Understanding “What are the social implications of increasing reliance on AI in decision-making?” – IELTS Reading Practice

The IELTS Reading test is crucial for candidates aiming for a high score in the IELTS examination. It evaluates your ability to understand and interpret written English, covering a range of topics from social sciences …

AI Decision-Making

The IELTS Reading test is crucial for candidates aiming for a high score in the IELTS examination. It evaluates your ability to understand and interpret written English, covering a range of topics from social sciences to technology. In this article, we will delve into understanding the social implications of increasing reliance on AI in decision-making—a topic that has garnered significant interest due to its relevance and potential impact.

Historically, topics related to technology, especially artificial intelligence (AI), have frequently appeared in the IELTS Reading section. The pervasiveness and evolving nature of AI suggest that it may continue to be a relevant subject in future exams. This article aims to provide a comprehensive IELTS reading sample, complete with questions, answers, vocabulary, and grammar tips, centering around the theme of AI’s implications in societal decision-making.

IELTS Reading Sample

Passage (Medium Text)

What Are The Social Implications Of Increasing Reliance On AI In Decision-making?

Artificial Intelligence (AI) is transforming the way decisions are made across various sectors, including healthcare, finance, and public administration. As AI systems continue to evolve and integrate into these fields, society faces both opportunities and challenges.

One of the primary benefits of AI in decision-making is its ability to process and analyze large datasets quickly and accurately. For instance, in healthcare, AI algorithms can diagnose diseases based on patient data with higher precision than some human doctors, potentially leading to better patient outcomes. AI can also help in predictive maintenance in industries by preemptively identifying machinery faults, thus reducing operational disruptions.

However, the increasing reliance on AI also raises significant social concerns. One of the major issues is the potential for bias. AI systems are only as good as the data they are trained on, and if this data reflects existing social biases, it can perpetuate or even exacerbate these biases. For example, AI used in hiring processes might favor candidates from certain demographics if historical hiring data is biased.

Privacy is another concern. AI systems often require vast amounts of data, raising questions about how this data is collected, stored, and used. There is a risk that personal information could be misused or exposed to cyber threats, compromising individuals’ privacy.

Moreover, the displacement of jobs due to automation remains a contentious issue. While AI can improve efficiency and reduce the need for certain manual tasks, it may also lead to unemployment for workers whose jobs are automated. This necessitates a societal shift towards reskilling and upskilling the workforce to adapt to new job roles created by AI technologies.

Lastly, ethical considerations regarding AI decision-making cannot be overlooked. Who is held accountable when an AI system makes a wrong decision? Establishing a framework for accountability in AI-related decisions is essential to ensure that these systems are used responsibly.

In conclusion, while AI offers significant advantages in decision-making processes, it is imperative to address the associated social implications proactively. Balancing the benefits of AI with ethical, unbiased, and privacy-conscious practices will shape its role in societal development.

AI Decision-MakingAI Decision-Making

Questions

Multiple Choice

  1. According to the passage, what is one way AI benefits the healthcare sector?
    A. By reducing the need for doctors
    B. By diagnosing diseases with high precision
    C. By reducing the healthcare costs
    D. By eliminating data storage needs

  2. What is a significant concern regarding AI in decision-making mentioned in the passage?
    A. The speed of decision-making
    B. The cost of implementing AI
    C. The potential for bias in AI systems
    D. The aesthetic design of AI systems

True/False/Not Given

  1. AI in predictive maintenance can help preemptively identify machinery faults.

  2. The passage states that AI has eliminated unemployment in several sectors.

  3. Ethical considerations are not relevant to AI decision-making, according to the passage.

Short-Answer Questions

  1. What is one key reason for privacy concerns associated with AI?

  2. Why is it important to establish a framework for accountability in AI-related decisions?

Answer Key

Multiple Choice

  1. B. By diagnosing diseases with high precision
  2. C. The potential for bias in AI systems

True/False/Not Given

  1. True
  2. False
  3. False

Short-Answer Questions

  1. AI systems often require vast amounts of data, raising questions about data collection, storage, and use, which can lead to privacy concerns.
  2. It is important to ensure that AI systems are used responsibly and that there is clarity on who is accountable when an AI system makes a wrong decision.

Lessons Learned

Common Mistakes:

  1. Misinterpreting information: Ensure you understand the question fully before selecting an answer.
  2. Neglecting context: Pay attention to the contextual clues within the passage.
  3. Overlooking details: Small details can often change the meaning significantly; read carefully.

Vocabulary

  • Algorithm [noun] /ˈælɡərɪðəm/: A process or set of rules followed in calculations or problem-solving operations.
  • Bias [noun] /ˈbaɪəs/: Inclination or prejudice for or against one person or group.
  • Privacy [noun] /ˈpraɪvəsɪ/: The state of being free from public attention.
  • Reskilling [noun] /riːˈskɪlɪŋ/: Learning new skills so that you can do a different job.
  • Accountability [noun] /əˌkaʊntəˈbɪlɪti/: The fact or condition of being responsible.

Grammar

  • Passive Voice Construction: Used to emphasize the action rather than who/what performed the action.
    • Structure: [Subject] + [to be] + [Past Participle] + [by agent (optional)].
    • Example: “AI systems are trained on large datasets.”

Conclusion

Preparing for the IELTS Reading section requires diligent practice and familiarity with a range of topics. AI in decision-making is an example of a high-relevance topic that not only tests your reading skills but also your understanding of contemporary issues. Focus on understanding the context, practice with similar topics, and use this guide to help improve your reading and comprehension skills. Good luck!

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