The Tyranny of the Algorithmic Palate

There’s a strange comfort in believing that machines know us better than we know ourselves. Spotify delivers the perfect background music for our melancholic Tuesday. Netflix predicts that we’ll enjoy yet another Nordic crime drama. Amazon whispers that if we liked this artisanal olive oil, we might love that copper-hinged pour spout. And wine? The sommelier has been replaced by a string of code with access to our purchase history, social media presence, and probably our blood type. “You may also like…” has become the default gesture of modern life—eerily confident, always suggestive, rarely questioned.

But when it comes to wine, this algorithmic seduction isn’t just flattening our preferences. It’s flattening us.

Wine, after all, is one of the last remaining bastions of subjectivity—an art of nuance, variation, and unpredictability. It’s a domain where memory, mood, temperature, food, glassware, and even the company you keep shape the experience of a single bottle. Wine is not data; it’s moment, context, and transformation. To taste well is to become a subject, not a data point. And yet, the wine world has eagerly embraced systems that promise to make taste predictable, legible, and above all, efficient.

Open your favorite wine app and you’ll find an interface not unlike a dating app: swipe right on the Napa Cab, left on the Barolo. Upload your preferences (“bold reds,” “dry whites”), and the system will churn out a list of labels that match your “taste profile.” Some of these tools rely on enormous user databases—effectively treating wines like Yelp-reviewed tacos—while others, more ambitious, claim to analyze chemical compounds and flavor profiles to engineer optimal matches. The assumption behind all this is clear: your taste is a stable, mappable entity. You like what you like. Our job is to deliver more of it.

But this is a dangerous lie. Taste, if it’s to mean anything, must exceed preference. It must be educable, elastic, capable of surprise. A wine recommendation system that only feeds you variations on your past favorites is not helping you develop a palate. It’s building you a cage.

Worse, it’s a cage with a feedback loop. The more we rely on algorithmic predictions to select our wines, the less adventurous we become, and the more our preferences harden into caricature. A consumer who once flirted with oxidative Jura whites or lightly chilled reds from Etna is now reassured, again and again, that what they really love is that mid-weight Oregon Pinot. This is not discovery; it’s recursion. And like all algorithmic systems, it thrives not on depth of knowledge but on breadth of data. The more predictable your behavior, the more efficiently you can be monetized.

The logic is eerily similar to that of social media echo chambers: tell us what you believe, and we’ll feed you back versions of it until you no longer know the difference between taste and identity. In wine, this manifests in curated subscription boxes, influencer-endorsed bottle lists, and the dark abyss of “people who bought this also bought…” Until suddenly, your wine cellar isn’t a reflection of your curiosity—it’s a reflection of your purchasing algorithm.

This would be merely annoying if wine were a simple commodity. But wine resists simplicity. Each bottle is a time capsule: of climate, soil, vintage, and human choice. No algorithm can account for the alchemy of an offbeat pairing, or the way a wine evolves over the course of a long evening. No metric captures the joy of trying a wine that confounds your expectations—a white that drinks like a red, a rustic blend that tastes of salt and stone. These are the moments that cultivate judgment, not just preference. And judgment is not static. It grows. It risks. It changes its mind.

To be clear, technology isn’t the enemy. There’s nothing wrong with wanting help navigating the overwhelming abundance of wine options today. But when recommendation systems replace the messy, human labor of learning how to taste, we don’t just lose variety—we lose agency. We become passengers in our own palates, carried along by automated predictions masquerading as personalized expertise.

So what’s the alternative? Start with doubt. Doubt the system. Doubt your preferences. Doubt the star ratings and the tidy tasting notes. Seek out wines that challenge your assumptions. Drink things that seem “off,” “funky,” “weird.” Talk to people, not just apps. Visit wine shops where someone wants to know what you ate for dinner before they recommend a bottle. Taste blind. Taste together. Taste often.

And above all, remember that good taste is not a matter of having your preferences confirmed—it’s a matter of discovering, over and over, that you are more complicated than any algorithm can measure.

Wine, if it’s anything at all, is a celebration of our irreducibility. Let’s not flatten it into code.