IELTS Reading: AI in Legal Services – Đề Thi Mẫu Có Đáp Án Chi Tiết

Trí tuệ nhân tạo (AI) đang tạo nên cuộc cách mạng trong ngành dịch vụ pháp lý toàn cầu, từ việc nghiên cứu án lệ đến dự đoán kết quả kiện tụng. Chủ đề về công nghệ và luật pháp thường xuyên xuất hiện trong bài thi IELTS Reading, đặc biệt ở Passage 2 và 3 với độ khó từ trung bình đến cao. Hiểu rõ về AI In Legal Services không chỉ giúp bạn làm tốt phần thi Reading mà còn mở rộng vốn từ vựng học thuật quan trọng.

Bài viết này cung cấp một đề thi IELTS Reading hoàn chỉnh với ba passages (dễ, trung bình, khó) bao gồm 40 câu hỏi đa dạng giống thi thật. Bạn sẽ học được các dạng câu hỏi phổ biến như True/False/Not Given, Matching Headings, Multiple Choice và Summary Completion. Mỗi câu trả lời đều có giải thích chi tiết kèm vị trí trong bài, cách paraphrase và chiến lược làm bài hiệu quả.

Đề thi này phù hợp cho học viên từ band 5.0 trở lên, giúp bạn làm quen với nội dung học thuật về công nghệ, nâng cao khả năng đọc hiểu và chuẩn bị tốt nhất cho kỳ thi IELTS thực tế.

Hướng Dẫn Làm Bài IELTS Reading

Tổng Quan Về IELTS Reading Test

Bài thi IELTS Reading kéo dài 60 phút với 3 passages và tổng cộng 40 câu hỏi. Điểm số được tính dựa trên số câu trả lời đúng, không bị trừ điểm khi sai. Độ khó tăng dần từ Passage 1 đến Passage 3, với nội dung từ đời thường đến học thuật chuyên sâu.

Phân bổ thời gian khuyến nghị:

• Passage 1: 15-17 phút (13 câu hỏi)
• Passage 2: 18-20 phút (13 câu hỏi)
• Passage 3: 23-25 phút (14 câu hỏi)

Quan trọng nhất là bạn phải hoàn thành việc chuyển đáp án vào Answer Sheet trong 60 phút. Không có thời gian bổ sung như phần Listening.

Các Dạng Câu Hỏi Trong Đề Này

Đề thi mẫu này bao gồm 7 dạng câu hỏi phổ biến nhất trong IELTS Reading:

1. Multiple Choice – Chọn đáp án đúng nhất từ các phương án A, B, C, D
2. True/False/Not Given – Xác định thông tin có đúng với bài đọc không
3. Matching Headings – Nối tiêu đề phù hợp với từng đoạn văn
4. Summary Completion – Điền từ vào chỗ trống trong đoạn tóm tắt
5. Sentence Completion – Hoàn thành câu với thông tin từ bài đọc
6. Matching Features – Nối thông tin với các đối tượng/người được nhắc đến
7. Short-answer Questions – Trả lời câu hỏi ngắn với số từ giới hạn

Mỗi dạng câu hỏi yêu cầu kỹ năng đọc hiểu khác nhau, từ tìm thông tin cụ thể (scanning) đến hiểu ý chính (skimming) và phân tích sâu.

IELTS Reading Practice Test

PASSAGE 1 – The Dawn of AI in Law Firms

Độ khó: Easy (Band 5.0-6.5)

Thời gian đề xuất: 15-17 phút

Law firms around the world are increasingly adopting artificial intelligence to streamline their operations and improve service delivery. What was once a profession reliant solely on human expertise is now embracing technology to handle routine tasks more efficiently. Legal professionals are discovering that AI can be a powerful ally rather than a replacement for their skills.

One of the most significant applications of AI in legal services is document review. Traditionally, junior lawyers spent countless hours reading through thousands of pages of contracts, emails, and other documents to find relevant information for cases. This process was not only time-consuming but also prone to human error due to fatigue. Modern AI systems can now scan and analyze vast quantities of documents in a fraction of the time it would take a human team. These systems use natural language processing to understand context and identify key clauses, dates, names, and legal terms with remarkable accuracy.

Contract analysis represents another area where AI has made substantial inroads. When companies merge or engage in complex transactions, lawyers must review hundreds of contracts to identify potential risks and obligations. AI-powered tools can extract critical information from these contracts, such as termination clauses, payment terms, and liability provisions. The technology creates standardized summaries that allow lawyers to quickly assess the legal landscape without reading every word. This capability has reduced the time required for due diligence from weeks to just days in some cases.

Trí tuệ nhân tạo đang phân tích hợp đồng pháp lý giúp luật sư tiết kiệm thời gian

Legal research has also been transformed by artificial intelligence. Lawyers traditionally spent hours in law libraries searching through case law and statutes to find precedents relevant to their cases. Today, AI-powered research platforms can search through millions of legal documents across multiple jurisdictions within seconds. These systems don’t just match keywords; they understand legal concepts and can find relevant cases even when different terminology is used. The technology ranks results by relevance and can even predict how judges might rule based on historical patterns.

However, the integration of AI into legal services is not without challenges. Many law firms, especially smaller ones, face significant financial barriers to adopting these technologies. High-quality AI systems require substantial upfront investment in software, hardware, and training. There are also concerns about data security and confidentiality. Legal documents contain highly sensitive information, and firms must ensure that AI systems comply with strict privacy regulations.

Despite these challenges, the benefits of AI in legal services are compelling. Law firms that have embraced the technology report increased efficiency, reduced costs, and improved accuracy in their work. Clients benefit from faster service delivery and often lower fees, as firms can complete tasks in less time. Moreover, by automating routine work, AI allows lawyers to focus on tasks that require human judgment, such as strategy development, client counseling, and courtroom advocacy.

