ChatGPT: Friend or Foe?

CHATGPT
Friend or Foe?
www.upm.edu.my
Assoc. Prof. Ts. Dr. Nurfadhlina Mohd Sharef
Centre for Academic Development (CADe), Universiti Putra Malaysia
Faculty of Computer Science and Information Technology, Universiti
Putra Malaysia
nurfadhlina@upm.edu.my

Assoc. Prof. Ts. Dr.
Nurfadhlina Mohd Sharef
Intelligent Computing Research Group, Faculty of Computer Science and Information
Technology, Universiti Putra Malaysia.
nurfadhlina@upm.edu.my, 0126672504, https://sites.google.com/view/nurfadhlina
Affiliation:
1. Associate Professor, Department of Computer Science,
Faculty of Computer Science and Information Technology,
Universiti Putra Malaysia.
2. Deputy Director (Innovation in Teaching and Learning),
Centre for Academic Development (CADe), Universiti Putra
Malaysia.
3. Task Force Member, National Artificial Intelligence Roadmap
Implementation 2021-2025, MOSTI
4. Task Force Member, Health Workforce Culture Survey
Analytics, MOSTI
5. Interim Research Associate, Malaysia Institute for Ageing
Research (MyAGEING), Universiti Putra Malaysia.
6. Research Associate, Institute for Mathematical Research
(INSPEM), Universiti Putra Malaysia.
7. Secretary, Young Scientist Network-Academy of Sciences
Malaysia (YSN-ASM)
8. Chair, COVID-19 ASM Data Scientist Group, Academy of
Sciences Malaysia, MOSTI
Data Analytics
1. Digitalisation and IoT for Precision Biodiversity
2. COVID19 Vaccination Distribution Planning
and Tracking
3. BSH- LHDNM Analytics Dashboard for
Program Bantuan Kerajaan
4. National Integrated Cybersecurity Threat
Factor Profiling
5. Learning Analytics and Chatbot for
Personalized Learning
Machine Learning
1. Deep Recurrent Q-Network Approach for
Multi Objective Recommendation System
2. Interactive Machine Learning based on Deep
Reinforcement Learning and Generative
Adversarial Network Hybrid for Digital Twin
Research Interests
● Artificial Intelligence
● Data Science and Data Analytics
● Text Mining and Question Answering
● Recommender Systems
● eLearning
Text Mining
1. Online Reputation Meter
2. Evolving Multi-Granular Temporal
Abstraction Method to Improve Clinical
Data Analysis
3. Multi-Tasking based Deep Learning for
Tweets Analytics
4. Deep Attention Model For Review-based
Multi-Criteria Recommendation System
5. Sequence-to-Sequence Based Natural
Answer Generation Models

Centre for Academic Development (CADe)

The fun is to join into the storm
Warm-Up: Play With the Tool
1. Go to https://chat.openai.com/
2. Think about an action that you want to
perform in your lesson. Post an
incomplete sentence or ask it an
explanation
3. What is your observation of its
response? Keep on interacting with it

Go to https://chat.openai.com/chat
1. Ask to create a lesson plan for a
topic
2. Specify that you want to conduct
group work among students
3. If you want the student to self-learn,
what needs to be changed?
4. What tips should you give to them
to complete the work?
5. Generate questions about the topic
6. Make the question harder
7. Change to multiple choice
questions
8. What are the answers to those
questions?
9. Create a rubric for this assessment

7

We now live in GPT era…
1. Go to your app store. Type ChatGPT
2. Scroll to look at the variants of chatting
apps that available

Safe and
responsible
AI
ChatGPT in
teaching and
learning
Opportunities
vs Risks
Introduction to
generative AI
2
3
4
1
CONCLUSION
Outlines

Introduction to
Generative AI

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Can machines think?

can generate new text
based on the input they
receive
“GENERATIVE”
because they are
trained on a large
corpus of text data
before being fine-tuned
for specific tasks
"PRETRAINED"
because they use a
transformer based neural
network architecture to
process input text and
generate output text.
"TRANSFORMERS"
A Generative Pretrained
Transformer (GPT) is a
type of large language
model (LLM) that uses
deep learning to
generate human-like
text.
ChatGPT3 was
announced on
30/Nov/2022.
The magic
of ChatGPT

