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1. PTE Academic Reading: Re-order Paragraphs Practice – Artificial Intelligence Ethics [Interactive Tutorial + Answers]
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August 1, 2025
![Master PTE Academic Reading ‘Re-order Paragraphs’ questions with this ultra-interactive tutorial! Practice with a real-level passage about Artificial Intelligence Ethics, get instant feedback, step-by-step explanations, advanced vocabulary and phrases, and two deep practice exercises. Includes mobile-friendly design, animated answer keys, and expert tips. Perfect for high PTE Reading scores! - PTE Academic Reading: Re-order Paragraphs Practice – Artificial Intelligence Ethics [Interactive Tutorial + Answers] - LingExam Language Academy - Lingexam.com](https://lingexam.com/wp-content/uploads/2025/08/Article-Thumbnail-5.jpg)
Re-order Paragraphs Questions (PTE Academic Reading Tutorial – Artificial Intelligence Ethics)
What are Re-order Paragraphs Questions?
In this PTE Academic question type, you are given several sentences or paragraphs from a passage in random order. Your task is to rearrange them to form a logically coherent and meaningful text. This question type tests your ability to understand overall structure, logical connectors, and the flow of academic writing—a critical skill for real-world academic and professional reading.
In this PTE Academic question type, you are given several sentences or paragraphs from a passage in random order. Your task is to rearrange them to form a logically coherent and meaningful text. This question type tests your ability to understand overall structure, logical connectors, and the flow of academic writing—a critical skill for real-world academic and professional reading.
How to Answer Re-order Paragraphs Questions – Step by Step
1
Read All Paragraphs Quickly:
Start by reading every paragraph once to get a general sense of the topic, tone, and main ideas. Do not try to reorder yet—just absorb what each paragraph is about. Notice recurring terms or ideas related to artificial intelligence ethics.
Example: Identify if a paragraph introduces the topic or summarizes the whole passage.
Start by reading every paragraph once to get a general sense of the topic, tone, and main ideas. Do not try to reorder yet—just absorb what each paragraph is about. Notice recurring terms or ideas related to artificial intelligence ethics.
Example: Identify if a paragraph introduces the topic or summarizes the whole passage.
2
Find the Topic Sentence or Introduction:
Look for the paragraph that introduces the topic or gives a general overview. It usually does not reference prior information and sets the context for what follows.
Example: "Artificial intelligence raises profound ethical questions..." is likely to be the first.
Look for the paragraph that introduces the topic or gives a general overview. It usually does not reference prior information and sets the context for what follows.
Example: "Artificial intelligence raises profound ethical questions..." is likely to be the first.
3
Identify Concluding or Summary Paragraphs:
The final paragraph usually sums up the argument, offers a solution, or calls for future action. It may use phrases like “in conclusion,” “ultimately,” or “as a result.”
Example: “In conclusion, effective regulation will require cooperation...”
The final paragraph usually sums up the argument, offers a solution, or calls for future action. It may use phrases like “in conclusion,” “ultimately,” or “as a result.”
Example: “In conclusion, effective regulation will require cooperation...”
4
Look for Logical Connectors:
Notice transition words (however, furthermore, in addition, as a result, on the other hand) and pronouns (this, these, such, they) that link one paragraph to another.
Example: A paragraph starting with “However, this raises concerns about bias...” cannot be the first.
Notice transition words (however, furthermore, in addition, as a result, on the other hand) and pronouns (this, these, such, they) that link one paragraph to another.
Example: A paragraph starting with “However, this raises concerns about bias...” cannot be the first.
5
Match References and Pronouns:
If a paragraph uses “this approach,” “these systems,” or “such concerns,” check previous paragraphs for the subject they refer to. This helps you determine the correct sequence.
Example: “These risks” must refer to risks already introduced.
If a paragraph uses “this approach,” “these systems,” or “such concerns,” check previous paragraphs for the subject they refer to. This helps you determine the correct sequence.
Example: “These risks” must refer to risks already introduced.
6
Establish Cause-and-Effect Relationships:
Find which paragraphs describe causes and which describe effects or consequences. Typically, cause comes before effect in academic logic.
