Brain dump alert, just a heads up, you might get bored and I know half of you reading this won't even finish reading this write up :(
Recently, I have been reflecting on why I want to pursue a PhD, especially at a time when artificial intelligence is advancing at an unprecedented pace.
After my first internship at a big tech company, I began telling a few friends that I was considering pursuing a PhD. One of the most common responses I received was whether a PhD would remain relevant given the rapid development of artificial intelligence or should I say super intelligence haha!
It is a question I have thought about myself.
With AI systems becoming increasingly capable of performing tasks that once required years of human training and expertise, what will the future of research look like? Will there still be a need for people to spend years investigating problems that intelligent systems might eventually solve in minutes?
Well spoiler alert, I believe there will be!
As these systems become more capable, new challenges will emerge, particularly concerning their safety, reliability, interpretability, and impact on society. Developing increasingly intelligent systems is one thing; ensuring that these systems do not harm the people they are intended to serve is another.
I believe humans still have an important role to play in understanding, evaluating, and guiding the development of these technologies.
However, there are moments when I question what these advancements mean for learning itself.
Recently, while studying partial derivatives for my Calculus III examination, I came across news about OpenAI models solving increasingly sophisticated mathematical problems. I remember thinking about the contrast between my own experience, spending hours trying to understand mathematical concepts :( , and the capabilities of systems that can solve problems far beyond what I am currently learning.
It made me wonder: What is becoming of learning?
Does learning certain concepts still matter when machines can already perform the tasks we are learning to do? What will education look like in a world where artificial intelligence continues to outperform humans in increasingly complex intellectual tasks?
I do not think the answer is to stop learning. In fact, I believe these advancements make it even more important to understand fundamental concepts rather than simply rely on the outputs of intelligent systems.
But I am still trying to understand how the purpose of learning might change.
Everything seems to be evolving so quickly, sometimes faster than we can fully comprehend its implications.
Amid these uncertainties, I have also been reflecting on what genuinely motivates me to pursue a PhD.
I am a deeply curious person, I mean i can be lazy at times ngl :(
For me, pursuing a PhD represents an opportunity to go beyond surface-level understanding and immerse myself in questions that do not necessarily have straightforward answers. There is something fascinating about investigating a concept deeply, questioning existing assumptions, and potentially discovering something that contributes to our collective understanding.
It is difficult to explain the excitement I feel about the possibility of contributing something novel to a field.
I do not want to spend my entire career simply consuming the products of other people's research.
I want to contribute. I realize the amount of I's i have used in alarming, hold me accountable people :(
Through my experiences building AI-powered applications and studying the internal mechanisms of language models, I have become increasingly interested in understanding not only what these systems can accomplish but also why they behave the way they do.
I want to investigate the mechanisms behind their capabilities, their limitations, and the risks associated with their deployment.
More importantly, I believe that as a computer scientist, I have a responsibility to think about the people whose lives these technologies will affect.
According to the 2025 AI index report, 84% of people living in the world do not use AI yet. Now let us use this analogy, Imagine a child somewhere in the world (an underdeveloped country for instance), studying under the light of a candle, no constant electricity, who is unaware of the extraordinary technological transformations happening elsewhere in the world.
By yours truly, artist Lucid Dame :) Call me Da Vinci or Claude Monet, fellas. I clearly missed my calling haha! 🎨
On a more serious note that child may not have access to the latest AI systems or opportunities to participate in their development, but the decisions made by researchers and technology companies today could eventually shape the world they inherit.
I think about the responsibility we have to ensure that technological progress does not come at the expense of people who have little influence over its direction.
I want to contribute to building a future where intelligent systems are not only powerful but also safe, reliable, accessible, and beneficial to society.
Perhaps this is one of the strongest reasons I am drawn to AI safety research.
I recognize that I am still at the beginning of this discovery journey. There are many things I do not understand, and I am still exploring the specific questions I want to dedicate myself to investigating.
I do not know exactly what the future of artificial intelligence will look like.
I do not know how much the research landscape will change over the next five or ten years.
But I know that I want to understand these changes rather than simply watch them happen.
And if I have the opportunity to contribute, even in a small way, to ensuring that these technologies create a safer future for others, I believe that would be meaningful work.
Perhaps pursuing a PhD, for me, is not about having all the answers. It is about being willing to spend years asking questions that matter.
Hmmm, if you got this far, there is hope for the Generation Z after all :)