Redefining Value In a World Saturated with Information
We are living through the largest democratization of information in human history.
Today, anyone with a smartphone can access more knowledge in a few minutes than most specialists would gather in days, only a generation ago. Naturally, this raises a question: if information is now effectively free, what remains valuable? Why invest years in learning anything when AI can explain almost everything?
The answer is that information was never a scarce resource. Judgment was.
AI has democratized access to knowledge, but it has not democratized the ability to recognise quality, authenticity, significance, or value. That ability, the essence of connoisseurship, is gaining value quicker than ever.
The anxiety surrounding artificial intelligence often assumes that expertise is primarily a matter of possessing information. If machines can access and reproduce knowledge at scale, what remains for human experts? Yet this assumption misunderstands what expertise has historically been and, in many ways, continues to be. For centuries, we confused expertise with information because information was difficult to obtain. Books and archives were expensive and inaccessible. Specialised knowledge lived inside institutions and professions. The expert appeared valuable because they possessed facts that others did not.
AI has shattered that arrangement almost overnight. As barriers to knowledge acquisition tumbled, people stopped turning to specialists and instead placed their trust in technology. Information became universal. Exceptional talent did not become less relevant; remarkably, it became more appreciated over time. Judgment was, and remains, its defining mark.
Connoisseurship is traditionally associated with art collecting; the term refers to expert discernment in matters of quality, authenticity, and taste. A connoisseur is not someone who possesses knowledge and information. A connoisseur is someone who has spent enough time looking, comparing, handling, tasting, observing, and evaluating that they can recognise quality when they encounter it.
This kind of expertise has always been difficult to explain because it does not exist primarily in language. A language model can describe the taste profile of Barolo. It can explain tannins, terroir, and vintage variation. It can summarise the opinions of critics and reproduce decades of wine literature. But none of this is the same thing as tasting hundreds of wines over twenty years and developing a sensory memory sophisticated enough to recognise a vintage blindly.
The difference seems obvious when framed this way, yet much of the current discussion around AI ignores it. What AI excels at is explicit knowledge: information that can be written down. Facts, definitions, explanations, summaries – these are the forms of knowledge that dominated education and intellectual status throughout much of the modern era.
Detail from the Hermès A/W 1998-1999 Collection by Martin Margiela, 1998. Photo by Marina Faust (https://www.cosmos.so/e/187787329)
Through his famous observation, “We know more than we can tell, ” philosopher Michael Polanyi argued that a great deal of human knowledge operates differently and cannot be conceptualized, almost like an instinct acquired through experience. A master violin maker cannot fully articulate every judgment that goes into evaluating a piece of wood. An experienced photographer often sees qualities in an image before being able to explain them. A jeweler notices details indiscernible to a novice. A chef recognises balance long before it can be reduced to a recipe. This level of insight is only cultivated through years of hands-on work in the retrospective field. And it is precisely this kind of expertise that gains visibility as informational knowledge becomes commoditised.
Historically, connoisseurs were valuable for exactly this reason. Nineteenth-century art scholar Giovanni Morelli became famous for attributing paintings by studying minute details such as ears and hands. Later, Bernard Berenson built one of the most influential careers in the art world through attribution and authentication based largely on cultivated visual judgment.
Their advantage was perception and experience, which wasn’t available to everyone. This distinction becomes increasingly important in the age of AI as we enter a world saturated with simulated knowledge. You can instantly access tons of information, essays, and recommendations. For the first time in history, information itself is becoming cheap enough to be taken for granted. When that happens, value migrates elsewhere. Luxury has always followed scarcity.
When books were rare, libraries were a luxury. When global travel was inaccessible, seeing distant places was a luxury. When expertise required years of research, knowledge itself functioned as a luxury good.
An artisan handcrafts a piece of Sophie Buhai jewelry in Los Angeles (https://www.cosmos.so/e/1052835843)
In the modern day and age, information is no longer scarce. This may be the most important cultural consequence of AI. Far from destroying connoisseurship, it transforms it into a new form of premium value. Connoisseurship cannot be mass-produced. We can take the winemaking sector as an example. An AI model can summarise the history of Burgundy wine, but it cannot spend years tasting it, accumulating sensory memory, and developing preferences through experience.
The same principle applies far beyond wine. Watches, furniture, architecture, fashion,
photography, literature, gemstones, music, design, food, every field where quality must be recognised rather than merely described becomes more valuable as information becomes easier to generate.
In this sense, AI does not diminish expertise. It separates expertise from information and reveals what was always underneath. Possessing endless data and knowledge is no longer an advantage when AI assistants are accessible at a few clicks on a phone. The real advantage is knowing what matters.
In a world flooded with generated content, opinions, recommendations, and aesthetics, the more valuable people are the ones whose judgments others trust.
This is why connoisseurship should not be confused with elitism. A person of affected taste uses taste to signal status, while a connoisseur pays attention to details to develop understanding. The difference matters because connoisseurship is not a social rank.
The future belongs neither to those who know the most facts nor to those who generate the most content. It belongs to those who can exercise judgment in conditions of abundance. And that is why connoisseurship is not disappearing.
Ultimately, the question arises: what forms of understanding gain value precisely due to the existence of AI?
Leave a Reply