Around the Web 35
Everything is a Game 🎲
My Other Publications:
Check out my latest AI newsletter: ε Pulse: Issue #22
Watch my latest short video essays on my YouTube Channel.
Here is one:
Others:
(For books I have read, reviewed, or currently read, go to the end of the newsletter)
In this newsletter:
[Talking Points]
⌨️Story of VueJS
👯 Twins Baby Boom
🪙US: No More Pennies?
🇰🇷Seoul: Marry, Take Cash.
📺YouTube is the New Tele.
🪖Latest Commandos Origin Game.
📰New York Times Approve AI-use.
[Long Reads/Watch]
[I]: 🎲Why Everything is Becoming a Game
Gurwinder’s brilliant essay examines how modern society increasingly employs gamification—a strategy rooted in B. F. Skinner’s behaviorist experiments with pigeons—to control human behavior by making everyday activities into games. By offering immediate, unpredictable, and conditioned rewards, this method shifts our focus from intrinsic values to extrinsic metrics, effectively turning our lives into score-driven systems. Though Gurwinder didn’t mention it in his essay, at the heart of it all of this, is mimetic desire, as a major driver.
The essay traces the origins of gamification from Skinner’s laboratory work, where he discovered that pigeons pecked more persistently for immediate and random rewards, to its evolution into a widespread tool in consumer and corporate environments. Early experiments demonstrated that conditioned reinforcers, such as a simple click or badge, could manipulate behavior more effectively than primary rewards, laying the foundation for modern applications.
Gurwinder details how gamification has permeated various sectors—from loyalty programs and employee management to social media platforms where “likes” and notifications serve as modern-day status symbols. This shift has redefined our societal values, leading us to prioritize quantifiable achievements over meaningful, long-term fulfillment. The essay highlights examples like social credit systems in China and the addictive design of dating apps and fitness trackers that subtly condition behavior for commercial and political gains.
Ultimately, the essay warns that while gamification promises immediate satisfaction and order, it often leads to a hollow existence defined by fleeting wins rather than true progress. Gurwinder urges readers to be discerning about the "games" they play, advocating for choices that emphasize long-term, positive-sum, and intrinsically rewarding pursuits, thereby reclaiming control over our lives and resisting the seductive pull of superficial metrics.
The essay will take you about 35 minutes to read, if you have that long to spare, I strongly recommend reading it. The idea/minute spent reading it is quite high. It articulates the problem of modernity. It’s probably the best thing I have read this year.
[II]: 💡How to Prepare for the Intelligence Age
This conversation between Jonathan Bi and Tyler Cowen offers a very rich exploration of the implications of AI, focusing on its impact on innovation, economic competition between the US and China, and the future of knowledge work. Re: DeepSeek, Cowen's insights challenge conventional wisdom, such as the belief that US sanctions effectively stifle Chinese technological advancement. He argues that restrictions, like the ban on high-end AI chips, can actually stimulate innovation by forcing China to innovate frugally. Cowen's analysis extends beyond the geopolitical landscape. He paints a picture of a future where AI radically reshapes the workforce, potentially leading to a greater divide between those who can effectively utilize AI tools and those who cannot (I suppose that goes without saying, a pronounced Matthew Effect of some sort). He also touches upon the psychological and societal challenges posed by rapid technological advancements, highlighting the difficulty in comprehending and responding to the pace of change. I, for example, write an AI blog to keep up with this stuff; and I must say, it’s not for the faint of heart. But I see the writing on the wall: the productivity gain from embracing these tools is huge. I have many internal protocols that just allow me to do so much more for the past 2 years.
