My Last Year as an Undergrad: Finding Uniqueness in the AI Era

The Existential Dread

I believe the way we collaborate with each other, and the way we manage the machines and software around us, is going to change dramatically now that AI is part of the picture. That realization sat with me as I prepared for my own transition from undergrad into research life.

I think the core task of a researcher is to explore uncertainty and make discoveries in service of goals and interests — whether they’re your own, or ones you’ve aligned with the institution you’re part of. Coming to terms with that shift, from executing known tasks to sitting with the unknown, is part of what this past year has been about.

The Shift in Value

For most of undergrad, I believed my value was tied to execution — how fast I could build something, how perfectly I could format it. The more experience and knowledge I gained, the better I thought I could understand human behavior and get ahead in every part of my life.

But I’ve come to realize execution only accounts for maybe 20% of the value I actually bring. The other 80% is about collaboration — understanding the people I’m working with and reading the situation we’re in together. That’s the part an AI can’t replicate. It can take over most of the execution side, but it can’t “read the air” (空気を読むこと) — understand the unspoken context inside a social interaction and make a decision based on it.

The “Aha” Moment

The moment I realized I wanted to work in HCI came during a project with an e-commerce platform. The team was studying user behavior online and trying to model it to improve product recommendations. I remember being surprised by how much of what I’d learned across school could suddenly become useful across such different parts of a company — I could feel my analytical mind, my engineering mind, and my design mind all coming together to help the company reimagine and redesign its story, both for internal strategy and for the actual experience of sellers and buyers.

What struck me even more was how powerful it was to bring the voice of the customers we’d interviewed into internal discussions. Their feedback genuinely reflected the gap between how the operations team believed they were doing and how customers actually felt — and seeing that feedback help the team figure out how to make things better, regardless of what role someone held on the platform, was the moment I knew this was the kind of work I wanted to do.

Asking vs. Answering

Learning to ask better questions is something you have to practice daily — nobody can pretend to know something they don’t, so asking is a discipline for yourself as much as it is a way of working with AI. Right now, AI isn’t omniscient; it doesn’t have full context on a given situation, so we’re the ones who have to supply that context. Asking a good question is essentially how you prompt an AI with your own ideas so it can actually help guide you using what it knows.

AI already has access to far more knowledge than any of us, and it can retrieve it far faster. That’s exactly why asking is more important than answering — most answers are already searchable, and an AI will often know them more precisely than I do. What isn’t searchable is the right question to ask in the first place.

Your Unique Mix

I have a background that blends different disciplines — industrial design, HCI, and more — and I don’t think that’s unusual anymore. Society itself is moving in that direction: technology is integrating the different parts of our lives into a whole, rather than keeping them divided the way work was split up after the industrial revolution.

I think of it like farmers before machinery: they built their own tools, cooked their own food, studied their own crops, calculated their own profit, and built and ran their own households — all as one integrated way of living, before industrialization pulled those pieces apart into separate roles. Technology now seems to be pulling them back together, and our whole communities are becoming part of that integration.

That’s where I think my own “taste” comes from. Because my background spans multiple disciplines, I can connect what I’m seeing now to something I’ve worked on before, or a conversation I’ve had with someone else, and draw on more patterns to make sense of problems I’m not familiar with. It gives me the ability to work through unfamiliar problems and then translate what I’ve found into language I can actually explain to a partner, a client, or a friend.

Advice to My Past Self

Looking back, I don’t regret the decisions I’ve made — even with all the room for improvement, and all the disappointments along the way. If I could tell my freshman self one thing, it would be to trust what you already believe and stay confident in it.

I’ve always had a bit of an FOMO streak — wanting to grab every opportunity in front of me, afraid of losing my chance. But not every opportunity is actually the right fit for you, and that’s a lesson worth learning earlier rather than later.