My first interaction with artificial intelligence occurred when I was a kid: playing video games. Whether I was chatting with NPCs to complete a quest or playing online checkers against an “opponent,” the computer acted as a kind of digital companion.
But my deeper introduction came later in college while studying computer science. In 2018, during my senior year, I took an “Intro to AI” course, where I learned to write programs that could solve problems autonomously. I built a Sudoku solver that could complete puzzles on its own and programmed a Pac-Man game, where my intelligent Pac-Man navigated the maze, collecting coins while avoiding ghosts. And while, in retrospect, it was a rudimentary introduction to the vast world of AI, it taught me how “knowledge” can be represented in a computer, how a system thinks.
The core ideas are still there, but obviously AI has evolved significantly in the last seven years — especially in the realm of image generation. To be honest, I initially shared the general public’s skepticism. I kept my distance, wary of its implications. Seeing how some people were using generative AI tools like DALL-E or Midjourney — inputting prompts to generate surreal (and at many times visually “muddy”) images trained on web-scraped content, without artists’ consent — only solidified my stance. It felt like an emerging artistic landscape where speed and quantity were prioritized over intentionality and craftsmanship. I worried that the world of creative technology would be reduced to a handful of controversial platforms.
I’d tell people, “I make art with code,” and many would assume it was AI art, that a computer was doing most of the work. It felt invalidating, like I had to prove myself as a new media artist. I felt like I needed to justify my process, explaining that I actually spent years studying the fundamentals of visual design, or that I’d spend hours sketching ideas on paper and then twice the amount of time meticulously translating them into code, carefully shaping the logic that would bring them to life.
So, I refused to use AI in my work because it felt like “cheating.” I held tightly to my tried-and-true methods of creative coding, afraid of being seen as someone lacking vision or skill — someone who relied on a computer to do the creative parts for them.
But it’s important to remember: Humans are tool makers — and yet, we’ve always been averse to the very same tools we’ve made, in much the same way art critics were critical of cameras when they were first introduced, because they thought photography took less skill.
My perspective on AI has shifted in the past year — specifically from recognizing the difference between AI as a tool for mass production versus its intentional use in experimental or self-referential art (see: Refik Anadol’s 2022 exhibit at the MoMA). I believe the art world is opening up to the idea of AI, so long as it’s done in a thoughtful way. There’s a difference between an artist using AI to see their vision through versus the computer’s idea of what it should be. The perspective must come from the artist. Even so, there are still those so turned off by AI, they’ll dismiss your work even if they ultimately agree with your core message.
Another major factor that contributed to my change of heart was experimenting with AI in my own practice. To give some context, I’m interested in integrating cultural practices within technology — and not just how to make technology more accessible and equitable, but also the ways we see ancestral, indigenous knowledge reflected in computation.
When I came across the Dogon tribe of Mali in my independent research, I was struck by their ancient understanding of astronomy and the parallels between their knowledge systems and modern technology. At the same time, I also found myself drawn to the craft of indigo dyeing native to West African cultures — particularly how it allowed women to build capital and gain independence. I saw these ideas reflected in modern day, where technology can also create new forms of autonomy and agency. Inspired by the parallel between these worlds, I took archival blueprint images of telescopes and blended them with traditional indigo textiles using AI. In doing so, I combined indigenous ideas with modern computing, exploring how technology can serve as both a bridge to the past and a tool for future-making.
I completely understand the fears surrounding AI — and many of them are valid. It’s already changing industries, and I’ve seen it firsthand in my work as a software engineer. When I ran into a technical problem, I could upload my code into a chatbot, and it would generate a solution in seconds — something that might have taken me days to figure out on my own. And while that shift can feel unsettling, I believe the best approach is to focus on learning how to work with AI rather than just solely fearing it. These tools aren’t truly autonomous; there will always be a need for human oversight, creativity, and critical thinking.
From an engineering perspective, the only thing I can do is learn. It’s not — and it shouldn’t be — competition at this point. It’s not me versus AI; it’s co-creation, the NPC assisting me in my quest. That mindset extends beyond software engineering and into my art practice as well. It’s about bringing my vision, strengths, and values to the work while staying in conversation with the computer. As Nina Simone once said, “An artist’s duty is to reflect the times in which we live.” AI is part of our present reality, and engaging with it thoughtfully allows me to shape its role in my creative process rather than letting it define the work for me.
The reality is, we’re not going back to a world without AI. I understand why people are critical of it, but I also believe that outright rejecting it means missing an opportunity to shape its role in ways that align with our values. AI is already becoming a part of our daily lives, and the best way to ensure these technologies remain accessible and ethical is for all people — especially artists — to be part of the conversation. Engaging with AI doesn’t mean blindly accepting it; it means actively participating in how it evolves.
That begins with digital literacy: understanding how AI actually works, honing critical thinking skills, and doing your own independent research on technology. It also means ensuring diverse perspectives — from artists to underrepresented groups — are part of the conversation so these systems don’t reinforce existing power structures but instead foster inclusive innovation. Otherwise, the future will be shaped by a narrow, homogenous tech elite — a reality we should challenge, not accept.
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