Summarize Written Text in PTE: Ethical Implications of Facial Recognition

Facial recognition technology (FRT) is a widely discussed topic in the Summarize Written Text section of the PTE exam. This technology has significant implications in various areas, ranging from security and law enforcement to privacy …

Facial recognition technology (FRT) is a widely discussed topic in the Summarize Written Text section of the PTE exam. This technology has significant implications in various areas, ranging from security and law enforcement to privacy concerns. In this article, we present sample PTE Summarize Written Text tasks related to “Ethical Implications Of Facial Recognition,” complete with suggested model answers for different score bands.

Summarize Written Text Task #1: Facial Recognition and Privacy Concerns

Task: Read the following passage and summarize it in one sentence in the box below. Your response has to be between 5 and 75 words.

Facial recognition technology is rapidly becoming a key feature in both public and private sectors to enhance security and convenience, but it has raised concerns about the infringement on personal privacy. Critics argue that the technology, often implemented without individual consent, can be abused for mass surveillance, leading to potential civil liberties violations. Furthermore, instances of bias in the algorithms behind facial recognition can disproportionately impact minority communities and exacerbate societal inequalities. Balancing the benefits and risks remains a critical ethical challenge for governments and corporations alike.

Model Answer for Different Score Bands

Band 90-100:
While facial recognition technology offers benefits in terms of security and convenience, it poses significant privacy and ethical concerns, particularly regarding unauthorized use, the potential for surveillance abuse, and the disproportionate impact on minority communities.

Content: Excellent. The answer includes all major components of the passage—security benefits, privacy concerns, surveillance risks, and societal inequality.
Form: 38 words. Fully complies with the word limit.
Grammar: Perfect. No grammatical issues.
Vocabulary: Excellent. Wide range of vocabulary with precise usage.
Spelling: No errors.

Band 70-80:
While facial recognition technology brings convenience, it raises ethical concerns due to privacy violations and potential misuse for surveillance, with added problems of biased algorithms that negatively affect vulnerable communities.

Content: Very good. Most key ideas are covered, but societal inequality isn’t fully addressed.
Form: 33 words. Well within the allowable limit.
Grammar: Small errors in terms of phrasing (“added problems”).
Vocabulary: Good, but could be more varied.
Spelling: No errors.

Band 50-60:
Facial recognition technology is useful, but its use without consent and risk of bias presents ethical challenges.

Content: Adequate. The answer features some main ideas (usefulness, privacy concerns, and bias) but misses important points such as surveillance abuse and broader societal impact.
Form: 20 words. Quite short, missing details.
Grammar: Acceptable, though somewhat simplistic.
Vocabulary: Limited in range.
Spelling: No issues.

Summarize Written Text Task #2: Ethical Concerns in the Use of Facial Recognition in Law Enforcement

Task: Read the following passage and summarize it in one sentence in the box below. Your response has to be between 5 and 75 words.

The increasing adoption of facial recognition technology by law enforcement agencies has sparked debate over its ethical implications, particularly concerning civil rights. Proponents suggest it aids in identifying criminals quickly and efficiently, making society safer. However, opponents argue that the technology can be misused for unwarranted tracking of citizens and protestors, infringing on freedom of expression and privacy. Additionally, reports have highlighted issues of racial bias in the software, raising concerns over the fair application of these tools. Policymaking on the use of facial recognition technology in law enforcement is still in its initial stages, with lawmakers aiming to strike a balance between innovation and rights protection.

Model Answer for Different Score Bands

Band 90-100:
Facial recognition’s growing use by law enforcement enhances security but raises significant civil rights concerns, particularly around racial bias, privacy infringement, and the potential for misuse in surveillance of protestors, making balanced regulation essential.

Content: Excellent. All key ideas are thoroughly included—security benefits, rights infringement, racial bias, and the need for balanced policymaking.
Form: 41 words. Perfectly within the word count limit.
Grammar: Flawless.
Vocabulary: Strong and precise use.
Spelling: No mistakes.

Band 70-80:
While facial recognition technology helps law enforcement fight crime, it raises concerns regarding privacy, racial bias, and the ethical implications of surveillance, making it essential to establish proper regulations.

Content: Very good. Covers most essential points but lacks specifics about protestors and civil rights in detail.
Form: 29 words. Sufficient, but could be more detailed.
Grammar: Minor simplifications, but no grammatical errors.
Vocabulary: Well-rounded but could include more variety.
Spelling: Error-free.

Band 50-60:
Facial recognition is useful for law enforcement, but it raises questions about privacy and potential misuse.

Content: Moderate. Misses key areas like racial bias and civil rights concerns.
Form: 14 words. Very brief and underdeveloped.
Grammar: Basic, simple structure without complexity.
Vocabulary: Insufficient variety.
Spelling: Correct.

Vocabulary and Grammar

Here are some advanced vocabulary words from the above tasks, along with definitions and examples:

  1. Infringement /ɪnˈfrɪnʤmənt/ (n.) – The action of breaking the terms of a law or agreement; violation.
    • Overuse of surveillance can lead to the infringement of privacy rights.
  2. Bias /ˈbaɪəs/ (n.) – Prejudice in favor of or against one thing, person, or group compared with another.
    • Facial recognition technology has been criticized for racial bias in its algorithms.
  3. Surveillance /sɜːrˈveɪləns/ (n.) – Close observation, especially of a suspected spy or criminal.
    • Mass surveillance has become a major concern with the application of facial recognition.
  4. Civil liberties /ˈsɪvəl ˈlɪbərtiz/ (n.) – Individual rights protected by law from governmental interference.
    • The technology might threaten civil liberties if improperly applied.
  5. Algorithm /ˈælgəˌrɪðəm/ (n.) – A set of rules or a process for solving a problem, especially in computing.
    • Improving the algorithms behind facial recognition is crucial to avoid bias.
  6. Proponent /prəʊˈpoʊnənt/ (n.) – A person who advocates a theory, proposal, or project.
    • Proponents of facial recognition argue for its benefits in combating crime.
  7. Misuse /mɪsˈjuːs/ (n.) – Incorrect or inappropriate use of something.
    • There is a risk of misuse of facial recognition to track innocent civilians.
  8. Protestor /prəˈtɛstər/ (n.) – A person who publicly demonstrates strong objection to something.
    • Facial recognition has been used to track protestors, raising ethical concerns.
  9. Regulation /ˌrɛgjəˈleɪʃən/ (n.) – A rule or directive made and maintained by an authority.
    • Stronger regulations are needed to control the use of this powerful technology.
  10. Disproportionately /ˌdɪsˌprəˈpɔːʃənətli/ (adv.) – To an extent that is too large or too small in comparison with something else.
    • Facial recognition technologies disproportionately misidentify ethnic minorities.

Conclusion

The ethical implications of facial recognition technology, particularly in terms of privacy, bias, and surveillance, are increasingly important topics in both real-world discussions and in the PTE Summarize Written Text section. These issues often appear in PTE tasks, which require a concise summary that covers both the benefits and risks associated with the technology. Practice with these sample tasks and model answers to boost your performance in the exam. Let us know your thoughts in the comments, and feel free to ask for additional practice examples!

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