The legal profession is also seeing the emergence of new roles specifically related to AI. Legal technologists and legal operations professionals are now in high demand to bridge the gap between traditional legal practice and modern technology. These professionals help firms select appropriate AI tools, integrate them into existing workflows, and train staff to use them effectively.

Looking ahead, experts predict that AI will become even more sophisticated in its ability to assist legal professionals. Future systems may be able to draft basic legal documents, predict litigation outcomes with greater accuracy, and even provide preliminary legal advice to clients. However, most legal experts agree that AI will augment rather than replace human lawyers, as the practice of law requires empathy, ethical judgment, and creative problem-solving that machines cannot replicate.

Questions 1-6

Do the following statements agree with the information given in Passage 1?

Write:

• TRUE if the statement agrees with the information
• FALSE if the statement contradicts the information
• NOT GIVEN if there is no information on this

1. Junior lawyers previously spent significant time reviewing documents for relevant case information.
2. AI systems can analyze documents faster than human teams but with lower accuracy.
3. Contract analysis using AI has reduced due diligence time in some instances from weeks to days.
4. All law firms, regardless of size, have successfully adopted AI technology.
5. Legal documents processed by AI systems always comply with privacy regulations.
6. AI technology allows lawyers to concentrate on tasks requiring human judgment.

Questions 7-10

Complete the sentences below.

Choose NO MORE THAN THREE WORDS from the passage for each answer.

7. AI systems use __ to understand context when analyzing documents.
8. The technology creates __ that help lawyers assess contracts quickly.
9. AI-powered research platforms can search through legal documents across __.
10. Future AI systems may be able to __ with greater accuracy.

Questions 11-13

Choose the correct letter, A, B, C or D.

11. According to the passage, what is one of the main challenges for smaller law firms adopting AI?

    • A. Lack of technical expertise
    • B. High initial investment costs
    • C. Resistance from senior lawyers
    • D. Insufficient legal cases to process

12. What role has emerged specifically related to AI in the legal profession?

    • A. Junior legal analyst
    • B. Digital court reporter
    • C. Legal technologist
    • D. AI software developer

13. What do most legal experts believe about AI’s future role in law?

    • A. It will completely replace human lawyers
    • B. It will supplement human lawyers’ work
    • C. It will only be used for document review
    • D. It will become less important over time

---

PASSAGE 2 – The Ethical and Regulatory Challenges of AI in Legal Practice

Độ khó: Medium (Band 6.0-7.5)

Thời gian đề xuất: 18-20 phút

The rapid proliferation of artificial intelligence in legal services has sparked intense debate among practitioners, ethicists, and regulators about the appropriate boundaries and safeguards for these technologies. While AI promises unprecedented efficiency and accuracy, its deployment in legal contexts raises fundamental questions about professional responsibility, algorithmic bias, and the preservation of core legal values such as confidentiality and the right to human oversight in critical decisions.

One of the most contentious issues surrounding AI in legal services concerns algorithmic transparency. Many sophisticated AI systems, particularly those using deep learning neural networks, operate as “black boxes” – their decision-making processes are so complex that even their creators cannot fully explain how they arrive at specific conclusions. This opacity presents a serious challenge in legal contexts where lawyers have a professional duty to understand and explain the basis for their advice to clients. The American Bar Association’s Model Rules of Professional Conduct require lawyers to provide competent representation, which includes understanding the tools they use. If a lawyer cannot explain how an AI system reached a particular conclusion, questions arise about whether they are fulfilling this ethical obligation.

Tương tự như How is artificial intelligence being used in financial services?, lĩnh vực pháp lý cũng đối mặt với những lo ngại về độ tin cậy của hệ thống AI trong các quyết định quan trọng.

The issue of algorithmic bias presents another significant concern. AI systems learn from historical data, and if that data reflects past prejudices or discriminatory patterns, the AI may perpetuate or even amplify these biases. In the legal field, this is particularly problematic given the profession’s commitment to equal justice. Several studies have documented instances where predictive policing algorithms and risk assessment tools used in criminal justice have shown bias against minority communities. When law firms use AI for tasks such as predicting case outcomes or assessing litigation risk, there is a danger that historical biases embedded in court decisions or legal precedents could influence the AI’s recommendations, potentially disadvantaging certain groups of clients.

Data privacy and security constitute critical regulatory challenges as AI systems in legal services process vast amounts of sensitive client information. Legal professional privilege – the principle that communications between lawyers and clients remain confidential – is a cornerstone of the legal system. However, when client data is fed into AI systems, particularly cloud-based platforms, new vulnerabilities emerge. There have been cases where AI tools inadvertently exposed confidential information through inadequate security measures or when data was used to train algorithms, potentially allowing information from one client’s case to influence another’s. Regulators worldwide are grappling with how to apply existing confidentiality rules to AI-enhanced legal services while fostering innovation.

The question of liability when AI systems make errors adds another layer of complexity. If an AI-powered legal research tool misses a critical precedent, or if a contract review system fails to identify a problematic clause, who bears responsibility – the law firm, the lawyer who relied on the tool, or the AI vendor? Traditional professional negligence frameworks were designed for human error, not algorithmic mistakes. Some jurisdictions are exploring new regulatory approaches, including mandatory disclosure when AI tools are used in legal work and requirements for human review of AI-generated analysis before it is presented to clients or courts.

