False/Not Given)
- AI in healthcare has completely eliminated human errors in diagnosis.
- Clear guidelines are essential to delineate roles and responsibilities in AI healthcare decision-making.
Matching Headings
- Match the following headings to the correct paragraphs:
- i) AI and Ethical Considerations
- ii) The Importance of Human Oversight
- iii) Accountability in AI Decisions
- iv) Data Privacy Concerns
Summary Completion
- Complete the summary using words from the text:
The integration of AI in healthcare has brought about several concerns, especially regarding the of algorithms and the of patient data. It is necessary for measures to be in place to ensure the ___ use of AI in healthcare.
Short-Answer Questions
- What could happen if AI systems are trained on non-diverse data?
- Who traditionally holds accountability in healthcare decisions?
Answer Key and Explanations
- C) Potential biases in algorithms – The passage highlights the risk of AI systems exacerbating social inequalities due to biases in algorithmic development.
- B) It undermines patient trust – The text mentions that AI might threaten patient trust if perceived as a replacement for healthcare professionals.
- False – The passage does not claim that AI has eliminated human errors completely.
- True – It clearly states the need for clear frameworks and guidelines.
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- i) AI and Ethical Considerations – Paragraph 2
- ii) The Importance of Human Oversight – Paragraph 4
- iii) Accountability in AI Decisions – Paragraph 3
- iv) Data Privacy Concerns – Paragraph 5
- ethical, transparency, security, robust, beneficial
- AI systems trained on non-diverse data could yield skewed results, exacerbating health disparities.
- Traditionally, medical professionals hold accountability in healthcare decisions.
Common Mistakes and Tips
Here are some common mistakes encountered in such exercises:
- Misidentifying information as True/False/Not Given based on assumptions rather than the text.
- Misinterpreting the specific ethical concerns surrounding AI.
- Overlooking the need for clear accountability frameworks.
Vocabulary and Key Terms
- Bias (noun): /baɪəs/ – A tendency to favor or disfavor certain results or groups.
- Accountability (noun): /əˌkaʊntəˈbɪlɪti/ – The state of being responsible for something.
- Augmentative (adjective): /ɔːɡˈmɛntətɪv/ – Serving to enhance or increase.
- Ramifications (noun): /ˌræmɪfɪˈkeɪʃənz/ – Consequences of an action or event.
Key Grammar Structures
- Conditional sentences: “If AI systems are trained predominantly on data from a specific ethnic group…”
- Passive voice: “Algorithms should be meticulously developed and continuously reviewed…”
Recommendations for High IELTS Reading Scores
- Practice Regularly: Engage with reading passages on varied topics regularly.
- Expand Vocabulary: Focus on academic and topic-specific vocabulary.
- Understand Question Types: Familiarize yourself with different question formats and practice them.
- Time Management: Develop a strategy to manage your time efficiently during the exam.
- Review Mistakes: Learn from your mistakes and understand why you got a question wrong.
AI and Healthcare
Embrace these tips and keep practicing to attain a high score in your IELTS Reading section. Good luck!