One particularly compelling aspect of the conversation revolves around the future of writing and knowledge creation. Cowen discusses how AI is already surpassing human capabilities in certain domains, such as answering complex (academic) questions and generating different kinds of creative text formats. In this context, Cowen emphasizes the importance of cultivating a unique voice and style in writing. He believes that as AI becomes more proficient at generating generic content, human writers will need to focus on incorporating their personal experiences, insights, and styles to differentiate themselves. While I see the point Cowen is making here, I think he might be underestimating how pervasive and powerful this technology is. For example, I do know of creators, such as Varun Mayya, who have been using his AI clones to 10X is output. But I do agree that the uncanny valley is a thing, maybe not so much of a big deal if folks like Varun literally have millions of followers. There was a quick chat too about the future of academia (On this topic, I recommend reading this blog by another economics professor: in brief, research will be overrated in the age of intelligence) The conversation ultimately leaves me with a sense of both the immense possibilities and the potential challenges that lie ahead in an era defined by increasingly powerful AI.
[III]: 📿Hidden History of Early Christian Art
I very much enjoyed watching this 45-minutes video essay partly because I am new to the whole business. Here, Harmony explores the fascinating history of early Christian art and its connection to Jewish traditions. The speaker posits that the first icon was actually the Ark of the Covenant, emphasizing its role as a prefiguration of Christ. The video discusses Jewish practices of using objects like mezuzah and phylacteries, which contained scripture and were believed to offer protection. These practices, the speaker argues, demonstrate a belief in the power of symbols to connect with the divine, a belief that carried over into early Christian art.
The video essay traces the development of Christian iconography, suggesting that it originated with Gentile converts who adapted their custom of making images of saviors to include Christ and his Apostles (this was news to me). The essay concludes by highlighting the continuity and discontinuity in modern Christian art. While traditional Orthodox churches have maintained the canonical approach to iconography, other denominations have adopted diverse styles that often lack the symbolic depth and devotional intent of early icons.
At the end of the essay, I became really interested in the discontinuity of Christian Art in a large aspect of modern Christianity, and I suppose I can speak to this to an extent. I come from a protestant background, and icons and images tend to spook a lot of folks. But in essence, the Protestant Reformation reshaped Early Christian visual traditions by adapting imagery, architecture, and symbolism to align with new theological values. The principle of sola scriptura led to concerns about idolatry, resulting in restricted use of religious images and episodes of iconoclasm. Protestant churches prioritized simplicity, centering worship around the pulpit and the spoken word instead of elaborate altars and decorations.
[IV]: 🔰Remembering Everything You Read
I read a lot of stuff, and this video caught my eye, largely because I haven’t revisited my lessons on learning how to learn in a long time. I have heard about most of the ideas shared in the video, practiced some of it in college, etc. Sometimes I have this apprehension about summarizing something that is complex and sort of reducing it to this kind of synonym regime. That notwithstanding, I think this video is really good. In brief, Justin Sung outlined this system (PACER) for effective learning.
Procedural: Information about how to do something. For example, instructions on how to bake a cake or write a Python program. The key to mastering this information is practice. Don't just read the instructions, actually bake the cake or write the code!
Analogous: Information that connects to something you already know. For example, if you're learning about electrical circuits, you might relate it to the flow of water in pipes. The key here is to critique the analogy – how is it similar? How is it different? This deepens your understanding. I like analogies alot, it’s one of the easiest ways to catalyze learning new stuff.
Conceptual: Facts, theories, and principles. For example, understanding the concept of gravity or the principles of economics. The best way to digest this is through mapping, creating visual representations like mind maps to connect the concepts.
Evidence: Specific data or examples that support conceptual information. For example, statistics on climate change or historical examples of economic crises. The key here is to store the information in a system like a second brain or flashcards and rehearse it by applying it in different contexts. (I don't understand why a lot of these things have to be stored because we do have search and now, research on demand thanks to AI.)
Reference: Minor details that might be needed later. For example, the exact date of a historical event or the specific name of a chemical compound. Like evidence, you should store this information and rehearse it, often through flashcards and spaced repetition. (Except you are sitting for an exam that requires you to know this detail. Again I really don't see why these things need to be rehearsed)
[Books/Papers 📚]
Book(s) recently completed:
Causal Inference by Paul R. Rosenbaum [Book Review]
What I am currently reading:
On Truth by Simon Blackburn
Reflex: Python Web Framework Docs