Thách thức đạo đức và quy định của trí tuệ nhân tạo trong dịch vụ pháp lý hiện đại

Access to justice concerns have emerged as a dual-edged aspect of AI adoption in legal services. Proponents argue that AI can democratize legal services by reducing costs, making legal assistance more affordable for individuals and small businesses who might otherwise be priced out of the market. AI-powered chatbots and automated document services can provide basic legal guidance at a fraction of the cost of traditional legal consultations. However, critics worry about a two-tier system emerging where wealthy clients continue to receive personalized human legal advice while less affluent individuals must settle for algorithm-generated guidance that may not account for the nuances of their situations. There are also concerns that over-reliance on AI could diminish the pipeline of junior lawyers who traditionally learned by doing the routine work that AI now handles.

Regulatory bodies worldwide are taking varied approaches to governing AI in legal services. The European Union’s proposed AI Act would classify certain legal AI applications as “high-risk,” subjecting them to stringent requirements including human oversight, transparency obligations, and conformity assessments before deployment. In contrast, the United States has largely left regulation to state bar associations, resulting in a patchwork of different rules and guidance. Some jurisdictions require lawyers to have technological competence and to stay informed about benefits and risks of relevant technology, while others have issued specific ethics opinions on AI use.

The legal profession itself is divided on how to balance innovation with regulation. Some practitioners advocate for a precautionary approach, arguing that stricter rules should be established before AI becomes more deeply embedded in legal practice. Others contend that overly restrictive regulations could stifle beneficial innovation and put firms that comply at a competitive disadvantage relative to those in less regulated jurisdictions. This tension between fostering innovation and ensuring accountability remains at the heart of ongoing debates about AI governance in legal services.

Questions 14-18

Choose the correct letter, A, B, C or D.

14. What does the passage identify as a major problem with deep learning neural networks in legal contexts?

    • A. They are too expensive to implement
    • B. Their decision-making processes cannot be fully explained
    • C. They make more errors than humans
    • D. They require constant human supervision

15. According to the passage, algorithmic bias in legal AI is concerning because:

    • A. It makes AI systems slower
    • B. It increases operational costs
    • C. It may disadvantage certain client groups
    • D. It violates copyright laws

16. What is described as a “cornerstone of the legal system”?

    • A. Algorithmic transparency
    • B. Legal professional privilege
    • C. Mandatory disclosure
    • D. Professional negligence frameworks

17. The passage suggests that AI’s impact on access to justice is:

    • A. Entirely positive
    • B. Completely negative
    • C. Both beneficial and concerning
    • D. Not yet determined

18. How does the EU’s approach to regulating legal AI differ from the United States?

    • A. The EU has no regulations while the US has comprehensive rules
    • B. The EU proposes unified stringent requirements while the US has varied state-level approaches
    • C. The EU bans all legal AI while the US encourages it
    • D. The EU and US have identical regulatory frameworks

Questions 19-23

Complete the summary below.

Choose NO MORE THAN TWO WORDS from the passage for each answer.

AI systems in legal services raise questions about (19) __, especially when using complex technologies that operate as “black boxes.” The issue of (20) __ is problematic because AI learns from historical data that may contain prejudices. Legal firms must protect (21) __ when using AI systems, particularly with cloud-based platforms. Questions about (22) __ arise when AI systems make mistakes, as traditional frameworks were designed for human error. Some practitioners advocate for a (23) __, arguing for stricter rules before AI becomes more embedded in practice.

Questions 24-26

Do the following statements agree with the claims of the writer in Passage 2?

Write:

• YES if the statement agrees with the claims of the writer
• NO if the statement contradicts the claims of the writer
• NOT GIVEN if it is impossible to say what the writer thinks about this

24. Lawyers can fully explain AI decisions even when using deep learning systems.
25. Over-reliance on AI might reduce opportunities for junior lawyers to develop skills.
26. All regulatory bodies worldwide have adopted the same approach to governing AI in legal services.

---

PASSAGE 3 – The Future Landscape: AI-Augmented Legal Intelligence and Its Societal Implications

Độ khó: Hard (Band 7.0-9.0)

Thời gian đề xuất: 23-25 phút

The inexorable integration of artificial intelligence into the legal profession represents not merely a technological evolution but a fundamental reconceptualization of how legal knowledge is created, disseminated, and applied. As AI capabilities advance from narrow, task-specific applications to more sophisticated systems capable of contextual reasoning and predictive analytics, the legal profession stands at an inflection point that will determine not only the future of legal practice but also the accessibility, equity, and legitimacy of legal systems worldwide. Understanding this transformation requires examining both the technological trajectories and the profound societal implications that extend far beyond the confines of law firms and courtrooms.

Contemporary discourse on AI in legal services often focuses on current applications – document review, contract analysis, and legal research – but emerging developments suggest far more transformative capabilities on the horizon. Advanced natural language generation systems are now capable of drafting increasingly sophisticated legal documents, from standard contracts to complex memoranda of law, with minimal human input. These systems don’t simply fill in templates; they can synthesize legal principles, apply them to specific factual scenarios, and generate reasoned arguments that mirror the structure and style of documents produced by experienced lawyers. More remarkably, experimental AI systems are demonstrating the ability to engage in legal reasoning that approximates the inferential processes humans use when applying legal rules to novel situations.

The development of predictive justice algorithms represents perhaps the most controversial frontier in legal AI. These systems analyze vast databases of judicial decisions, identifying patterns in how judges rule based on factors such as case characteristics, procedural history, jurisdictional context, and even the demographic composition of parties involved. Some systems claim accuracy rates exceeding 70% in predicting appellate court outcomes. Proponents argue this technology can help lawyers make more informed strategic decisions, assist courts in managing caseloads more efficiently, and potentially reduce arbitrary disparities in judicial decision-making by highlighting inconsistencies. However, critics contend that such systems risk creating self-fulfilling prophecies where AI predictions influence lawyer behavior and settlement decisions in ways that reinforce existing patterns, potentially calcifying injustices rather than correcting them.

