Machine supervised taste? From Bourdieu to NewJeans
The internet and social media have completely changed how our tastes define who we are. In the past, sociologists like Bourdieu saw taste as a way for social classes to set themselves apart - you either had "good taste" or you didn't, based on fairly rigid cultural rules. But today's digital world is much messier and way more interesting than that.
Let's look at K-pop fans as an example. A teenager in Mexico City can be deeply into NewJeans' carefully crafted style while also being passionate about completely different things - maybe rejecting motherhood and embracing alternative ways to create meaningful connections and build supportive networks, or how enriching comforts and sophistication led to ‘Mocha Mousse’ being Pantone color of the year.
In the past, these different tastes wouldn't have "made sense" together. But there's another layer to this: AI systems and algorithms are increasingly shaping how fans discover and engage with content. This creates two different speeds of change in how tastes evolve: the natural, gradual shifts in what people like, and the sudden whiplash changes that happen natively on tiktok or when platforms update their algorithms or recommendation systems.
Phillips once described taste as being like a "club" with clear insiders and outsiders. This idea still holds up, but the walls of these clubs have become much more flexible. You can now belong to many different taste communities at once. However, these communities are increasingly shaped by AI recommendation systems. Think of these systems as eager but imperfect assistants - they can help connect people with content they might like, but they still need human oversight to work well.
Instead of traditional power structures simply dictating taste from the top down, we now have what could be called a “machine supervised taste ecosystem." Like the AI systems currently transforming various industries, taste formation increasingly works through a combination of algorithmic processes and human guidance, creating multiple centers of influence that operate at different speeds and scales.
The old saying that taste is about "how others see us" is still true, but with a twist: those "others" now include AI systems that watch, categorize, and spread our taste preferences. When a NewJeans fan masters their dance moves or deeply understands their "teen fresh" style, that knowledge becomes valuable not just in their local community, but globally and in the eyes of algorithms that might promote their content.
When NewJeans drops a new style and it spreads worldwide within hours through TikTok and Instagram, something interesting happens. We're seeing a new system where human tastemakers and AI amplification work together. The power to decide what's "cool" hasn't disappeared - it's shifted from traditional gatekeepers to a complex mix of social media platforms, algorithms, and influencers.
This shift mirrors what's happening with AI technology more broadly. Just as AI capabilities are split between your personal devices and powerful remote servers, taste formation now happens through a distributed system where individual preferences mix with algorithmic recommendations and rapid global trends. You can still be part of exclusive "taste clubs," but membership is more fluid and globally connected than ever before.
The question of who really controls these taste standards becomes even more interesting in this context. Instead of traditional power structures simply dictating taste from the top down, we now have what could be called a “machine supervised taste ecosystem." Like the AI systems currently transforming various industries, taste formation increasingly works through a combination of algorithmic processes and human guidance, creating multiple centers of influence that operate at different speeds and scales.
We're seeing a new system where human tastemakers and AI amplification work together. The power to decide what's "cool" hasn't disappeared - it's shifted from traditional gatekeepers to a complex mix of social media platforms, algorithms, and influencers.
Fast forward a little bit more we might see the emergence of a complex system that helps shape and maintain what people consider "good taste” or even “taste AGI.”
Looking ahead, we might see taste formation follow a similar path to AI development: moving from systems that need constant human supervision to ones that can operate more independently. Just as AI might evolve from needing guidance every few minutes to every few hours or days, taste communities might develop more sophisticated ways of maintaining themselves through a mix of human and algorithmic curation.
Fast forward a little bit more we might see the emergence of a complex system that helps shape and maintain what people consider "good taste” or even “taste AGI.” Rather than having one big AI system deciding what's cool or beautiful, imagine a network of different systems working together. These systems would understand, adapt to, and influence aesthetic preferences across different groups, cultures, and situations - all while allowing those preferences to naturally change over time.
Think of it like a living, breathing ecosystem of taste that can maintain consistency while still being flexible enough to evolve. It wouldn't be controlled by a single authority, but would instead emerge from the interactions between people, AI systems, and cultural trends.
This evolution suggests that while the basic ideas about how taste works in society (from thinkers like Bourdieu and Phillips) are still valuable, today's digital landscape has created something much more complex. Understanding how tastes form and spread now requires us to look not just at human social dynamics, but at how people, algorithms, and digital platforms all work together to shape what we consider cool, beautiful, or worth paying attention to.
AI’s rise to cultural and technological prominence isn't just changing how we work - it's transforming how we develop and share our tastes. And just as businesses are figuring out how to integrate AI effectively, our culture is learning to navigate a world where human judgment and algorithmic influence are increasingly intertwined.
P.S. Don’t count humans out yet though. Until Reddit is taken over by AI bots talking to each other, people’s opinions and taste will keep vivid color and friction in the picture.
