A Food Critic That Never Eats: AI's Emerging Ability To Taste

Welcome to this week’s Deep-Fried Dive with Fry Guy! In these long-form articles, Fry Guy conducts in-depth analyses of cutting-edge artificial intelligence (AI) developments and developers. Today, Fry Guy dives into AI’s emerging ability to taste. We hope you enjoy!

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Imagine a food critic who never eats, yet still knows exactly what makes for a delicious piece of pizza or a perfect cup of coffee. It sounds absurd … until you realize AI is beginning to do just that.

Instead of using taste buds to enjoy the smoky flavor of some chicken wings, AI systems use a mix of chemical data, machine learning, and human input to analyze flavor. Some are trained on thousands of taste reviews to predict which new drink will go viral, while others rely on ultra-sensitive sensors to catch spoilage or subtle flavor shifts faster than any human could.

In this deep dive, we’ll look at two examples showing how AI is learning to “taste”: one that learns from crowdsourced flavor reviews, and another that quite literally mimics a tongue by leveraging advanced materials and sensors. Together, they offer a glimpse at the future of food—where your next favorite flavor might be chosen by an algorithm.

HOW AI SIMULATES TASTE

You might be thinking to yourself, why would anyone bother to teach machines to taste? After all, I don’t want a robot stealing my fries! Well, it’s because flavor is more than just fun—it’s fundamental. Taste drives what we eat, how we connect, and even how we stay healthy. By teaching AI to taste, we can enhance our own food. For food companies, getting it right means fewer flops on store shelves and faster paths to crave-worthy hits. For scientists, it means new ways to detect spoilage or contamination—or even diagnose health problems through saliva or breath. And for everyday eaters, it means the possibility of personalized meals that satisfy your taste buds and help you reach your wellness goals.

Of course, AI can’t taste the way humans do, but it gets pretty close by using two key methods:

• Learning from people: Platforms like Gastrograph collect detailed flavor reviews from people, who describe things like sweetness, bitterness, or spiciness. The AI learns patterns from this data and uses it to guess how other people might respond to new products—even in specific regions of the world and/or by age group.

• Using chemical sensors: Systems like Penn State’s “electronic tongue” work more like a real tongue. They use sensitive chemical sensors to measure the actual makeup of liquids. An AI then analyzes those signals to figure out what a sample is—like which soda it is or whether a juice has gone bad.

Together, these approaches let AI systems simulate tasting with surprising accuracy. They don’t need to eat the food; they just need to analyze the right data. Let’s look at how each of these systems work in more detail!

PREDICTING WHAT PEOPLE WILL LIKE

Gastrograph helps food and beverage companies understand how different groups of people experience flavor. It starts with a mobile app that lets trained tasters or everyday consumers rate products on specific characteristics—like how sour, bitter, floral, or creamy something is. Each rating creates a detailed data point in a massive database. Over time, the AI uses machine learning to recognize patterns across all this feedback. It learns not only what people say about flavors but also how age, region, cultural background, and even lifestyle can affect taste preferences. The goal is to train the AI to predict how a given product will be received by a specific group—or how to tweak it to make it more appealing to them.

In a remarkable experiment, just 12 Japanese testers sampled a product and gave their flavor feedback. Gastrograph used this small sample size to predict how 10 different consumer groups in China would respond to that same product. The results closely matched what real surveys later confirmed. The crazy part? The AI delivered its predictions in just two weeks, while traditional methods would have taken months.

This isn’t just some beta test that may be implemented down the road. Real companies are now using tools like Gastrograph during product development to adjust recipes before going to market. If a snack is too bitter for younger consumers or not salty enough for a specific region, the AI will spot it early and suggest that the company adjust their approach. This is like having a virtual taste-testing lab that can see into the future.

Some experts believe this technology will soon lead to hyper-personalized foods—where AI can learn from your taste preferences to suggest recipes tailored to your unique palate, much like how Spotify suggests songs you’ll love.

AN ELECTRONIC TONGUE: DETECTING FLAVORS WITH AI

While some machines are learning from human tastes, other machines are learning to taste for themselves. At Penn State, researchers are developing an experimental “electronic tongue”—a system that uses tiny chemical sensors to detect what’s in a liquid, then sends that data to an AI for analysis. These sensors are made from graphene—a super-thin, highly sensitive material that changes its electrical properties depending on which molecules it touches.

When dipped into something like juice or milk, the sensors produce a unique electrical signal based on the drink’s chemical makeup. The AI, which has been trained on a variety of samples, reads the signal like a fingerprint. It can identify what the drink is, how fresh it is, and whether it’s been tampered with—all in under a minute.

What’s even more impressive is that when researchers allowed the AI to decide for itself which parts of the chemical makeup were important (instead of telling it what to look for), its accuracy improved dramatically. The system learned to detect subtle differences in liquids—even tiny signs of spoilage that humans might miss.

This kind of technology could revolutionize food safety. Factories could use it to test every batch of juice for freshness or contamination, and smart packaging could alert your phone when milk is about to turn. It’s like giving our food system a high-tech sense of taste that never sleeps.

WHAT’S NEXT FOR AI AND TASTE?

Now that AI can analyze flavors and even mimic a tongue, the next question is: where does it go from here? As the technology advances, it’s likely we’ll see the following:

• Flavors made just for you, tailored not only to your preferences but potentially to your biology. AI could learn your personal taste profile, analyze your health data, and even factor in your mood or microbiome to suggest foods that hit the sweet spot between delicious and nutritious.

• Faster and bolder food innovation, where AI simulations test and refine thousands of ingredient combinations before a single one is cooked. This could lead to entirely new kinds of food, created with an algorithm’s sense of adventure—things that taste amazing but would never occur to a human chef. In fact, AI may discover the best food pairing since peanut butter and jelly.

• Smarter food systems, with AI-powered sensors integrated into packaging, factory lines, or even your fridge. Alluded to earlier, these systems could check freshness, detect spoilage, offer recipe suggestions to reduce waste, and help people store food more efficiently.

While these implications are realistic, it’s possible AI taste doesn’t stop there. In the future, dining could become interactive: seasoning might adjust in real time based on your reactions, or AI could generate flavors that change as you eat. Who knows? Maybe certain foods will be designed so they get better with each bite!

Now, before we get too crazy about AI’s ability to taste, it’s worth noting that it doesn’t experience food like we do and likely never will. AI won’t savor a home-cooked meal or understand the nostalgia behind grandma’s pie. But it might help recreate that feeling for someone else, in a new way. Whether it’s making your meals more personal, your kitchen smarter, or your palate more adventurous, AI is adding a new flavor to the future of food.