When My Way of Thinking Got Formatted by Code
First of all, if you haven’t done this yet and are looking through my post, I suggest using the second link (this is the second link) and logging in with nyu email for free access.
I also recommend reading The I in the Internet by Jia Tolentino (link). Both articles have a similar vibe and discuss the transition of the internet from a wonderful place to a toxic one. However, The I in the Internet delves deeper into the reasons behind these phenomena.
For me, the way I manage my daily tasks is deeply influenced by the logic of computational media. Every day, I rely on to-do list apps and Google Calendar to break down my day into executable steps. Each task becomes a node in a larger network, and my entire schedule resembles a directed graph that maps out what I need to do and when to do it. Even if I were to lose access to these tools, my mental structure would continue to follow this logic—breaking complex goals into smaller tasks, organizing them by priority, and executing them sequentially.
In essence, this is computational thinking: breaking complex objectives into smaller, manageable parts and applying a systematic approach to complete them. Computational media redefined my perception of “efficiency” as I now see tasks as modular components that can be adjusted, re-prioritized, and tackled one by one.
Similarly, my approach to social interactions has also been influenced by this systematic mindset. As an introvert, I often rely on pre-prepared scripts and strategies to communicate. The frequency of sending messages, the choice of topics, and the timing of responses are carefully considered, just like an algorithm aimed at reducing friction. Computational media encourages me to think in terms of patterns, routines, and optimization strategies.
However, this systematic approach comes with its own cost: spontaneity and genuine emotional engagement are sometimes constrained by the “rules” I have set for myself. Just as a computer program follows its coded instructions, I find myself adhering to these scripts, and my approach makes interactions feel more like simulations rather than true human connections. Computational systems have a tendency to systematize and format even the most natural of experiences.
Algorithmic filtering mechanisms have a profound impact on how we perceive reality. For example, my Twitter feed is almost devoid of political content because I have deliberately blocked it out. I click “Not Interested” on all politically related posts. However, this self-curation is far from perfect: I’ve noticed that my timeline is filled with a large number of memes and shitposts because I frequently interact with them (liking, downloading, and url sharing through other apps).
So interestingly, in trying to avoid one type of content, I have inadvertently optimized my feed for memes. This reveal to me that what influences the content of my feed is not my stated preferences, but my behavior patterns, and if you think about it, it’s not even surprising because for computational medias what we see is not based on autonomous choices but on feedback loops and data-driven optimization. In other words, the active and passive coexist, with the passive often overpowering the active.
One of the most compelling characteristics of computational media is its ability to break away from the constraints of linear narratives. A piece of music I really enjoy, Random by Silentroom & Sobrem, is originally composed for a game, and has a unique structure: at a critical point (1:45), the song can branch into eight different random variations based on the player’s input (the video shows the default one). As the player, you are no longer a passive listener but an active participant in the creation of the music. The variations at the track’s climax are unpredictable, and the final presentation depends on the interaction between the listener and the game.
Without computational media, this kind of interactive experience would be impossible. It represents a new form of narrative where the user’s choices influence the story’s development. Computational media transforms narratives from fixed paths into flexible networks of possibilities. Media experiences are no longer confined to consuming a single, author-defined version but are about exploring randomness co-determined by input and interaction.
The flexibility of computational media also has a darker side: the echo chamber effect and what I call idiot resonance. One of the biggest issues with information bubbles is that they can amplify certain perspectives to the extreme. In the past, an idiot might have been isolated in a village of a few hundred people. But now, through the power of computational media, the idiots in LA, the idiots in NYC, and the idiots in Shanghai can all come together, supporting each other, amplifying each other’s viewpoints, and forming an ultimate idiotness, a more extreme kind of bias or ignorance, and make you, an innocent person who happens to pass by, become so confused about the strength and volume of those idiots.
Like-minded individuals reinforce each other’s perspectives within their information bubbles. The more they interact, the more their beliefs are validated, and the stronger their echo chamber becomes. We are fed content that matches our behavioral data, reinforcing existing beliefs rather than challenging them. The promise of computational media was to offer a more informed, connected society, but in some ways, it has made us more fragmented and polarized.