Cover image by Quentin Grignet
Welcome to 2025: A More Human Update
I'm a bit late to the "Welcome 2025" party, but I haven't published a post in a while, and it's been even longer since I wrote something personal about myself. So, I'm glad to be writing this now.
Writer's block
Sometimes I want to write, but other times I wonder, "What's the point?" Despite my efforts to remind myself, I often forget that writing is most beneficial for me. I also need to recall a quote on my wall that, in modern terms, suggests that if my words can help even one person understand something better, then it is not a waste of time at all. After recently telling someone how much her blog posts have helped me realise things about myself, it feels even more silly. But, hey, compartmentalisation can be tricky.
I'm trying to allow myself to write more casually again. It's tough since I tend to explore complex topics that are hard to address without using specific terms. But when talking about myself and life experiences, it's easier to drop all of that and sound a little more like I do when I'm typing a message to a friend in a chat application. (What? You don't think I'm a pedant who types like this, even casually?)
Anyway, I digress. Let's get to it. Here are some random thoughts from the world of this random human on earth.
AI or human?
One thing I've been struggling with a little is the name of my blog. With how much LLMs have been taking over the internet, I now sit in a strange area where my blog title gives the impression that my posts are all written solely by an AI. But as they aren't, it feels misleading.
A large language model (LLM) is a machine learning model designed to understand and generate language. Machine learning is a branch of artificial intelligence that trains computers to learn patterns and make predictions based on data instead of following explicit programming. LLMs are trained on vast amounts of text data and have many parameters but often lack true understanding and context. Many LLMs, like OpenAI's ChatGPT, are generative pre-trained transformers (GPTs). However, they don't always provide reliable or accurate responses and can be easily influenced by specific prompts, which raises concerns about their reliability.
Alternatively, I could slap my "Not By AI" badge somewhere on the site from https://notbyai.fyi and call it a day, but this still requires visitors to mentally go through an extra step.
On the other hand, I just really like this name and don't want to change it.
It's a nod to the intersection of technology and humanity—a play on the question of whether androids dream, inspired by Philip K. Dick's novel Do Androids Dream of Electric Sheep? Just as that book explores the blurred lines between the artificial and the real, I aim to examine the often unnoticed influences shaping our perceptions and lives.
Even though changing it might be more practical, I feel like my current name still represents me and where I'm at. So, perhaps it is something to think about for another time. The LLMs won't be going away anytime soon, anyway.
Finding a voice
I've done a couple of talks at work now, if being interviewed as though I'm on a talk show can count among them. Doing so, I find that I do actually enjoy talking to people about things that interest me. However, a thing that makes a big difference is the reaction of the audience. I felt the people who asked questions were genuinely curious about the answers. At no point did it ever feel like a battle to defend myself, even though I'm sure not everyone agreed with my beliefs—they were just curious to know what I thought. But, then again, these conversations were about games, which much of society doesn't take very seriously. If we had been talking about history or political economy, things indeed could have turned out differently!
I also briefly introduced game theory for one of these talks, which was fun. I made a web app to accompany the talk and make it more visually interesting. To make it a bit more relevant, I tied it to the customer churn we're talking about at work and added a bonus section on gamification as a solution to ensuring continued customer engagement.
As I'm clearly outspoken against dark patterns and the consequences of gamification and exploitative tactics in games, explaining gamification techniques and methods to others is something that I find to be very important. While I wasn't in a great position during that talk to really get into the dangers of gamification, I still managed to slip in a few indications that it's not all positive.
Problems big and small
It's not a new revelation or anything of the sort, but it's been pretty clear that one of my primary motivators is solving problems. The problems don't have to be preventing something. For example, I like playing city-builder games to solve mini logistics puzzles and games with tactical combat for similar reasons. I also enjoy finding a better way to stack my dishes or lay out furniture and items in a room in my apartment. No matter how small, the problem-solving aspect is satisfying.
But the best part about these things is the restrictions. The complete freedom to do anything makes finding a solution very difficult. Where are the constraints? Even in a literal sandbox, I'm somewhat confined by the medium, and trying to reach the limits of that confinement is what can really make building structures in the sand all the more interesting.
Another simple constraint is colour in furnishing and decorating the apartment. If I hadn't set an accent colour for each room before I started, everything would have been black, shades of grey, and white or silver. (The white would only be there because the walls are such a colour, so I have to balance out the black furniture against the white walls. We live in a small enough space that painting the walls darker is generally ill-advised. But, then again, we should prioritise our own comfort, shouldn't we?)
So, where am I going with this? Nowhere, really. Screw needing a neatly wrapped conclusion, sources, and measurable results for every topic!
2024 in three words
To wrap things up, I thought about what three words I would use to describe the year we recently left behind. It was surprisingly easy to come up with these:
Eventful: It was a long year in which many things happened, from pleasant social events with my partner and friends to my personal learnings and workplace achievements.
Reflective: I've continued to hone in on what kind of person I want to be, what I don't want to be, and how I want to contribute to those around me.
Evolutionary: I feel like I've grown a lot in many different ways. I chose "evolutionary" because time will tell whether everything is to my benefit, and evolution is the same—it doesn't always result in the most optimal or effective outcomes.