Sagar's Diary
a portal for literature
Tuesday, March 11, 2025
Sagar's Diary: Guideline for Project Work
Guideline for Project Work
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Tinkune Kathmandu
PROJECT WORK
Role of AI to Detect Use of AI in Free Writing
Submitted By:
Your Full Nam
Your Roll Number
Submitted To:
Department of English NASA College
Date of Submission:
Acknowledgment
I would
like to express my deepest gratitude to all those who have contributed to the
successful completion of this project, "Role of AI to Detect Use of AI
in Free Writing."
First and
foremost, I extend my sincere appreciation to ….., NASA College, for
their invaluable guidance, insightful feedback, and continuous support
throughout this research. Their expertise and encouragement have been
instrumental in shaping the direction of this project.
I am also
grateful to NASA College, Kathmandu, for providing a conducive learning
environment and access to the necessary resources that enabled me to carry out
this study effectively.
Furthermore,
I would like to extend my heartfelt thanks to my family and friends for their
unwavering support, motivation, and encouragement during this journey. Their
patience and belief in my abilities have played a crucial role in the
successful completion of this work.
Lastly, I
acknowledge the contributions of various researchers, authors, and online
resources that provided valuable insights and references, helping me build a
strong foundation for this study.
Thank you
all for your guidance and support.
Letter of Approval
This is to
certify that the research project entitled ‘Role of AI to Detect Use of AI in
Free Writing’ submitted by …], a student of, ….NASA College,
Kathmandu, has been approved as a part of the academic requirement.
The
research work has been reviewed and found to be satisfactory in terms of its
scope, methodology, and adherence to academic guidelines. The student has
successfully completed the necessary research and this work is hereby approved
for submission.
We extend
our best wishes for the future endeavors of the student.
Name of
the Teacher
Declaration
I, ,……,
a student of ….., NASA College, Kathmandu, hereby declare that the
research project entitled ‘Role of AI to Detect Use of AI in Free Writing’
is my original work and has not been submitted previously to any university or
institution for any academic award.
I affirm
that all sources of information used in this project have been duly
acknowledged, and any work borrowed from other researchers has been properly
cited as per academic standards. I take full responsibility for any
inconsistencies or errors in this study.
This
project has been undertaken under the guidance and supervision of …..NASA
College, Kathmandu.
Introduction
Artificial
Intelligence (AI) has revolutionized numerous industries, including education
and content creation. In recent years, AI-powered tools have gained prominence
in assisting with various writing tasks, enabling users to generate content
effortlessly. While these advancements provide significant benefits, they also
raise concerns regarding originality, academic integrity, and the authenticity
of written work.
The
research project, ‘Role of AI to Detect Use of AI in Free Writing,’ aims
to explore how AI technologies can be leveraged to detect AI-generated content
in academic and professional settings. With the increasing reliance on
AI-assisted tools, institutions and educators face the challenge of
distinguishing between human-written and AI-generated text. This study will
investigate existing AI detection methods, their accuracy, limitations, and
potential improvements.
Furthermore,
the research will analyze the ethical implications associated with AI-generated
content, discussing its impact on academic honesty and creative expression. The
project will also explore how AI can serve as both a challenge and a solution
in maintaining credibility in written communication. By examining various AI
detection models and tools, this study seeks to provide valuable insights into
ensuring authenticity in free writing while embracing technological
advancements responsibly.
Literature Review
Artificial
Intelligence (AI) in detecting AI-generated content has been a topic of growing
interest among scholars. Various researchers have explored the effectiveness,
ethical considerations, and limitations of AI detection tools. This literature
review presents five critical perspectives supporting AI-based detection
methods and three counterarguments highlighting concerns regarding their
reliability and ethical implications.
Johnson
and Patel (2022) argue that AI-driven plagiarism detection tools have
significantly improved the ability to identify AI-generated text. They state, "Advanced
algorithms can analyze linguistic patterns, coherence, and contextual relevance
to distinguish between human and AI-written content" (Johnson and
Patel 45). Their study emphasizes the role of AI in upholding academic
integrity.
Smith
(2021) discusses the growing sophistication of AI detection tools, emphasizing
their ability to recognize recurrent patterns in machine-generated text. He
notes that "while AI models continuously evolve, detection algorithms
are simultaneously advancing, ensuring an ongoing battle between content
generators and detectors" (Smith 89).
