Online culture moves at a breakneck pace, with subcultural terms like "6-7" and "looksmaxxing" breaking into public consciousness alongside past fads that once dominated headlines. Only a few years ago, technology advocates pitched non-fungible tokens (NFTs) as the financial future and audio networking apps like Clubhouse as the next epoch of social interaction, only for both to rapidly flame out. According to Ruby Thelot, a cyber-ethnographer and media theory researcher at NYU, our collective framework for assessing digital trends is fundamentally flawed. Internet spaces have become thoroughly balkanized into isolated digital islands, where phenomena that appear viral are frequently nothing more than forced algorithmic consumption within specific provinces rather than broad mainstream adoption. Ahead of the fall release of his book In Defense of Being-On-Line, Thelot offers a critical breakdown of manufactured virality, dating app fatigue, prediction markets, and the philosophical misconceptions driving artificial intelligence narratives.
The Virality Trap and Goodhart's Law in Digital Media
The primary issue with understanding contemporary digital culture stems from turning a measurement metric into an explicit target. Under Goodhart's law, formulated by British economist Charles Goodhart, whenever a measure becomes a target, it ceases to function as a reliable measure. In modern media production, content is systematically engineered solely to achieve high view counts, completely bypassing the inherent cultural value that creates lasting resonance. Because the media ecosystem is so deeply entrenched in Goodhart's law, creators can reliably manufacture artificial virality without that engagement ever filtering down into real world culture or achieving true mainstream staying power.
Deconstructing Dating Burnout and the Reality of Heteropessimism
Over the past several years, media narratives surrounding dating app burnout have led platforms to pivot toward artificial intelligence features. In May, Bumble announced the discontinuation of its iconic swipe feature in an effort to re-engage users. However, Thelot argues that the pervasive narrative of dating exhaustion is largely a cultural mirage. While "heteropessimism" has been documented since 2019 to describe systemic dating frustration among heterosexual women, its actual prevalence on social platforms is significantly overblown.
To test this thesis empirically, an investigation examined approximately 1,000 social media videos across Instagram and TikTok that had accumulated over 1 million views. The objective was to quantify the exact proportion of content expressing genuine negative sentiment regarding dating. The findings revealed that negative content hovered consistently around just 25 percent. Furthermore, platform specific dynamics play a key role, with networks like X maintaining algorithms designed for heightened conflict. The data indicates that culture writers have exaggerated heteropessimism, mistaking platform specific echo chambers for a universal social collapse in dating.
Prediction Markets as Social Infrastructure for Male Bonding
Widespread adoption of prediction markets like Kalshi and Polymarket has seen young demographics wagering on diverse events ranging from Bad Bunny's Super Bowl halftime performance to Oregon wildfires. Thelot draws a direct parallel between this trend and his study of young men trading meme coins between 2020 and 2024. Far from being isolated financial decisions, these activities operate primarily as forms of collective gambling within group chats, colloquially dubbed "the trenches."
In these digital spaces, participants share intelligence, execute trades simultaneously, and absorb financial losses as a collective. Amid an ongoing male loneliness epidemic, this shared financial risk functions as a novel, interactive mechanism for male bonding. Prediction markets operate not merely as financial instruments but as tools for cultural participation. For individuals spending up to 8 hours daily in front of screens, the primary motivation is not necessarily monetary reward, but achieving closeness to the cultural events themselves through the act of placing a wager.
Why Raw Intelligence Is Not AI's Ultimate Metric
As artificial intelligence continues to reshape technological workflows, apocalyptic forecasts predicting world ending scenarios are growing increasingly vocal. Thelot contends that such predictions will be viewed with skepticism in 10 years because human societal issues are rarely bottlenecked by a shortage of raw intelligence. Instead, global challenges stem from difficulties in human cooperation, coordination, and aligning large groups toward shared objectives. Quantifying intelligence as the single defining metric repeats the trap of Goodhart's law.
Furthermore, the belief that raw intelligence is the ultimate power echoes the assumptions of Sir Francis Galton, the father of eugenics, who posited that a specific group held superior intellectual capacity. Modern AI enthusiasts frequently project their own self perceived values onto the concept of superintelligence, a stance that is philosophically flawed. Drawing on the work of French philosopher Gilbert Simondon, who noted that technological advances often leave crucial human elements behind, Thelot emphasizes that focusing exclusively on quantified intelligence risks marginalizing essential non-computational human faculties, including emotional intelligence, physical bodily awareness, and artistic intuition.