Điều này có điểm tương đồng với What are the challenges of regulating autonomous vehicles? khi cả hai lĩnh vực đều phải cân nhắc giữa dự đoán công nghệ và các hệ quả pháp lý tiềm tàng.

The epistemological implications of AI in law extend to fundamental questions about the nature of legal knowledge itself. Traditional legal education and practice emphasize interpretive skills, the ability to construct persuasive arguments, and the application of professional judgment in ambiguous situations. As AI systems become more capable of performing these cognitive tasks, questions arise about what distinctly human contribution remains essential to legal practice. Some scholars argue that law’s normative dimension – its role in expressing societal values and making ethical judgments – constitutes an irreducible human element that machines cannot replicate. Others suggest that even these seemingly ineffable qualities might eventually be algorithmatized as AI systems become more sophisticated in processing contextual and cultural nuances.

The economic ramifications of widespread AI adoption in legal services are multifaceted and potentially disruptive. Traditional law firm business models, which have historically billed clients based on hours worked, face fundamental challenges when AI can complete in minutes tasks that previously required days of lawyer time. This has accelerated the shift toward value-based billing and alternative fee arrangements, fundamentally altering the economics of legal practice. While large firms with resources to invest in AI infrastructure may gain competitive advantages, smaller firms could find themselves unable to compete, potentially leading to market concentration that paradoxically reduces competition and increases costs for clients despite AI’s efficiency gains.

For legal professionals themselves, AI’s ascendancy necessitates profound adaptations in skills and roles. The commoditization of routine legal work threatens to eliminate many entry-level positions that have traditionally served as training grounds for new lawyers. This creates what some call a “missing middle problem” – a gap between legal education and the high-level strategic work that remains valuable in an AI-augmented profession. Legal educators are grappling with curricular reforms, debating whether law schools should incorporate more training in technology, data science, and AI systems, potentially at the expense of traditional doctrinal instruction or clinical legal education.

Một ví dụ chi tiết về Smart cities and data privacy cho thấy cách các hệ thống công nghệ phức tạp cần cân bằng giữa hiệu quả và quyền riêng tư, một bài học quan trọng cho ngành pháp lý.

From a societal perspective, AI in legal services raises critical questions about democratic accountability and the rule of law. Legal systems derive legitimacy partly from their transparency and the ability of citizens to understand and contest the application of laws. When legal decisions are influenced by opaque algorithms, this transparency is compromised. Moreover, if access to the most sophisticated AI legal tools becomes a significant determinant of legal outcomes, existing inequities in legal representation could be exacerbated, creating what some scholars call “algorithmic injustice” – systematic disadvantages for those without resources to deploy equivalent technological capabilities.

The international dimensions of legal AI development add further complexity. Different legal traditions – common law versus civil law systems, adversarial versus inquisitorial procedures – may be differentially amenable to AI augmentation. Countries with more codified legal systems might find it easier to develop effective AI tools, potentially giving them advantages in cross-border legal services and international arbitration. This raises questions about whether AI could drive convergence among different legal systems or alternatively create new forms of legal fragmentation where technological capabilities rather than substantive legal principles determine forum selection and jurisdictional preferences.

Looking toward the coming decades, the trajectory of AI in legal services will likely be shaped by ongoing dialectical tensions: between efficiency and equity, between innovation and regulation, between augmentation and displacement of human expertise, and between the universalizing tendencies of technology and the particularistic requirements of law rooted in specific cultural and political contexts. How these tensions are resolved will determine not only the future of the legal profession but also the character of justice systems and the accessibility of legal remedies in an increasingly complex world. The challenge for policymakers, legal professionals, and society broadly is to harness AI’s potential to enhance legal services while preserving the essential human elements of judgment, empathy, and ethical reasoning that remain central to the administration of justice.

Questions 27-31

Complete each sentence with the correct ending, A-H, below.

27. Advanced natural language generation systems can
28. Predictive justice algorithms analyze
29. Traditional legal education emphasizes
30. The commoditization of routine legal work may
31. Different legal traditions worldwide might

A. eliminate entry-level positions that serve as training grounds
B. vast databases to identify patterns in judicial decisions
C. create algorithmic injustice for disadvantaged groups
D. generate complex legal documents with minimal human input
E. respond differently to AI augmentation opportunities
F. require only template-based document production
G. interpretive skills and professional judgment application
H. reduce the need for human lawyers completely

Questions 32-36

Do the following statements agree with the claims of the writer in Passage 3?

Write:

• YES if the statement agrees with the claims of the writer
• NO if the statement contradicts the claims of the writer
• NOT GIVEN if it is impossible to say what the writer thinks about this

32. Current AI systems can only perform simple, template-based tasks in legal work.
33. Predictive justice algorithms that influence legal outcomes may reinforce existing patterns of injustice.
34. All scholars agree that AI will never be able to replicate the normative dimension of law.
35. Smaller law firms may struggle to compete if they cannot invest in AI infrastructure.
36. Law schools have successfully implemented comprehensive AI training programs worldwide.

Questions 37-40

Answer the questions below.

Choose NO MORE THAN THREE WORDS from the passage for each answer.

37. What do some systems claim to predict with over 70% accuracy?
38. What type of billing is becoming more common as AI changes how legal work is completed?
39. What problem describes the gap between legal education and high-level strategic work?
40. According to the passage, what must be preserved in the administration of justice despite AI adoption?