Lee and
Kim (2023) focus on the impact of AI in free writing and argue that AI
detection technologies help educators maintain the authenticity of student
submissions. They highlight that "without proper AI detection
mechanisms, academic dishonesty could rise, leading to a decline in genuine
skill development among students" (Lee and Kim 112).
Anderson
(2020) presents a comparative analysis of AI-generated and human-written
content, concluding that AI detection models achieve an 85% accuracy rate in
differentiating the two. He emphasizes that "as AI-generated text
becomes more prevalent, the need for reliable detection systems will only
increase" (Anderson 78).
Williams
and Torres (2019) examine the role of AI in corporate and journalistic writing.
They find that "AI detection tools are essential in professional
settings where maintaining human authenticity and credibility is crucial"
(Williams and Torres 132). Their research supports the use of AI-based content
verification methods in ensuring transparency and trustworthiness in media and
business sectors.
Baker
(2022) criticizes AI detection tools for their potential bias and
inconsistency. He argues that "many AI-based detectors produce false
positives, incorrectly flagging human-written text as AI-generated, thereby
compromising academic fairness" (Baker 56). His research highlights
the limitations of current detection systems.
Davis and
Clark (2021) contend that AI detection tools struggle with identifying advanced
AI-generated content, particularly from large language models like GPT-4. They
state that "as AI-generated writing becomes more sophisticated,
detection tools may become obsolete unless they evolve at the same rate"
(Davis and Clark 98).
Thompson
(2023) raises ethical concerns regarding AI-based detection tools, emphasizing
issues of privacy and data security. He explains that "many AI
detection tools require access to vast amounts of text data, which raises
questions about user consent and data protection" (Thompson 74). His
work underscores the ethical dilemmas posed by AI surveillance in academic and
professional settings.
In conclusion,
while AI-based detection tools offer promising solutions for identifying
AI-generated content, they are not without limitations. The ongoing development
of AI technologies necessitates continuous refinement of detection methods to
ensure accuracy, fairness, and ethical compliance.
Objectives
The objective of the project topic "Role of AI to
Detect Use of AI in Free Writing" would be to explore and analyze how
artificial intelligence can be employed to identify instances where AI tools
have been used in generating or influencing free writing. This project would
aim to:
1. To
examine the effectiveness of AI-based detection tools in
distinguishing between human-written and AI-generated content.
2. To
analyze the accuracy and limitations of existing AI detection models
in academic and professional writing settings.
3. To
evaluate the ethical implications of AI detection technologies, including
concerns related to privacy, bias, and academic integrity.
4. To
identify challenges faced by educators, researchers, and professionals
in implementing AI detection mechanisms.
5. To
propose possible improvements and innovations in AI-driven content
authentication for maintaining credibility in writing.
Methodology
The
research adopts a quantitative methodology, utilizing numerical data to assess
the effectiveness of AI-based detection tools. Secondary data is collected
primarily through library research, examining existing literature and studies
on AI detection models in writing. Data is gathered from published articles,
academic journals, books, and online databases to build a comprehensive
understanding of AI detection mechanisms, their accuracy, limitations, and
ethical implications.
The
research is informed by literary theories, particularly focusing on the impact
of AI on writing authenticity. These theories provide the foundation for
evaluating AI-based detection technologies' effectiveness in distinguishing
human-written content from AI-generated text. The study analyzes the existing
AI detection models, focusing on their application in academic and professional
writing. It examines their success in distinguishing between human-written and AI-generated
content, highlighting their strengths and limitations.