Example: “Because of unregulated data use,...” should precede “As a result, public trust may decline.”
Find which paragraphs describe causes and which describe effects or consequences. Typically, cause comes before effect in academic logic.
Example: “Because of unregulated data use,...” should precede “As a result, public trust may decline.”
7
Organize Supporting Details:
After identifying the introduction and conclusion, place supporting detail paragraphs in a logical order. These usually provide examples, case studies, or arguments that build on the main idea.
Example: After the introduction, a paragraph about AI bias might logically be followed by one on transparency as a solution.
After identifying the introduction and conclusion, place supporting detail paragraphs in a logical order. These usually provide examples, case studies, or arguments that build on the main idea.
Example: After the introduction, a paragraph about AI bias might logically be followed by one on transparency as a solution.
8
Re-read Your Chosen Order:
Put the paragraphs in your chosen sequence and reread the full passage. Make sure the flow is smooth and logical, with no sudden jumps or missing information.
Example: Do all pronouns and ideas refer clearly to something earlier? Does the argument develop naturally?
Put the paragraphs in your chosen sequence and reread the full passage. Make sure the flow is smooth and logical, with no sudden jumps or missing information.
Example: Do all pronouns and ideas refer clearly to something earlier? Does the argument develop naturally?
9
Double-Check Transitions and References:
Ensure each paragraph leads naturally into the next. If a paragraph seems out of place or repeats information, reconsider its position.
Example: A paragraph about solutions should not come before a paragraph about the problems.
Ensure each paragraph leads naturally into the next. If a paragraph seems out of place or repeats information, reconsider its position.
Example: A paragraph about solutions should not come before a paragraph about the problems.
10
Practice Regularly!
Re-order Paragraphs is a skill that improves with practice. Use a variety of academic topics—like AI ethics—to build your intuition for structure, cohesion, and logical development.
Example: The more you practice, the easier it becomes to recognize patterns and correct paragraph flow.
Re-order Paragraphs is a skill that improves with practice. Use a variety of academic topics—like AI ethics—to build your intuition for structure, cohesion, and logical development.
Example: The more you practice, the easier it becomes to recognize patterns and correct paragraph flow.
Example: Mini Re-order Task
Example Sentences (Random Order):
(A) As AI becomes more widespread, ethical considerations grow more urgent.
(B) In conclusion, society must ensure ethical standards are embedded in all AI systems.
(C) However, without oversight, these systems may perpetuate existing biases.
Sample Correct Order: (A) → (C) → (B)
Why? (A) introduces the topic, (C) adds a problem, (B) concludes with a call to action.
(A) As AI becomes more widespread, ethical considerations grow more urgent.
(B) In conclusion, society must ensure ethical standards are embedded in all AI systems.
(C) However, without oversight, these systems may perpetuate existing biases.
Sample Correct Order: (A) → (C) → (B)
Why? (A) introduces the topic, (C) adds a problem, (B) concludes with a call to action.
Practice: Re-order Paragraphs – Artificial Intelligence Ethics
Instructions: Below are four paragraphs from an academic passage about Artificial Intelligence ethics. They are presented in the wrong order. Drag and drop the cards to arrange them into the most logical and coherent sequence.
When you are finished, click "Submit" to check your answer and get a detailed step-by-step explanation for each paragraph’s position.
When you are finished, click "Submit" to check your answer and get a detailed step-by-step explanation for each paragraph’s position.
Arrange the Paragraphs:
A. Artificial intelligence (AI) has advanced rapidly, offering transformative benefits but also raising profound ethical concerns. As AI systems are entrusted with decisions in areas such as healthcare, law, and hiring, questions about fairness, accountability, and transparency have become central to public debate.
B. A major challenge lies in the potential for AI systems to inherit or even amplify human biases. For example, if algorithms are trained on historical data that reflects social inequalities, their decisions may reinforce discrimination rather than correct it, leading to unjust outcomes.
C. In response, experts emphasize the importance of transparency and oversight. Making AI algorithms open to inspection and requiring clear explanations for automated decisions can help build public trust and reduce the risk of unintended harm.
