Tyler Calabrese

I am a second-year PhD student in Boston University's Faculty of Computing and Data Sciences, working with Dr. Allison McDonald. I am a usable privacy researcher with a particular interest in state and workplace surveillance. Previously, I worked as a software developer in the finance industry after earning my BA in computer science and English from Tufts.

You can get in touch with me at tylerjc [at] bu [dot] edu.

My pronouns are he/him.

My resume is available here.

Latest

Nov 12, 2026: Back in college, I TA'd Data Structures for six semesters. I loved it! Recently, the professor reached out to former TAs asking what advice we would give to current students about AI usage. He got what I think he wanted, which was a series of entreaties not to use LLMs to cheat on Data Structures homework. It's a nice read, here. My comment starts on page 6:

First of all, undergrad is HARD. Tufts is an expensive school full of high achievers, and there is a lot of pressure to keep up with your peers, excel at many different things, and eventually get a job that makes it all feel worthwhile. You’re also at the beginning of your adult lives and can’t honestly be sure that anything will work out the way you hope. I am so grateful for Tufts and happy I went there, but I spent my years there very over-extended and anxious about what came next. We can’t know the specifics of what kind of pressures you are under, but I hope that if some of our (my) advice comes from an idealistic place, you can still see that it comes from an informed and sympathetic place, too.

I won’t spend too much time repeating other peoples’ advice who are more in touch with industry life than me, although I wholeheartedly agree a CS degree is about learning bedrock computing concepts, of which code is really just an expression; AI can get in the way of you building necessary and transferable skills; nobody will ever pay you to implement a circular buffer from scratch (sadly) and that’s not why your professors are asking you to do things like this.

What I will say is this: what turns good careers into great careers is figuring out, with increasing specificity, what it is that you care about more than any of your peers. Plenty of successful people in academia and industry are saying things to this effect. AI can’t care about stuff for you. Learning what you care about requires experimentation, attention, serendipity, and play. College is an especially good opportunity for this because you are somewhat insulated from the prerogatives of your future employer. (Not insulated enough, in my opinion, but that’s a conversation for another day.) Getting a little lost in the occasional assignment, naming your variables after Pokémon or your friends, hanging out in office hours, are all part of the point.

As a parting thought, some but not all of you probably have ethical or political qualms of some sort with AI, either specific products or the technology writ large. Frankly, you are adults now and allowing your morals to be a factor in your decisions, both big and small, is part of living a moral life. I’m not saying this from a puritan place. I know you have lots of competing priorities; we live in a society; none of us is perfect and nobody should expect you to be. All I’m suggesting is that you allow it to be a factor.