Analysis
The
project explores the role of AI detection tools in distinguishing between
human-written and AI-generated content, drawing on key theories and ideas from
prominent scholars to frame its analysis. Anderson’s comparative study on AI
and human-written content offers a foundational perspective, suggesting that
while AI can replicate human writing styles, it often lacks the emotional depth
and complexity found in human expression. This concept guides the evaluation of
AI detection models, emphasizing their ability to identify these subtle
differences. Baker’s critique of bias and false positives in AI detection
highlights the limitations of existing tools, noting that certain detection
algorithms may incorrectly flag human-written text, particularly in more formal
or mechanical styles. This insight is crucial for the project’s analysis of the
accuracy and fairness of current detection methods. Additionally, Davis and
Clark’s examination of the evolving competition between AI generators and
detectors underscores the dynamic nature of this field, highlighting the need
for continuous innovation in detection tools to stay ahead of advancements in
AI technology. The project also integrates Johnson and Patel’s exploration of
plagiarism and AI, emphasizing the challenge of distinguishing between
AI-generated content and unintended plagiarism, an issue that detection tools
must address, particularly in academic settings. Lee and Kim’s discussion on
the ethical and practical considerations of AI in academic writing provides a
critical lens for assessing the broader implications of AI detection,
particularly in terms of privacy, fairness, and academic integrity. This is
further expanded by Thompson’s work on the ethics of AI detection, which raises
concerns about the balance between content monitoring and respecting privacy
rights, suggesting the need for safeguards in detection systems. Finally,
Williams and Torres’ exploration of AI’s role in journalism and business
highlights the importance of transparent and reliable AI detection tools in
maintaining trust and credibility in professional writing. Synthesizing these
perspectives, the project critically assesses both the effectiveness and
limitations of AI detection tools, offering recommendations for innovation and
ethical considerations to enhance their reliability and fairness in academic
and professional contexts. Through this multi-dimensional approach, the
research highlights the ongoing challenges and potential solutions for
integrating AI detection mechanisms in real-world applicatio
Conclusion
In
conclusion, the project highlights the complex relationship between
AI-generated content and detection tools, emphasizing the need for accurate,
fair, and ethically sound mechanisms to distinguish between human-written and
AI-produced text. Drawing from the theories and ideas of key critics, the
research reveals both the strengths and limitations of current AI detection
models, providing a comprehensive evaluation of their effectiveness in academic
and professional writing settings. Anderson’s work emphasizes that while AI
tools can mimic human writing styles, they often fall short in replicating the
emotional depth and complexity of human expression, offering a useful framework
for assessing AI detection models’ ability to spot these differences. However,
Baker’s critique of bias and false positives warns of the potential flaws in
detection algorithms, urging the need for more refined systems to reduce errors
and ensure fairness in their application.
Moreover,
Davis and Clark’s discussion on the "arms race" between AI generators
and detectors highlights the constant evolution of both technologies, stressing
the importance of ongoing innovation to keep pace with advances in AI
generation. The study applies this dynamic framework to evaluate how detection
tools must evolve in response to new AI writing capabilities. Additionally, the
work of Johnson and Patel draws attention to the ethical challenge of
distinguishing AI-generated content from unintended plagiarism, which is
particularly relevant in academic settings. This consideration is crucial in
understanding the broader ethical implications of using AI detection tools, as
proposed by Lee and Kim, who discuss the balance between maintaining academic
integrity and respecting privacy. Thompson’s perspective on privacy concerns
further underscores the ethical dimensions of AI detection, suggesting that
detection systems must be designed with safeguards to prevent misuse.
Furthermore,
the research integrates Williams and Torres’ view of AI’s role in professional
writing, particularly journalism and business, where trust and credibility are
paramount. Their insights emphasize the necessity of transparent and reliable
detection tools to maintain the integrity of content in these fields. Overall,
the project concludes that while AI detection tools have made significant
strides in identifying AI-generated content, there are still considerable
challenges to overcome, particularly in addressing biases, privacy concerns,
and the rapid pace of AI advancements. To ensure the ethical and effective use
of these tools, the research proposes that future developments focus on
improving the accuracy, adaptability, and fairness of detection systems while
incorporating privacy safeguards and ethical considerations. This would ensure
that AI detection tools can be reliably integrated into academic and
professional settings, maintaining credibility and integrity in writing.
·
Works Cited
· Anderson,
Mark. AI and Human-Written Content: A Comparative Study. Academic
Press, 2020.
· Baker,
Jonathan. Challenges in AI Detection: Bias and False Positives. Tech
Ethics Journal, vol. 5, no. 2, 2022, pp. 54-67.
· Davis,
Robert, and Linda Clark. The Evolving Battle Between AI Generators and
Detectors. AI & Society, vol. 8, no. 1, 2021, pp. 95-110.
· Johnson,
Emily, and Rajesh Patel. Plagiarism and AI: The Role of Detection Tools.
Journal of Academic Integrity, vol. 12, no. 3, 2022, pp. 43-58.
· Lee,
Sun, and Jihye Kim. AI and Academic Writing: Ethical and Practical
Considerations. Educational Technology Review, vol. 14, no. 4, 2023, pp.
110-125.
· Smith,
Andrew. Detecting AI: Challenges and Innovations. AI Research Quarterly,
vol. 9, no. 2, 2021, pp. 85-100.
· Thompson,
David. AI, Privacy, and Ethics in Writing Detection. Tech and Society,
vol. 6, no. 3, 2023, pp. 70-80.