D. Ultimately, ensuring ethical AI development will require collaboration between technologists, policymakers, and the wider community. By establishing robust ethical standards and accountability mechanisms, society can better harness the benefits of AI while minimizing its risks.
Answer Key & Step-by-Step Explanation
See exactly how to solve this PTE Academic Re-order Paragraphs question. Read the step-by-step academic reasoning for each paragraph’s position. Deep explanations help you master both logic and English cohesion.
1st: (A)
Artificial intelligence (AI) has advanced rapidly, offering transformative benefits but also raising profound ethical concerns. As AI systems are entrusted with decisions in areas such as healthcare, law, and hiring, questions about fairness, accountability, and transparency have become central to public debate.
This paragraph serves as a classic academic introduction. It establishes the general subject (“Artificial intelligence... has advanced rapidly...”) and introduces both the positive (“transformative benefits”) and the negative (“profound ethical concerns”) sides. Academic writing often starts with a wide focus and then narrows to the specific issues. By listing several domains (healthcare, law, hiring) and presenting the central debate (fairness, accountability, transparency), this paragraph prepares the reader for detailed arguments to follow.
Notice how there are no references to previous ideas—no pronouns or linking words (“however,” “therefore,” etc.) that would make it depend on something earlier. This is a sign of an opening paragraph.
It creates the context: readers know what to expect (an exploration of AI’s ethical dilemmas) and are ready for more specific arguments or examples, which should follow directly after.
In real PTE tasks, the first paragraph nearly always sets up the debate or theme in this way.
2nd: (B)
A major challenge lies in the potential for AI systems to inherit or even amplify human biases. For example, if algorithms are trained on historical data that reflects social inequalities, their decisions may reinforce discrimination rather than correct it, leading to unjust outcomes.
This paragraph must logically follow the introduction. It transitions from general debate to a specific ethical problem—bias. The phrase “A major challenge...” signals a shift from the general introduction to a more focused point.
The example (“if algorithms are trained on historical data...”) adds depth and specificity, showing the *mechanism* by which ethical issues arise. Academic passages often move from an overview to a concrete example, as seen here.
There are no references to solutions or responses yet—just presentation of a challenge. This paragraph sets up the need for later discussion of how to address such risks.
Cohesion: The paragraph uses “a major challenge” (not “this challenge”), confirming it is not a concluding or summary paragraph.
Notice the cause-and-effect logic: the problem (bias) and its consequences (unjust outcomes).
3rd: (C)
In response, experts emphasize the importance of transparency and oversight. Making AI algorithms open to inspection and requiring clear explanations for automated decisions can help build public trust and reduce the risk of unintended harm.
The phrase “In response” clearly signals that this paragraph is reacting to something just stated (the bias challenge in B). This is a classic structure in academic English: “problem → solution.”
The first sentence identifies what should be done: transparency and oversight. The following sentence explains the practical methods (open inspection, clear explanations).
By connecting directly to the preceding paragraph, this section builds flow. It wouldn’t make sense as the introduction or conclusion, but perfectly bridges problem and solution.
Notice the reference to “experts”—this links back to the broader academic context set up in A, and advances the discussion from “what is wrong?” to “what can be done?”
Logically, paragraphs about solutions should always follow those describing problems.
4th: (D)
Ultimately, ensuring ethical AI development will require collaboration between technologists, policymakers, and the wider community. By establishing robust ethical standards and accountability mechanisms, society can better harness the benefits of AI while minimizing its risks.
“Ultimately” is a key signpost for a conclusion or summary paragraph in academic writing. The tone becomes broad and forward-looking.
This paragraph summarizes what must be done (collaboration, standards, accountability), and provides a hopeful vision: society can enjoy AI’s benefits while managing its dangers.
The references to “robust ethical standards” and “accountability mechanisms” draw together points from all the previous paragraphs: the need for ethical focus (A), specific dangers (B), and transparency/oversight as a solution (C).
In the PTE Academic, a conclusion often returns to or reframes the ideas in the introduction—here, about maximizing benefit and minimizing risk. It brings closure and encourages reflection.
No new information is introduced here; it’s purely a wrap-up, another clue that it is the final paragraph.