---

Answer Keys – Đáp Án

PASSAGE 1: Questions 1-13

1. TRUE
2. FALSE
3. TRUE
4. FALSE
5. NOT GIVEN
6. TRUE
7. natural language processing
8. standardized summaries
9. multiple jurisdictions
10. predict litigation outcomes
11. B
12. C
13. B

PASSAGE 2: Questions 14-26

14. B
15. C
16. B
17. C
18. B
19. algorithmic transparency
20. algorithmic bias
21. client data / data privacy
22. liability
23. precautionary approach
24. NO
25. YES
26. NO

PASSAGE 3: Questions 27-40

27. D
28. B
29. G
30. A
31. E
32. NO
33. YES
34. NO
35. YES
36. NOT GIVEN
37. appellate court outcomes
38. value-based billing
39. missing middle problem
40. human elements / judgment, empathy (accept either)

---

Giải Thích Đáp Án Chi Tiết

Passage 1 – Giải Thích

Câu 1: TRUE

• Dạng câu hỏi: True/False/Not Given
• Từ khóa: Junior lawyers, spent significant time, reviewing documents
• Vị trí trong bài: Đoạn 2, dòng 2-4
• Giải thích: Bài đọc nói rõ “junior lawyers spent countless hours reading through thousands of pages of contracts, emails, and other documents to find relevant information for cases” – phù hợp hoàn toàn với câu hỏi về việc junior lawyers dành thời gian đáng kể để xem xét tài liệu.

Câu 2: FALSE

• Dạng câu hỏi: True/False/Not Given
• Từ khóa: AI systems, analyze documents faster, lower accuracy
• Vị trí trong bài: Đoạn 2, dòng 6-9
• Giải thích: Câu hỏi nói AI phân tích nhanh hơn nhưng độ chính xác thấp hơn. Bài đọc khẳng định AI có thể “scan and analyze vast quantities of documents in a fraction of the time” và “identify key clauses… with remarkable accuracy” – nghĩa là độ chính xác cao, không phải thấp. Do đó đáp án là FALSE.

Câu 3: TRUE

• Dạng câu hỏi: True/False/Not Given
• Từ khóa: Contract analysis, due diligence time, weeks to days
• Vị trí trong bài: Đoạn 3, dòng cuối
• Giải thích: Bài đọc có câu “This capability has reduced the time required for due diligence from weeks to just days in some cases” – khớp chính xác với câu hỏi.

Câu 4: FALSE

• Dạng câu hỏi: True/False/Not Given
• Từ khóa: All law firms, regardless of size, successfully adopted
• Vị trí trong bài: Đoạn 5, dòng 2-3
• Giải thích: Bài đọc nói “Many law firms, especially smaller ones, face significant financial barriers to adopting these technologies” – nghĩa là không phải tất cả firms đều thành công, đặc biệt là các firm nhỏ gặp khó khăn. Câu hỏi nói “all” nên sai.

Câu 6: TRUE

• Dạng câu hỏi: True/False/Not Given
• Từ khóa: AI technology, lawyers concentrate, tasks requiring human judgment
• Vị trí trong bài: Đoạn 6, dòng cuối
• Giải thích: Bài đọc nói “by automating routine work, AI allows lawyers to focus on tasks that require human judgment” – paraphrase của câu hỏi với “allows lawyers to focus” = “lawyers concentrate”.

Câu 7: natural language processing

• Dạng câu hỏi: Sentence Completion
• Từ khóa: AI systems use, to understand context
• Vị trí trong bài: Đoạn 2, dòng 8
• Giải thích: “These systems use natural language processing to understand context” – đúng chính xác 3 từ.

Câu 10: predict litigation outcomes

• Dạng câu hỏi: Sentence Completion
• Từ khóa: Future AI systems, with greater accuracy
• Vị trí trong bài: Đoạn 8, dòng 2-3
• Giải thích: Bài đọc nói “Future systems may be able to… predict litigation outcomes with greater accuracy” – đúng 3 từ.

Câu 11: B – High initial investment costs

• Dạng câu hỏi: Multiple Choice
• Từ khóa: challenges, smaller law firms, adopting AI
• Vị trí trong bài: Đoạn 5, dòng 2-4
• Giải thích: Bài đọc nói rõ “Many law firms, especially smaller ones, face significant financial barriers… High-quality AI systems require substantial upfront investment” – “substantial upfront investment” = “high initial investment costs”.

Câu 13: B – It will supplement human lawyers’ work

• Dạng câu hỏi: Multiple Choice
• Từ khóa: most legal experts believe, AI’s future role
• Vị trí trong bài: Đoạn 8, dòng cuối
• Giải thích: “most legal experts agree that AI will augment rather than replace human lawyers” – “augment” = “supplement”, không phải thay thế hoàn toàn.

Passage 2 – Giải Thích

Câu 14: B – Their decision-making processes cannot be fully explained

• Dạng câu hỏi: Multiple Choice
• Từ khóa: major problem, deep learning neural networks
• Vị trí trong bài: Đoạn 2, dòng 2-5
• Giải thích: Bài đọc nói AI systems using deep learning “operate as ‘black boxes’ – their decision-making processes are so complex that even their creators cannot fully explain how they arrive at specific conclusions.” Đây chính là vấn đề về transparency.

Câu 15: C – It may disadvantage certain client groups

• Dạng câu hỏi: Multiple Choice
• Từ khóa: algorithmic bias, concerning
• Vị trí trong bài: Đoạn 3, dòng 8-10
• Giải thích: “there is a danger that historical biases… could influence the AI’s recommendations, potentially disadvantaging certain groups of clients” – khớp chính xác với đáp án C.

Câu 16: B – Legal professional privilege

• Dạng câu hỏi: Multiple Choice
• Từ khóa: cornerstone of the legal system
• Vị trí trong bài: Đoạn 4, dòng 2-3
• Giải thích: “Legal professional privilege… is a cornerstone of the legal system” – trích dẫn trực tiếp từ bài.

