ENG1503
ASSIGNMENT 2 SEMESTER 2 2025
UNIQUE NO. 737611
DUE DATE: 17 SEPTEMBER 2025
, Introduction
Large language models (LLMs) such as ChatGPT are powerful tools that generate
fluent text through large-scale data processing. However, their rise has provoked
important debates about plagiarism, authorship, and academic honesty. This essay
argues that using outputs from LLMs does constitute plagiarism when they are
presented without proper acknowledgment, since the generated content is not
original human creation. I will present three reasons to justify this stance and propose
three strategies that universities can adopt to preserve the credibility of their
qualifications in the era of AI.
Plagiarism and the Use of LLMs
Plagiarism is the unacknowledged use of another’s ideas or expressions. While LLMs
can produce convincing essays, they do not “think” or produce original insights; rather,
they predict patterns from vast training datasets (Naithani, 2025). If students pass such
outputs as their own work, they misrepresent machine-generated text as original
authorship.
Reasons for My Stance
1. Lack of Original Authorship
Cyphert (2024) observes that LLMs do not innovate but recombine pre-existing material.
Submitting their text without attribution constitutes plagiarism because it falsely
attributes originality to the student.
2. Absence of Moral Right to Attribution
Naithani (2025) highlights the author’s moral right to attribution. When students fail to
ASSIGNMENT 2 SEMESTER 2 2025
UNIQUE NO. 737611
DUE DATE: 17 SEPTEMBER 2025
, Introduction
Large language models (LLMs) such as ChatGPT are powerful tools that generate
fluent text through large-scale data processing. However, their rise has provoked
important debates about plagiarism, authorship, and academic honesty. This essay
argues that using outputs from LLMs does constitute plagiarism when they are
presented without proper acknowledgment, since the generated content is not
original human creation. I will present three reasons to justify this stance and propose
three strategies that universities can adopt to preserve the credibility of their
qualifications in the era of AI.
Plagiarism and the Use of LLMs
Plagiarism is the unacknowledged use of another’s ideas or expressions. While LLMs
can produce convincing essays, they do not “think” or produce original insights; rather,
they predict patterns from vast training datasets (Naithani, 2025). If students pass such
outputs as their own work, they misrepresent machine-generated text as original
authorship.
Reasons for My Stance
1. Lack of Original Authorship
Cyphert (2024) observes that LLMs do not innovate but recombine pre-existing material.
Submitting their text without attribution constitutes plagiarism because it falsely
attributes originality to the student.
2. Absence of Moral Right to Attribution
Naithani (2025) highlights the author’s moral right to attribution. When students fail to