Good academic structure moves from general (A) to specific (B), solution (C), and general (D), giving the passage unity and logical progression.
Key Strategy for Re-order Paragraphs:
Step 1: Always start by finding the introduction—no references to earlier ideas, sets the stage.
Step 2: Next, identify supporting details—usually giving a problem, with or without examples.
Step 3: Find paragraphs with connectors like “In response,” “However,” or “As a result”—these are rarely first or last, but link the story.
Step 4: The conclusion will sum up, use “Ultimately,” “In conclusion,” or “As a result,” and not introduce new issues.
Step 5: Practice often! Each PTE passage follows these core logic rules, even with different topics.
10 Hardest Words from the Passage & Questions
Master these advanced academic words from the AI ethics passage! Each card below shows phonetics, parts of speech, word patterns, clear definitions, usage, synonyms, and typical learner mistakes.
(Hover over each card for a soft blue glow!)
(Hover over each card for a soft blue glow!)
ethical
/ˈeθɪkəl/ (BrE & AmE)
Part of Speech:
adjective
Word Pattern:
ethical issue/problem/concern/standardbe ethical to do sth
Definition:
Relating to principles of right and wrong; connected to what is morally acceptable.
Example:
AI development must address complex ethical questions. (Here, "ethical" means connected to what is right or fair.)
Synonym: moral, principled
Common Mistake: Mixing up "ethical" (about morals) with "legal" (about laws).
transparency
/trænˈspærənsi/ (BrE & AmE)
Part of Speech:
noun (uncountable)
Word Pattern:
transparency in/of sthhigh/low transparency
Definition:
The quality of being open, honest, and easy to understand; not hiding information or methods.
Example:
Transparency in AI algorithms builds public trust. (Means people can see and check how things work.)
Synonym: openness, clarity
Common Mistake: Thinking "transparency" only means physical clearness, not honesty or openness.
accountability
/əˌkaʊntəˈbɪləti/ (BrE & AmE)
Part of Speech:
noun (uncountable)
Word Pattern:
accountability for/toensure/require/demand accountability
Definition:
The responsibility to explain and justify actions or decisions; being answerable for outcomes.
Example:
AI designers must have clear accountability for system failures. (They must answer for mistakes or results.)
Synonym: responsibility, answerability
Common Mistake: Using "accountability" as a verb; it is only a noun.
bias
/ˈbaɪəs/ (BrE & AmE)
Part of Speech:
noun (countable/uncountable), verb (less common)
Word Pattern:
bias against/towards/in favour ofto be biased
Definition:
An unfair preference or prejudice for or against something; in AI, when algorithms produce unfair results due to data or design.
Example:
Biased algorithms can reinforce discrimination. (They produce unfair outcomes.)
Synonym: prejudice, partiality
Common Mistake: Thinking "bias" is always positive; it is often negative in academic contexts.
discrimination
/dɪˌskrɪmɪˈneɪʃən/ (BrE & AmE)
Part of Speech:
noun (uncountable)
Word Pattern:
discrimination againstsuffer/face/prevent discrimination
Definition:
Unfair treatment of different groups of people, often based on race, gender, age, etc.; in AI, when technology treats groups unfairly.
Example:
AI can unintentionally cause discrimination if trained on biased data. (Certain groups are treated unfairly.)
Synonym: unfairness, inequity
Common Mistake: Using "discrimination" for any difference, not just unfair ones.
oversight
/ˈəʊvəsaɪt/ (BrE), /ˈoʊvərsaɪt/ (AmE)
Part of Speech:
noun (uncountable; countable for "mistake" meaning)
Word Pattern:
government/independent oversighthave oversight of/over
Definition:
The process of monitoring and checking actions or systems to ensure they are correct and ethical; also, a mistake made due to not noticing something (context here: supervision).
Example:
Strong oversight is needed to make AI fair and safe. (It means active supervision and review.)
Synonym: supervision, monitoring
Common Mistake: Confusing "oversight" (supervision) with "overlook" (to miss).
robust
/rəʊˈbʌst/ (BrE), /roʊˈbʌst/ (AmE)
Part of Speech:
adjective
Word Pattern:
robust standards/systems/solutionsbe robust enough (to do sth)
Definition:
Strong, effective, and able to deal with difficult conditions or criticism; in policy, means comprehensive and reliable.