Câu 17: C – Both beneficial and concerning

• Dạng câu hỏi: Multiple Choice
• Từ khóa: AI’s impact, access to justice
• Vị trí trong bài: Đoạn 6
• Giải thích: Đoạn 6 bắt đầu với “dual-edged aspect” và nêu cả mặt tích cực (democratize legal services, reduce costs) và tiêu cực (two-tier system, algorithm-generated guidance may not account for nuances).

Câu 18: B – The EU proposes unified stringent requirements while the US has varied state-level approaches

• Dạng câu hỏi: Multiple Choice
• Từ khóa: EU’s approach differ from United States
• Vị trí trong bài: Đoạn 7
• Giải thích: Bài đọc nói EU có “AI Act” với “stringent requirements” while US “has largely left regulation to state bar associations, resulting in a patchwork of different rules” – khớp với đáp án B.

Câu 19: algorithmic transparency

• Dạng câu hỏi: Summary Completion
• Vị trí trong bài: Đoạn 2, dòng đầu
• Giải thích: Câu mở đầu đoạn 2: “One of the most contentious issues… concerns algorithmic transparency.”

Câu 20: algorithmic bias

• Dạng câu hỏi: Summary Completion
• Vị trí trong bài: Đoạn 3, dòng đầu
• Giải thích: “The issue of algorithmic bias presents another significant concern.”

Câu 22: liability

• Dạng câu hỏi: Summary Completion
• Vị trí trong bài: Đoạn 5, dòng đầu
• Giải thích: “The question of liability when AI systems make errors…”

Câu 24: NO

• Dạng câu hỏi: Yes/No/Not Given
• Vị trí trong bài: Đoạn 2
• Giải thích: Bài đọc nói rõ “even their creators cannot fully explain how they arrive at specific conclusions” – nghĩa là lawyers KHÔNG thể giải thích đầy đủ, trái với câu hỏi.

Câu 25: YES

• Dạng câu hỏi: Yes/No/Not Given
• Vị trí trong bài: Đoạn 6, dòng cuối
• Giải thích: “over-reliance on AI could diminish the pipeline of junior lawyers who traditionally learned by doing the routine work that AI now handles” – hoàn toàn khớp với câu hỏi.

Câu 26: NO

• Dạng câu hỏi: Yes/No/Not Given
• Vị trí trong bài: Đoạn 7
• Giải thích: Bài đọc nói “Regulatory bodies worldwide are taking varied approaches” – nghĩa là KHÔNG giống nhau, trái với câu hỏi nói “same approach”.

Passage 3 – Giải Thích

Câu 27: D – generate complex legal documents with minimal human input

• Dạng câu hỏi: Matching Sentence Endings
• Vị trí trong bài: Đoạn 2, dòng 2-4
• Giải thích: “Advanced natural language generation systems are now capable of drafting increasingly sophisticated legal documents… with minimal human input.”

Câu 28: B – vast databases to identify patterns in judicial decisions

• Dạng câu hỏi: Matching Sentence Endings
• Vị trí trong bài: Đoạn 3, dòng 2-3
• Giải thích: “These systems analyze vast databases of judicial decisions, identifying patterns…”

Câu 29: G – interpretive skills and professional judgment application

• Dạng câu hỏi: Matching Sentence Endings
• Vị trí trong bài: Đoạn 4, dòng 2-3
• Giải thích: “Traditional legal education and practice emphasize interpretive skills… and the application of professional judgment.”

Câu 30: A – eliminate entry-level positions that serve as training grounds

• Dạng câu hỏi: Matching Sentence Endings
• Vị trí trong bài: Đoạn 6, dòng 2-3
• Giải thích: “The commoditization of routine legal work threatens to eliminate many entry-level positions that have traditionally served as training grounds.”

Câu 31: E – respond differently to AI augmentation opportunities

• Dạng câu hỏi: Matching Sentence Endings
• Vị trí trong bài: Đoạn 8, dòng 2-3
• Giải thích: “Different legal traditions… may be differentially amenable to AI augmentation” – paraphrase là “respond differently”.

Câu 32: NO

• Dạng câu hỏi: Yes/No/Not Given
• Vị trí trong bài: Đoạn 2
• Giải thích: Bài đọc nói AI hiện tại đã vượt qua “narrow, task-specific applications” và có thể “synthesize legal principles, apply them to specific factual scenarios” – không chỉ làm các task đơn giản dựa trên template. Câu hỏi nói “only simple” nên là NO.

Câu 33: YES

• Dạng câu hỏi: Yes/No/Not Given
• Vị trí trong bài: Đoạn 3, dòng cuối
• Giải thích: “such systems risk creating self-fulfilling prophecies… potentially calcifying injustices rather than correcting them” – khớp với câu hỏi về việc reinforce existing patterns of injustice.

Câu 34: NO

• Dạng câu hỏi: Yes/No/Not Given
• Vị trí trong bài: Đoạn 4, dòng cuối
• Giải thích: Bài đọc nói “Some scholars argue… Others suggest that even these… might eventually be algorithmatized” – nghĩa là KHÔNG phải all scholars đồng ý, mà có quan điểm khác nhau.

Câu 35: YES

• Dạng câu hỏi: Yes/No/Not Given
• Vị trí trong bài: Đoạn 5, dòng 4-6
• Giải thích: “smaller firms could find themselves unable to compete” nếu không thể invest in AI infrastructure – khớp với câu hỏi.

Câu 37: appellate court outcomes

• Dạng câu hỏi: Short-answer Questions
• Vị trí trong bài: Đoạn 3, dòng 5-6
• Giải thích: “Some systems claim accuracy rates exceeding 70% in predicting appellate court outcomes.”

Câu 38: value-based billing

• Dạng câu hỏi: Short-answer Questions
• Vị trí trong bài: Đoạn 5, dòng 4
• Giải thích: “This has accelerated the shift toward value-based billing and alternative fee arrangements.”

