Gen Z Speaks: I started an AI interest group in school. Working with humans — not computers — was the bigger challenge

Before the days of ChatGPT and Midjourney, I remember a time when the field of artificial intelligence (AI) was regarded as a buzzword for automating mundane tasks away.
Perhaps it wasn’t seen among my peers as being on the cutting edge. In my first year at Nanyang Polytechnic (NYP) in 2020, most of the tech interest groups were mainly related to app development and cybersecurity. 
AI was not something that could compel enough students to want to start a collective of like-minded individuals. 
Simply put, there wasn’t much interest in an AI interest group. 
But as a 19-year-old who has been devoted to the pursuit of AI and machine learning, I knew that this was a field that would blow up not just in popularity but also importance.
The human mind is so complex in its intricacies and it is a considerable achievement that medical science has been able to understand how it works. The next bound was for a machine to replicate what our brain does. 
The possibilities are endless, as the public is now starting to discover with tools like ChatGPT.
So, encouraged by my lecturers who taught us to think innovatively and out of the box, I had a wild idea to start an AI interest group in NYP.
I have to admit: I was somewhat worried that I did not have enough content to share with people who would join this group, or that my technical knowledge in AI was still limited.
Little did I expect that the greatest challenge in forming a collective of interested students wasn’t the machines, it was in trying to decipher the human connection.
I have always been interested in technology and artificial intelligence (AI) since I was a child, thanks to my father, who holds a computer science degree.
And as a family, we bonded over sci-fi movies and series such as The Matrix and Black Mirror and geeked out on technological advances in the news.
Stuff like the Smart Nation Initiative that the Government launched in 2014, which doesn’t often make for conversational material among people in my cohort, was something my dad, my older brother and I discussed voluminously about.
Our dinner talk often revolved around how the latest tech would change our daily interactions and experiences. 
We would discuss and debate the impact of artificial intelligence (AI) on robotics, the latest advances in machine learning, and the exciting future ahead as machines begin to pick out patterns and predict our actions. 
As I got older, my brother, who was studying for his diploma in cybersecurity and digital forensics at NYP’s School of Information Technology, continued to fuel my interest through his daily post-school recaps.
I still dearly remember these conversations that played such a formative part in my childhood.
But there remained one unanswered question of how one would set about teaching a lifeless machine to make sense of the world and make autonomous decisions, possibly surpassing human intelligence.
So, hungering for an answer, I paid the library a visit one Thursday afternoon while waiting for my O-Level results and borrowed a book titled Machine Learning Fundamentals, which was published by Packt Publishing. 
Reading it was a revelation that kickstarted my passion in the field of AI, and what also helped was being further exposed to tech through programming Lego Mindstorms and creating games using the Alice programming environment.
But my thirst for knowledge, as well as the influence of my father and brother made me want to pursue a career in information technology. So, I followed my brother’s path in NYP, securing an education in IT at NYP that would give me the rigorous academic experience I desired.
As it turns out, NYP’s IT diploma programme had indeed surpassed all expectations I had. 
I was given full rein to explore my interests and further them with opportunities like competitions, internships and extracurricular programmes. I could always feel my lecturers’ passion for the subject in their slides and lectures, and they never failed to address all the quips I had about the industry.
It was also with their encouragement that I decided to start an AI interest group at school for other like-minded students. 
But the initial months were the toughest phase.
My first tasks: I needed to learn how to write a proposal, pitch an idea, and convince others that learning AI was a worthwhile endeavour. 
How do I articulate this massive train of thought into a one-liner? Why would anyone be convinced to be a part of this? Where could I find members to join my executive committee? 
Beyond that, I had many concerns and doubts swirling around the top of my head.
While there were online materials and how-to guides readily available, I found many of them challenging for beginners to understand. 
I wanted to create content from scratch, from the eyes of a regular polytechnic student, so my peers and seniors could relate to it.
I was glad my family was very supportive when I shared the idea with them, with my dad and brother giving me valuable advice. 
Especially my brother, who also had experience starting an interest group in NYP. He taught me the basics, from organisational structure to developing a proposal.
What also helped was that my classmates and lecturers were by my side too, providing me with necessary feedback, even joining me for brainstorming sessions for my proposal, which I had to revise thrice before submitting it to the school.
In June 2020, NYP AI was launched as the first AI interest group among all polytechnics in Singapore.
But the challenges didn’t end there, as I had to make sure the group was productive and achieve the goals that the executive committee and I had set out.
I still vividly recall our first event: A “beginner-friendly” project that used AI to predict housing prices. I had spent hours creating the slides and done multiple rehearsals to ensure that everyone could understand my sharing.
I soon realised that my way of teaching could be overwhelming and confusing for some participants. 
At some point, I thought I was not cut out to teach — I was too dull and serious of a teacher. 
However, as NYP AI’s committee team grew and received more participant feedback, I learnt creative ways to infuse interactivity into our events.
Getting student interest was another hurdle we had to tackle. We relied heavily on word-of-mouth, our blog, schoolwide email blasts and our social media for publicity. 
However, it wasn’t enough — we were not seeing growth in numbers.
It was disappointing. For all the effort we’d put into creating the content, we wanted to reach out to a greater student population. Was NYP AI too niche, or were we not cut out to run an interest group?
Our recognition increased as we adapted our teaching styles to be more approachable. Hosting events frequently definitely created visibility for us.
From 30 members, we grew to 150 members in three years and continue to get larger.
As we adapted and found new solutions to our problems, I thought that this is exactly what I like about AI and machine learning.
Learning from experience is at the core of AI and my whole experience came full circle. My growth as an individual charting the unknowns in human relationships mirrored that of a machine making sense of the world.
My greatest takeaway? It is to let go of fear, which is the core hurdle of every passion project. Do the task, because even if you fall, you will still fall forward. 
NYP AI would have remained a vision if I had not taken the leap of faith, it wouldn’t be a reality if I had surrendered to my fears and doubts.
Looking back, this project turned out to be a humbling and meaningful experience for me. Witnessing my schoolmates’ “Aha!” moments when they finally understand an AI concept is enough to put a smile on my face. It makes the road taken worthwhile.
ABOUT THE AUTHOR:
Alex Chien is a 19-year-old graduate from the Diploma in Information Technology at Nanyang Polytechnic’s School of IT. He’s also awarded the Lee Kuan Yew Award for Mathematics and Science for his outstanding achievements at his recent graduation.