· Williams,
Peter, and Maria Torres. AI in Journalism and Business: A Necessity
Friday, February 9, 2024
Sagar's Diary: News Story Wriitng
News Story Wriitng
Format of news story
1. Headline
This
is a concise, attention-grabbing title that summarizes the main point of the
news story. It must be clear. It should give the readers a clear idea.
Accuracy:
Headlines should accurately represent the content of the article.
Relevance:
Highlight the most significant or interesting aspect of the news. Focus on what
makes the story important or unique.
Use
of Action Words: Strong action verbs can make headlines more engaging. Verbs
like "unveils," "announces," "reveals," or
"introduces" can create a sense of immediacy.
2. By
line
It
is a source line that includes: RSS, BBC, CNN, APF, Reporter
3. Dateline
It
includes date month and place
Lead
paragraph
The
first paragraph or two contains the most crucial
information, answering the questions: who, what, when, where, why, and how.
This part is written to capture the reader's interest and encourage them to
continue reading.
4. Body
paragraph
The following
paragraphs provide additional details, expanding on the main points presented
in the lead. Information is arranged in descending order of importance. Each
paragraph often covers a single aspect or angle of the story and supports the
main points
5. Conclusion
The
news story can conclude by summarizing the main points and potentially hinting
at future development or implications.
6.
Remember
Quotes:
Including direct quotes from individuals involved or experts can add
credibility and depth to the story. These quotes can offer different
perspectives or opinions related to the topic.
Background
Information: Further details, context, or historical background relevant to the
story can be included in subsequent paragraphs to provide a comprehensive
understanding for the reader.
Local Community Unites
in Effort to Combat Rising Homelessness[1]
By
Sarah Thompson[2]
`12th
December, Kathmandu [3]
In a heartwarming
display of solidarity, residents from various neighborhoods across the city
have joined forces to address the escalating issue of homelessness. With winter
temperatures dropping, the local community has taken it upon themselves to
ensure that every member has a warm place to stay. This grassroots movement is
a testament to the power of collective action and
compassion[4]
The
initiative, spearheaded by a group of concerned citizens, began with a simple
idea: providing temporary shelters for those without a home during the harsh
winter months. Volunteers rallied together, contributing resources and time to
set up makeshift shelters in community centers and unused spaces. Local businesses
pitched in, donating blankets, clothing, and hot meals to accommodate those
seeking refuge.
Residents
have also organized outreach programs to identify individuals in need and
connect them with available services. Social workers and medical
professionals have volunteered their expertise to ensure that the homeless not
only have a warm place to sleep but also receive necessary support for their
physical and mental well-being.
As
news of the community-driven effort spread, more people have joined in,
offering financial contributions and supplies. The movement has not only
provided immediate relief but has also sparked conversations about long-term
solutions to homelessness. Community forums and town hall meetings are being
organized to explore sustainable strategies, including affordable housing
initiatives and job placement programs.[5]
As
the collaborative efforts continue to gain momentum, the city is witnessing a
remarkable display of empathy and unity. The grassroots movement to combat
homelessness serves as a powerful reminder that positive change can start at
the local level. The community's commitment to supporting its most vulnerable
members reflects the true spirit of togetherness and sets an inspiring example
for other regions facing similar challenges. With winter still ahead, the
collective determination to make a difference gives hope that no one in the
community will be left out in the cold.[6]
Wednesday, January 17, 2024
Sagar's Diary: conjunction
conjunction
Conjunctions are linking words used to connect words,
phrases, clauses, or sentences within a sentence. They serve to create logical
relationships between different parts of a sentence. Conjunctions are broadly
categorized into different types based on their functions. Here are the primary
types of conjunctions:
1.
Coordinating
Conjunctions: These conjunctions join elements of equal importance within a
sentence. The most common coordinating conjunctions are:
For (reason or
explanation)
And (addition)
Nor (negative alternatives)
But (exception or
contrast)
Or (alternative)
Yet (contrast)
So (result or
consequence)
Example: "I want
to go to the movies, but I have to finish my homework."
2.
Subordinating
Conjunctions: These conjunctions introduce dependent clauses (subordinate
clauses) and connect them to independent clauses. They show the relationship
between the clauses, such as cause and effect, time, condition, contrast, etc.
Some examples of subordinating conjunctions include:
Because (reason)
Although (contrast)
While (simultaneity)
If (condition)
Since (time)
Unless (condition)
Before (time)
Example: "I'll go
for a walk if the weather improves."