Câu 39: missing middle problem

• Dạng câu hỏi: Short-answer Questions
• Vị trí trong bài: Đoạn 6, dòng 4-5
• Giải thích: “This creates what some call a ‘missing middle problem’ – a gap between legal education and the high-level strategic work.”

Câu 40: human elements / judgment, empathy

• Dạng câu hỏi: Short-answer Questions
• Vị trí trong bài: Đoạn 9, dòng cuối
• Giải thích: “preserving the essential human elements of judgment, empathy, and ethical reasoning” – chấp nhận “human elements” hoặc “judgment, empathy” (lấy 2-3 từ đầu).

---

Từ Vựng Quan Trọng Theo Passage

Passage 1 – Essential Vocabulary

Từ vựng	Loại từ	Phiên âm	Nghĩa tiếng Việt	Ví dụ từ bài	Collocation
adopt	v	/əˈdɒpt/	áp dụng, chấp nhận	Law firms are increasingly adopting AI	adopt technology, adopt a system
streamline	v	/ˈstriːmlaɪn/	đơn giản hóa, tối ưu hóa	to streamline their operations	streamline operations, streamline processes
reliant	adj	/rɪˈlaɪənt/	phụ thuộc vào	reliant solely on human expertise	be reliant on, heavily reliant
document review	n	/ˈdɒkjumənt rɪˈvjuː/	việc xem xét tài liệu	document review is time-consuming	conduct document review, automate document review
time-consuming	adj	/ˈtaɪm kənˌsjuːmɪŋ/	tốn thời gian	This process was time-consuming	time-consuming task, time-consuming process
prone to	adj phrase	/prəʊn tuː/	dễ có khuynh hướng	prone to human error	prone to error, prone to mistakes
vast quantities	n phrase	/vɑːst ˈkwɒntɪtiz/	số lượng khổng lồ	analyze vast quantities of documents	vast quantities of data, vast quantities of information
natural language processing	n	/ˈnætʃrəl ˈlæŋɡwɪdʒ ˈprəʊsesɪŋ/	xử lý ngôn ngữ tự nhiên	use natural language processing	apply NLP, NLP technology
substantial	adj	/səbˈstænʃəl/	đáng kể, quan trọng	made substantial inroads	substantial investment, substantial progress
extract	v	/ɪkˈstrækt/	trích xuất, lấy ra	extract critical information	extract data, extract information
due diligence	n	/djuː ˈdɪlɪdʒəns/	quy trình thẩm định	reduced time for due diligence	conduct due diligence, due diligence process
augment	v	/ɔːɡˈment/	bổ sung, tăng cường	AI will augment human lawyers	augment capacity, augment skills

Passage 2 – Essential Vocabulary

Từ vựng	Loại từ	Phiên âm	Nghĩa tiếng Việt	Ví dụ từ bài	Collocation
proliferation	n	/prəˌlɪfəˈreɪʃən/	sự phát triển nhanh chóng	rapid proliferation of AI	proliferation of technology, nuclear proliferation
contentious	adj	/kənˈtenʃəs/	gây tranh cãi	contentious issues	contentious issue, contentious debate
algorithmic transparency	n phrase	/ˌælɡəˈrɪðmɪk trænsˈpærənsi/	tính minh bạch của thuật toán	concerns algorithmic transparency	ensure algorithmic transparency, lack of transparency
deep learning neural networks	n phrase	/diːp ˈlɜːnɪŋ ˈnjʊərəl ˈnetwɜːks/	mạng nơ-ron học sâu	systems using deep learning neural networks	train neural networks, neural network architecture
opacity	n	/əʊˈpæsɪti/	tính không minh bạch	This opacity presents a challenge	opacity of algorithms, lack of transparency
algorithmic bias	n phrase	/ˌælɡəˈrɪðmɪk ˈbaɪəs/	sự thiên vị của thuật toán	issue of algorithmic bias	address algorithmic bias, eliminate bias
perpetuate	v	/pəˈpetʃueɪt/	duy trì, làm tồn tại lâu	perpetuate biases	perpetuate inequality, perpetuate stereotypes
discriminatory patterns	n phrase	/dɪˈskrɪmɪnətəri ˈpætənz/	các mô hình phân biệt đối xử	data reflects discriminatory patterns	identify discriminatory patterns, eliminate discrimination
cornerstone	n	/ˈkɔːnəstəʊn/	nền tảng, trụ cột	cornerstone of the legal system	cornerstone of democracy, cornerstone principle
inadequate security measures	n phrase	/ɪnˈædɪkwət sɪˈkjʊərɪti ˈmeʒəz/	các biện pháp bảo mật không đầy đủ	exposed information through inadequate security	implement security measures, strengthen security
liability	n	/ˌlaɪəˈbɪlɪti/	trách nhiệm pháp lý	question of liability	legal liability, liability for damages
professional negligence	n phrase	/prəˈfeʃənəl ˈneɡlɪdʒəns/	sơ suất chuyên môn	professional negligence frameworks	claim of professional negligence, negligence lawsuit
democratize	v	/dɪˈmɒkrətaɪz/	dân chủ hóa, phổ cập	AI can democratize legal services	democratize access, democratize information
two-tier system	n phrase	/tuː tɪə ˈsɪstəm/	hệ thống hai cấp	worry about a two-tier system	create a two-tier system, two-tier healthcare
stringent requirements	n phrase	/ˈstrɪndʒənt rɪˈkwaɪəmənts/	các yêu cầu nghiêm ngặt	subjecting them to stringent requirements	meet stringent requirements, impose requirements