Example:
We need robust ethical standards for AI development. ("Robust" means strong and thorough.)
Synonym: strong, sturdy
Common Mistake: Using "robust" only for physical strength; in academics, often refers to ideas, systems, or rules.
reinforce
/ˌriːɪnˈfɔːs/ (BrE), /ˌriːɪnˈfɔːrs/ (AmE)
Part of Speech:
verb (reinforce sth)
Word Pattern:
reinforce the idea/belief/behavior
Definition:
To make a feeling, idea, or behavior stronger or more likely to happen; in AI, to make biases more powerful.
Example:
The algorithm may reinforce unfair stereotypes. (It makes them stronger or repeated.)
Synonym: strengthen, support
Common Mistake: Using "reinforce" for building physical structures only; often used for ideas or behaviors in academic texts.
unintended
/ˌʌnɪnˈtɛndɪd/ (BrE & AmE)
Part of Speech:
adjective
Word Pattern:
unintended consequence/effect/result
Definition:
Not planned or meant to happen; accidental.
Example:
Biased data can have unintended negative impacts. (Negative results happen by accident.)
Synonym: accidental, unplanned
Common Mistake: Using "unintended" for anything surprising, not just what was not planned.
mechanism
/ˈmekənɪzəm/ (BrE & AmE)
Part of Speech:
noun (countable)
Word Pattern:
mechanism for/ofprovide/create/build a mechanism
Definition:
A system or process that enables something to happen or be done; in AI, a way by which an effect or result is produced.
Example:
Oversight mechanisms are needed to monitor AI decisions. (They are systems for checking actions.)
Synonym: system, process
Common Mistake: Thinking "mechanism" always means a physical machine; in academics, often means a process or method.
10 Hardest Phrases & Expressions from the Passage & Questions
Unlock the most challenging phrases and expressions! Each interactive card gives you phonetics, grammar, patterns, definition, usage, synonyms, and common mistakes.
(Hover over each card for a beautiful blue glow!)
(Hover over each card for a beautiful blue glow!)
ethical concerns
/ˈeθɪkəl kənˈsɜːnz/ (BrE) /ˈeθɪkəl kənˈsɝːnz/ (AmE)
Part of Speech:
adjective + noun phrase
Word Pattern:
ethical concerns/issues/questions about + noun
Definition:
Worries or doubts about what is morally right or wrong in a given situation.
Example:
The use of AI in decision-making raises serious ethical concerns. (People are worried about right and wrong choices.)
Synonym: moral issues
Common Mistake: Thinking "ethical concerns" only means "personal preferences," not broader moral debates.
public debate
/ˈpʌblɪk dɪˈbeɪt/ (BrE & AmE)
Part of Speech:
adjective + noun phrase
Word Pattern:
public debate over/about + issue
Definition:
Widespread discussion or argument among many people, especially in society or the media, about a particular issue.
Example:
There is ongoing public debate about AI's role in hiring. (Many people are discussing the issue in public.)
Synonym: societal discussion
Common Mistake: Thinking a "debate" is only in formal settings; it can be any widespread argument.
amplify human biases
/ˈæmplɪfaɪ ˈhjuːmən ˈbaɪəsɪz/ (BrE) /ˈæmpləˌfaɪ ˈhjumən ˈbaɪəsɪz/ (AmE)
Part of Speech:
verb + adjective + noun phrase
Word Pattern:
amplify + bias/problem/concern
Definition:
To make existing prejudices or unfairness stronger, especially through technology or systems.
Example:
Poorly designed AI can amplify human biases in decision-making. (It makes unfairness worse.)
Synonym: increase prejudice
Common Mistake: Using "amplify" to mean "fix" or "remove" instead of "make stronger."
historical data
/hɪˈstɒrɪkəl ˈdeɪtə/ (BrE) /hɪˈstɔrɪkəl ˈdeɪtə/ (AmE)
Part of Speech:
adjective + noun phrase
Word Pattern:
historical data on/of/about + topic
Definition:
Information or records from the past, used as evidence for analysis, especially in training AI systems.