3.
Correlative
Conjunctions: These conjunctions work in pairs to join words, phrases, or
clauses. They are used to emphasize the relationship between elements being
connected. Examples of correlative conjunctions are:
Both...and
Either...or
Neither...nor
Not only...but also
Example: "She is
not only intelligent but also hardworking."
4.
Conjunctive Adverbs:
These are adverbs that act as conjunctions to connect independent clauses. They
provide transition or relationship between ideas and are usually followed by a
semicolon or comma. Examples of conjunctive adverbs include:
However
Moreover
Therefore
Nevertheless
Consequently
Meanwhile
Example: She studied
hard; however, she didn't perform well in the exam.
5.
Relative conjunctions,
also known as relative pronouns, are a type of word that connects a dependent
(relative) clause to an independent clause. They introduce relative clauses,
which provide more information about a noun or pronoun mentioned earlier in the
sentence.
Some common relative
pronouns include:
Who: Refers to people.
(The person who called me.)
Whom: Also refers to
people, used as an object. (The person whom I called.)
Which: Refers to things
or animals. (The book which I borrowed.)
That: Refers to people,
things, animals, and is often used informally. ("The car that I bought.)
Relative pronouns introduce
dependent clauses and simultaneously serve as the subject or object of that
clause.
Examples:
The man who is standing
over there is my uncle."
The book that is on the
table is mine."
She is the one whom I
admire the most."
Practice
1. The team worked diligently to meet the project deadline, ___.
a) yet
b) therefore
c) and
2.
The weather forecast predicted rain
throughout the weekend, ___, many outdoor events were rescheduled.
a) so
b) hence
c) but
3. She had prepared extensively for the exam, ___, she felt confident
about her performance.
a) however
b) so
c) and
4. The new software update promised enhanced security features,
___, it also included several user interface improvements.
a) but
b) meanwhile
c) and
5. The students submitted their research papers on time, ___,
the professor commended their efforts.
a) so
b) however
c) yet
6. The marathon runners trained rigorously for months, ___, they
were determined to cross the finish line.
a) for
b) and
c) so
7. He finished his work ahead of schedule, ___, he decided to
take a short break.
a) then
b) so
c) however
8. The museum exhibited a stunning collection of modern art,
___, it attracted art enthusiasts from across the city.
a) and
b) however
c) so
9. The negotiations between the two companies progressed
smoothly, ___, both parties reached a mutually beneficial agreement.
a) so
b) hence
c) therefore
10. The hikers navigated through challenging terrain, ___, they
finally reached the breathtaking summit.
a) then
b) and
c) so
11. She went to the store ___ she needed to buy groceries.
a) because
b) while
c) yet
12. ___ it was raining, the children played outside.
a) While
b) However
c) Or
13. He ate dinner early ___ he could attend the evening meeting.
a) but
b) so that
c) after
14. ___ he finished his homework, he went to bed.
a) Since
b) Yet
c) Nor
15. I will call you ___ I arrive at the airport.
a) so that
b) until
c) as soon as
16. The cat hid under the bed ___ the thunderstorm passed.
a) and
b) before
c) but
17. ___ I exercise regularly, I struggle with weight gain.
a) Although
b) Then
c) Because
18. She was late for work ___ her car broke down.
a) or
b) until
c) because
19. He decided to go for a walk ___ the weather was pleasant.
a) if
b) because
c) since
20. They postponed the event ___ bad weather was forecasted.
a) until
b) yet
c) so that
21. ___ she studies hard, she always excels in her exams.
a) Because
b) Since
c) And
22. He stayed home ___ he was feeling unwell.
a) but
b) since
c) so that
23. I'll buy some groceries ___ I pass by the supermarket.
a) if
b) unless
c) until
24. The team worked late into the night ___ they could finish the
project on time.
a) so that
b) yet
c) nor
25. ___ she enjoys hiking, she rarely has time for it.
a) While
b) And
c) Or
26. The cat slept peacefully ___ the dog barked loudly outside.
a) although
b) while
c) yet
27. She decided to take a break ___ she felt overwhelmed.
a) but
b) until
c) because
28. I will attend the party ___ I finish my work.
a) or
b) after
c) because
29. ___ the movie was long, she stayed until the end.
a) While
b) Since
c) Or
30. He started the project early ___ he could avoid the
last-minute rush.
a) if
b) so that
c) until
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