Passage 3 – Essential Vocabulary

Từ vựng	Loại từ	Phiên âm	Nghĩa tiếng Việt	Ví dụ từ bài	Collocation
inexorable	adj	/ɪnˈeksərəbəl/	không thể cản lại, tất yếu	inexorable integration	inexorable decline, inexorable trend
reconceptualization	n	/ˌriːkənˌseptʃuəlaɪˈzeɪʃən/	việc tái khái niệm hóa	fundamental reconceptualization	require reconceptualization, undergo reconceptualization
inflection point	n phrase	/ɪnˈflekʃən pɔɪnt/	điểm uốn, bước ngoặt	stands at an inflection point	reach an inflection point, critical inflection point
transformative capabilities	n phrase	/trænsˈfɔːmətɪv ˌkeɪpəˈbɪlɪtiz/	khả năng chuyển đổi	far more transformative capabilities	demonstrate capabilities, technological capabilities
natural language generation	n phrase	/ˈnætʃrəl ˈlæŋɡwɪdʒ ˌdʒenəˈreɪʃən/	tạo ngôn ngữ tự nhiên	advanced natural language generation	use language generation, NLG systems
memoranda of law	n phrase	/ˌmeməˈrændə əv lɔː/	bản ghi nhớ pháp lý	draft complex memoranda of law	prepare memoranda, legal memoranda
synthesize	v	/ˈsɪnθəsaɪz/	tổng hợp	synthesize legal principles	synthesize information, synthesize data
inferential processes	n phrase	/ˌɪnfəˈrenʃəl ˈprəʊsesɪz/	các quá trình suy luận	mirror inferential processes	use inferential processes, cognitive processes
predictive justice algorithms	n phrase	/prɪˈdɪktɪv ˈdʒʌstɪs ˈælɡərɪðəmz/	thuật toán dự đoán công lý	development of predictive justice algorithms	deploy algorithms, sophisticated algorithms
appellate court outcomes	n phrase	/əˈpelət kɔːt ˈaʊtkʌmz/	kết quả tòa phúc thẩm	predicting appellate court outcomes	influence outcomes, predict outcomes
self-fulfilling prophecies	n phrase	/self fʊlˈfɪlɪŋ ˈprɒfɪsiz/	lời tiên tri tự ứng nghiệm	risk creating self-fulfilling prophecies	become a self-fulfilling prophecy, avoid prophecies
calcify	v	/ˈkælsɪfaɪ/	làm cứng lại, làm cố định	calcifying injustices	calcify attitudes, calcify divisions
epistemological implications	n phrase	/ɪˌpɪstəməˈlɒdʒɪkəl ˌɪmplɪˈkeɪʃənz/	các hàm ý nhận thức luận	epistemological implications of AI	examine implications, philosophical implications
normative dimension	n phrase	/ˈnɔːmətɪv dɪˈmenʃən/	khía cạnh quy phạm	law’s normative dimension	normative dimension of ethics, normative framework
irreducible	adj	/ˌɪrɪˈdjuːsəbəl/	không thể rút gọn	irreducible human element	irreducible complexity, irreducible minimum
algorithmatized	v (past participle)	/ˌælɡəˈrɪðməˌtaɪzd/	được thuật toán hóa	might be algorithmatized	algorithmatize processes, become algorithmatized
commoditization	n	/kəˌmɒdɪtaɪˈzeɪʃən/	sự hàng hóa hóa	commoditization of routine legal work	prevent commoditization, commoditization of services
value-based billing	n phrase	/ˈvæljuː beɪst ˈbɪlɪŋ/	thanh toán theo giá trị	shift toward value-based billing	adopt value-based billing, value-based pricing
market concentration	n phrase	/ˈmɑːkɪt ˌkɒnsənˈtreɪʃən/	sự tập trung thị trường	lead to market concentration	increase market concentration, high concentration
dialectical tensions	n phrase	/ˌdaɪəˈlektɪkəl ˈtenʃənz/	những căng thẳng biện chứng	shaped by dialectical tensions	resolve tensions, dialectical relationship
particularistic requirements	n phrase	/pəˌtɪkjʊləˈrɪstɪk rɪˈkwaɪəmənts/	các yêu cầu đặc thù	particularistic requirements of law	meet requirements, specific requirements

---

Kết Bài

Chủ đề về AI in legal services không chỉ là một xu hướng công nghệ mà còn phản ánh sự chuyển đổi sâu rộng của toàn ngành pháp lý toàn cầu. Qua ba passages với độ khó tăng dần, bạn đã được tiếp cận với từ vựng chuyên ngành đa dạng, các cấu trúc ngữ pháp học thuật và kỹ thuật paraphrase tinh vi thường xuất hiện trong đề thi IELTS Reading thật.

Đề thi mẫu này cung cấp đầy đủ 40 câu hỏi với 7 dạng khác nhau, giúp bạn làm quen với tất cả các định dạng phổ biến như True/False/Not Given, Multiple Choice, Matching Headings và Summary Completion. Phần giải thích chi tiết không chỉ đưa ra đáp án mà còn hướng dẫn cách xác định vị trí thông tin, nhận diện từ khóa và áp dụng chiến lược làm bài hiệu quả.

Để hiểu rõ hơn về Impact of smart technologies on urban living, bạn có thể tham khảo bài viết liên quan trên website. Ngoài ra, chủ đề The role of renewable energy in rural electrification cũng cung cấp nhiều từ vựng hữu ích cho kỳ thi IELTS.

Hãy thực hành thường xuyên với các đề thi mẫu chất lượng cao như thế này, ghi nhớ từ vựng trong ngữ cảnh và phân tích cách paraphrase để nâng cao band điểm Reading của bạn. Chúc bạn thi tốt và đạt được mục tiêu IELTS mong muốn!