As the name suggests, generative AI let
computers take existing content, like text,
images, music, speech, code or video,
and create new content.
Generative AI is not a new concept, and
machine-learning techniques behind
generative AI have evolved over the past
decade.
Text ChatGPT Language model
Image DALL-E Image generation including
photos and artworks
Video Wibbitz Create short form video
online in minutes
Speech Replicastudios AI voice actors
for games, film
& the metaverse
Audio Ampermusic Create your own songs and
compositions
16
Generative AI – a game-changer
society needs to be ready for

Supervised fine tune step Mimic human preferences Proximal policy optimization

18

ChatGPT in
Academia

Face filter on TikTok
20

How have you used ChatGPT?
What is your observations?
Have you found any pitfalls?
Open Mic

The use of ChatGPT in teaching and learning
1. Create lesson plans
2. Question answering
3. Text classification
4. Get fresh creative ideas or advise for a refined thought
5. Create rubrics of assessments
6. Translate sentences
7. Compose a write up (e.g social media posts, product
review, promotional copywriting)
8. Summarize text
9. Text completion
10. Get generated text in a particular style (eg a 7-year old
understanding vs 27 years old)
22
You can keep on interacting
with it, ask it to refine and
personalise your request!

Only (a) is
correct, but
ChatGPT got it
wrong, most
probably
because the
logic is wrong.
Both answers
are correct,
and ChatGPT
got it correct
Clustering is an unsupervised learning. Look at the
answer generated. According to the rules of Truth
table, yes ^ no = no. But in ChatGPT the reasoning
needs some work. This is an example how we as a
human educator could tune our way of assessing
students. Rather than asking straight forward fact
(which is lower level of Bloom taxonomy), we could
test their analysis level eg C4
23

ChatGPT can
easily be tricked!
24

ChatGPT can
communicate in
Bahasa Melayu!
25

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ChatGPT understands
dialect!
27

Do you have any recommendations
on how ChatGPT can be used
safely in academia?
Open Mic

The fun is to join into the storm
Ask ChatGPT how can we use it best to
support our teaching

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Guides for educators to embrace ChatGPT in activities
1. Allow students to use ChatGPT and have a discussion on the rules of its usage.
2. Practice retrieval and other memorisation activities that specify certain time, topic or
activities conducted previously to ensure students take effort to understand and analyze any
references they have utilized.
3. Create more collaborative and discussion activities. When students discuss, they do so from
their own working and long-term memory. Sure, they can look up quick answers, but to carry on a
conversation, most of the work comes from their own thinking. After a discussion, students can
recap the discussion and share their reflections about it ... and that's much harder to do with a bot.
4. Emphasize experiential learning and engage students in personalized elaboration that relate to
their local surroundings and routines. Let students demonstrate what they have learnt. Asking
students to bring in ideas, evidence, perspectives, and data from contemporary or personal events
or geographical contexts will make it more difficult (although not impossible) for them to just ask an
AI to write their assignment.
5. Conduct activity that requires students to use ChatGPT to answer questions related to a topic,
and experiment to identify questions that can’t be answered. This will let the students think
critically and dive deeper into the topic. 33

Guides for educators to embrace ChatGPT in
1. Review your assessment; avoid straightforward questions or simple facts. Ask current, complex,
open, real-world problem, and based on a contextual topic or issues discussed in your lesson.
2. Be empowered with AI. Incorporate ChatGPT to personalise or draft a unique case study for
each student or their group based on their interest and level to use in your authentic assessment.
3. Include a section in assessments to let students to critique for improvements (what they got, if it
fits, how to organize it, how to communicate it effectively, etc.) and reflect their synthesis of the
information gathering through their reading, internet searching, peer discussions and ChatGPT
responses they have used and ask them to give their opinions and justifications.
4. Try different assessment types that are more immune to AI and can allow students to develop
and demonstrate understanding such as figurative related, oral assessment and live
demonstration. Additionally, staging assessments, such as requiring students to submit drafts,
receive feedback, and improve their work, are less prone to risk from generative AI.
5. Use ChatGPT to draft quiz questions and possible answers with feedback setting. Use
ChatGPT to generate a draft rubric that you can then refine.
34

ELIZA was one of the first chatterbots (later
clipped to chatbot).
It was also an early test case for the Turing
Test, a test of a machine's ability to exhibit
intelligent behavior equivalent to, or
indistinguishable from, that of a human.
Using "'pattern matching" and substitution
methodology, the program gives canned
responses that made early users feel they
were talking to someone who understood
their input. The program was limited by the
scripts that were in the program.
By today's standards ELIZA fails very
quickly if you ask it a few complex
questions.
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Opportunities vs Risks
38

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AI in education is not new!!