Example:
AI algorithms trained on historical data may repeat past mistakes. (The data comes from earlier times.)
Synonym: past records
Common Mistake: Thinking "historical" means "important"; here it simply means "from the past."
reinforce discrimination
/ˌriːɪnˈfɔːs dɪˌskrɪmɪˈneɪʃən/ (BrE) /ˌriːɪnˈfɔrs dɪˌskrɪməˈneɪʃən/ (AmE)
Part of Speech:
verb + noun phrase
Word Pattern:
reinforce + bias/stereotype/discrimination
Definition:
To make unfair treatment of certain groups more likely or more common.
Example:
If unchecked, AI may reinforce discrimination in hiring. (It makes unfairness continue or get worse.)
Synonym: worsen unfairness
Common Mistake: Using "reinforce" for positive results only; here, it makes a negative stronger.
build public trust
/bɪld ˈpʌblɪk trʌst/ (BrE & AmE)
Part of Speech:
verb + noun phrase
Word Pattern:
build/establish/gain public trust/confidence
Definition:
To make people believe that something or someone is reliable and honest.
Example:
Transparency helps build public trust in AI systems. (People feel safe and confident.)
Synonym: create confidence
Common Mistake: Using "build" only for physical things; here it means to develop a relationship.
unintended harm
/ˌʌnɪnˈtɛndɪd hɑːm/ (BrE) /ˌʌnɪnˈtɛndɪd hɑrm/ (AmE)
Part of Speech:
adjective + noun phrase
Word Pattern:
cause/lead to/result in unintended harm/effect/consequence
Definition:
Negative results that happen by accident, not because someone planned them.
Example:
Lack of oversight can cause unintended harm in AI projects. (Problems that no one wanted or expected.)
Synonym: accidental damage
Common Mistake: Confusing "unintended" with "unexpected"; all unintended effects are accidental, not all are surprises.
in response
/ɪn rɪˈspɒns/ (BrE) /ɪn rɪˈspɑːns/ (AmE)
Part of Speech:
prepositional phrase (discourse marker)
Word Pattern:
in response (to + noun/issue)
Definition:
As an answer or reaction to something that has happened or been mentioned.
Example:
In response to rising concerns, new regulations were proposed. (Used to introduce a solution or reaction.)
Synonym: as a reaction, as an answer
Common Mistake: Forgetting to use "to" when specifying what you respond to.
accountability mechanism
/əˌkaʊntəˈbɪləti ˈmekənɪzəm/ (BrE & AmE)
Part of Speech:
noun phrase
Word Pattern:
establish/create/design accountability mechanism/s
Definition:
A system or process to make sure people or organizations are answerable for their actions or decisions.
Example:
Effective accountability mechanisms reduce the risk of unethical behavior in AI. (They help check responsibility.)
Synonym: control system
Common Mistake: Thinking "mechanism" means only a machine; here, it's a method or system.
harness the benefits
/ˈhɑːnɪs ðə ˈbɛnɪfɪts/ (BrE) /ˈhɑrnɪs ðə ˈbɛnɪfɪts/ (AmE)
Part of Speech:
verb + noun phrase
Word Pattern:
harness + the benefits/power/potential (of sth)
Definition:
To make use of something's positive features or advantages effectively.
Example:
With proper safeguards, society can harness the benefits of AI. (Means to use the good parts of AI in a positive way.)
Synonym: use, exploit (neutral/positive)
Common Mistake: Using "harness" for negative things; it usually means using something useful or powerful in a controlled way.
Interactive Exercise 1: Vocabulary & Phrase Practice
Test your understanding! Choose the best answer for each question. After every choice, you'll see a deep explanation to help you learn.
(Covers the hardest words and phrases from the passage and questions.)
(Covers the hardest words and phrases from the passage and questions.)
Interactive Exercise 2: Words & Expressions in Context
Challenge yourself with new contexts! Each question practices a key word or phrase from the passage. Choose your answer and see a full explanation instantly.
(All 10 hardest items – now in new sentences and real-world examples!)
(All 10 hardest items – now in new sentences and real-world examples!)
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