Capstone Begins

    Who am I?

    I started college in 2008. I was 18, a senior in high school. I can vividly remember sitting in the library of the local community college, watching the later parts of the Great Recession meltdown while timidly eating a sandwich. My favorite course that semester was in chemistry, but I was already obsessed with history. I doubt I knew how privileged I was, or how much that privilege was about to be challenged.

    A year later, I got a full scholarship to a liberal arts college. I had the run of majors, with an exciting honors program based in the study of the cultures of southern and eastern Europe. If you can’t tell, I’m a definite humanities nerd. I wasn’t particularly impressed with the chemistry department at Houghton College, not meaning any offense to them. My chemistry professor from the community college is still one of the top three teachers I’ve ever studied with. However, my history professors were the tough but fair type, and I thrived in their introductory courses.

    Of course, the world was in the middle of burning cash, if not metaphorically, at least digitally. For a world that was, to use Francis Fukuyama’s phraseology, at the end of history, history was still definitely happening. By the time I was ready to graduate, the key players of the past fifteen years were in place. Government debt and resentment towards the banks for the bailouts. A libertarian resurgence. The Tea Party. Vladimir Putin and his imperial ambitions. The Arab Spring. When these pieces were thrown into the almighty whirlwind of human society, we ended up with dramatic events such as the stagnant wage crisis of the 2010s and, eventually, the election of Donald Trump. Don’t worry, this isn’t a political blog, but I’m telling a story and any story set in the US between 2015 and 2022 needs to mention Donald Trump.

    I graduated in 2013 bursting with potential. I’d applied for and been accepted into graduate school, but my advisors dissuaded me. The economic and social costs were too great, they said. They all wished they had gone into other fields, instead of what felt like a slowly crumbling academic edifice in the humanities. They counseled me to publish a paper or two (I have one, still a proud achievement) and see where the world lay in a few years. They counseled me to go to law school.

    But as you can tell, I somehow ended up in computer science. That’s the real story, the one I’m working towards. You see, as I was about to graduate, in fact, as I was working on that one article I published, I went over to a friend’s house. He was a computer science major and he had spent the past two semesters working on the very early stages of the AI boom. He was working with Twitter sentiment analysis, which at the time was relatively cutting edge. And suddenly I realized that the problems I was trying to solve over in the history department, problems about causality and relationships and power dynamics, could actually be solved automatically. It seemed magical! Aim a dataset at a computer, see what it spits out, bam! Answer achieved!

    This is not how it works. My level of understanding of computer science has come along a bit since then and, even now, I’m uncertain we could accomplish the type of projects I envisioned then. The paucity of historical sources combined with the uniqueness of each source combined with the known historical and AI bias problems all make historical machine learning still challenging. But I was sold. I wanted to get my hands on that tech.

    Now, this is not a linear story. I got a job as an elementary school teacher, eventually. After a few years doing that, I decided to move into tech. The teaching market was short on funding, long on abuse and saturated with burnout. I still had visions of writing some sort of grand historical thesis using machine learning. I figured it couldn’t be too hard, so I started teaching myself how to program.

    Since I’m now graduating from OSU’s computer science course, this self-taught route obviously didn’t work. It was more a matter of focus than anything else. Earning a living always took a priority and without coursework, deadlines and other people, I was lost. Thus, eventually, in 2020, I signed up for OSU. The courework at OSU has helped me focus in on an actual interest in computer science for itself. I remain deeply interested in the idea of machine learning for history, but I’m now also interested in algorithm efficiency, secure computing, and parallelism for their own sake’s. I’ve been given the gift of double interests and double undergraduate expertise.

    What am I doing?

    With that background in mind, I looked at the project list for this final capstone course. My humanities brain kicked into gear when I saw the list. It was a tyranny of choice problem, certainly, since most if not all of the projects looked extremely interesting. I had to balance any number of factors. Some seemed to play to my education background, such as the AR popup book. Some played to my interests in machine learning. And of course there were the ones related to climate change and firefighting that played to my altruistic idealism.

    I’m actually more interested in producing something usable and useful than in producing something impressive. This is why at the top of my list were the two firefighting projects. Not to say that these projects wouldn’t be impressive, but I meant that they are using existing technology to solve real world needs. I’m considering getting a masters degree in Data Science, but even then I don’t really expect to advance the computer science field. But a real world project that actually helps people solve a concrete problem appeals to me.

    I also applied for the AI Coder project. To be honest, I have mixed feelings about ChatGPT-* and the like. I love playing around with the technology and the emergent behaviors are very exciting. That being said, there are some definite pitfalls, for society and for individual users. I don’t see replacing software engineers with AI as being very helpful for the end users, but I do see it as being fantastically enriching for the shareholders. However, I’m excited to have an always-on assistant for idea generation. The actual code being produced has to be really improved, such as by measuring efficiency or by requesting greater use of one-liners. It’s coding with supervision. I would like, moreover, to flesh out some of those ideas. If permitted, I’d like to use ChatGPT for all of my coding assignments and work in the future, but only because I’d like to focus on optimizing and enhancing the code.

    Group Projects

    This is a natural time, then, to consider this specific group project we’re about to be working on. I’m not sure I fit any one role, but I know what roles I prefer to avoid. I am not a natural frontend developer. I love usability studies, I should clarify, and I like the actual wireframing/page layout part of frontend. But I find client programming and especially Javascript very frustrating. So I’m not sure I’m a “Contributor”, in the sense of, “whatever needs doing, I’m willing to do”. I am definitely a “Collaborator”. I function best in a project with clearly defined goals and clearly defined responsibilities. I like code reviews and continuous integration so I know I’ve “completed” something. I find test-driven development to be a major salve to anxiety about whether what I’ve programmed is “good enough” for this very reason.

    I like working in a project management role and would like to move my career in that direction at about the mid career point. So in that sense I guess I’m a “Leader”, but I definitely do not like the role of setting deadlines or expectations unless I’m actually in charge. So, for this group project, as the instructors and TAs are the “managers”, I’d prefer to help organize but don’t want to be a team lead. Overall, I’m probably best described as a Collaborative Planner, where I like to plan a project out but also like bouncing ideas off people and changing the plan to incorporate better ideas.

    I’m not particularly worried about working in groups, as it seems the students who made it this far are good at programming and hold up their end of the group projects. I will be insisting on spending time on the early parts of the software development lifecycle, though, as us technical people tend to delve into implementation way too quickly. I also want a continuous integration workflow with code reviews. This really helps me be certain about where we’re going and forces a sort of collaboration that negates the loneliness of online learning.

    Overall, I’m excited for this class and to graduate!

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