New wave of creativity!
What are the risks?
Try at https://openai.com/dall-e-2/

Are all generative AI reliable?
Meta’s Galactica – a model trained on
48 million science articles with claims to
summarize academic papers, solve
math problems, and write scientific code
– was taken down after less than three
days of being online as the scientific
community found it was producing
incorrect results after misconstruing
scientific facts and knowledge.
41
Meena is a multi-turn open-domain chatbot researched by
Google. It is trained end-to-end on data mined and ﬁltered
from public domain social media conversations.

42

Issues
1. False and misleading content? Disinformation typhoon by generating toxic and biased output, and
internet will be flooded with artwork that is indistinguishable from its original
2. Disruption of labour market. Large parts of the creative workforce, including commercial artists working in
entertainment, video games, advertising, and publishing, could lose their jobs because of generative AI
models. Advertising has the means not only to fund creators but also help those of differing backgrounds
find their careers in the industry. If we (or even our clients without or input) look to robots to create their
work, what does that mean for them?
3. Ethical concerns. The datasets behind generative AI models are generally scraped from the internet
without seeking consent from living artists or work still under copyright. Should the artists who created the
image used to train the AI get paid for this?
4. Authenticity and ownership. Would the art pieces generated by AI be regarded authentic?How about
writing that is composed with the assistance of generative AI? Authors of a publication or an innovation is
usually considered accountable for their writing. Since AI is not an individual, therefore the product should
not be regarded as a valid contribution?
5. Reliability of intelligence. Generative AI systems are only as good as their training data and may
perpetuate biases or even generate and spread misinformation. Evaluation metrics: Sensibleness and
Specificity Average (SSA), perplexity
43

Safe and responsible AI
44

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Humanising and democratising fair and responsible AI
for education
How can AI be leveraged to enhance
education?
How can AI be best exploited for the
common good in education?
How can we ensure the ethical, inclusive and
equitable use of AI in education?
How can education prepare humans to live
and work with AI?

Gartner expects:
● By 2025, 30% of outbound
marketing messages from
large organizations will be
synthetically generated, up
from less than 2% in 2022.
● By 2030, a major blockbuster
film will be released with 90%
of the film generated by AI
(from text to video), from 0%
of such in 2022.
● Generative AI in drug design: predict drug efficacy and side effects
● Generative AI in material science: inverse design, defines the required
properties and discovers materials likely to have those properties
● Generative AI in chip design: reinforcement learning (a machine
learning technique) to optimize component placement in semiconductor
chip design (floorplanning), reducing product-development life cycle time
from weeks with human experts to hours
● Generative AI in synthetic data: which is a class of data that is obtained
from direct observations of the real world without identifying the specific
sources of that data
● Generative design of parts: design parts that are optimized to meet
specific goals and constraints, such as performance, materials and
manufacturing methods
48

Prepare for disruptions!
To ensure safe and trustworthy use of AI:
● Relevant regulations and appropriate requirements on the AI;
● Understanding systems with AI inside;
● Appropriate assurance.
49

How to ensure a safe and responsible AI?
OpenAI are self-governing the space
through limited release strategies,
monitored use of models, and
controlled access via API’s for their
commercial products like DALL-E2
50

The world’s citizens need to understand
what the impact of AI might be, what AI can
and cannot do, when AI is useful, when its
use should be questioned, and how it might
be steered for the public good (UNESCO
International Forum on AI and the Futures of Education
under the theme of Developing Competencies for the AI
Era).
This requires everyone to achieve some level
of competency with regard to AI, including
knowledge, understanding, skills, and value
orientation. Together, these might be called ‘AI
literacy’.
Source:
https://unesdoc.unesco.org/ark:/48223/pf0000380602
2022 51

1. Steer AI-and-education policy development and practices towards protecting
human rights and equipping people with the values and skills needed for
sustainable development and effective human-machine collaboration in life,
learning and work;
2. Ensure that AI is human-controlled and centred on serving people, and that it is
deployed to enhance capacities for students and teachers.
3. Design AI applications in an ethical, non-discriminatory, equitable, transparent and
auditable manner; and monitor and evaluate the impact of AI on people and society
throughout the value chains.
4. Foster the human values needed to develop and apply AI.
5. Analyse the potential tension between market rewards and human values, skills,
and social well-being in the context of AI technologies that increase productivity.
6. Define values that prioritize people and the environment over efficiency, and
human interaction over human-machine interaction.
7. Foster broad corporate and civic responsibility for addressing the critical societal
issues raised by AI technologies (such as fairness, transparency, accountability,
human rights, democratic values, bias, and privacy).
8. Ensure that people remain at the core of education as an implicit part of the
technology design; and protect against automating tasks without identifying and
compensating for the values of current practices.
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53

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54

Tech4FutureLearning Playbook
Scan me to get your copy!
55

Conclusion
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Takeaways
57
1. Generative AI systems have the ability to create new content, such as images, text, or music - they
can produce new ideas or variations on existing ones, which can be very powerful in certain fields like art,
music, and writing.
2. One main risk that is happening right now is that Gen AI can create fake or misleading content, such
as deepfake videos or fake news. For many years also, there are concerns about these systems being
used to automate certain jobs, which could lead to job loss and economic disruption.
3. Gen AI is currently governed by a combination of laws and guidelines, such as copyright laws, and
self-regulation by companies and organizations that develop and use these systems. However, there is
ongoing debate about the best ways to regulate and govern this technology. There is no specific law
governing the ways to create AI and how it impacts others negatively.
4. It's definitely going to grow smarter, faster, and more pervasive. Not in years but in months! The road
ahead for generative AI is likely to involve continued growth and development of these systems, as well as
increased research into how to use them safely and responsibly. As the technology improves, it may
become more widely used in a variety of fields, and it will be important to continue to monitor and
address any risks that may arise.

Guide for educators
As an educator, it is important to have a general understanding of artificial
intelligence and how it can be used in education. Here are a few key points
to consider:
1. AI can be used to personalize learning experiences for students, by
adapting to their strengths, weaknesses, and learning style.
2. AI can be used to assist with grading and providing feedback on
student assignments.
3. AI can be used to create interactive and immersive learning
environments.
4. It is important to be aware of the potential ethical implications of
using AI in education, such as issues of algorithm bias and user
privacy.
5. As AI continues to advance and become more widely used in
education, it is important for educators to stay up-to-date on
developments and best practices for incorporating AI into their
teaching.
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References
https://www.gartner.com/en/articles/beyond-chatgpt-the-future-of-generative-ai-for-enterprises
https://www.weforum.org/agenda/2023/01/davos23-generative-ai-a-game-changer-industries-and-society-code-developers/#:~:text=As%20the%20n
ame%20suggests%2C%20generative,evolved%20over%20the%20past%20decade.
https://www.lbbonline.com/news/dai-advertising-in-the-chatgpt-era
https://medium.com/geekculture/chatgpt-what-is-it-and-how-does-it-work-exactly-62e7010524d3
https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcTgdR2UCbWFoV54h16EFcImHYCOL1P26hYL0Q&usqp=CAU
https://daleonai.com/transformers-explained
https://ai.googleblog.com/2020/01/towards-conversational-agent-that-can.html
https://web.njit.edu/~ronkowit/eliza.html
https://lablab.ai/blog/generative-ai-in-action-real-world-applications-and-examples
https://www.weforum.org/agenda/2023/01/how-to-trust-systems-with-ai-inside
https://www.nytimes.com/2023/01/24/learning/lesson-plans/lesson-plan-teaching-and-learning-in-the-era-of-chatgpt.html
https://chat.openai.com/chat
https://www.teachingprofessor.com/topics/teaching-strategies/teaching-with-technology/chatgpt-or-how-i-learned-to-stop-worrying-and-love-generati
ve-ai/?cb=9704394&cac=3804439
https://ditchthattextbook.com/ai/
https://educational-innovation.sydney.edu.au/teaching@sydney/how-can-i-update-assessments-to-deal-with-chatgpt-and-other-generative-ai/
https://educational-innovation.sydney.edu.au/te
https://www.assemblyai.com/blog/how-chatgpt-actually-works/
https://lifearchitect.ai/chatgpt/
https://towardsdatascience.com/beginners-guide-to-the-gpt-3-model-2daad7fc335a
https://www.springboard.com/blog/data-science/machine-learning-gpt-3-open-ai/
61

THANKS!
www.upm.edu.my
Nurfadhlina Mohd Sharef
nurfadhlina@upm.edu.my

ChatGPT: Friend or Foe?

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