Skip to Content

Eating App Tells You How Healthy—or Not—Your Meal Was

The Eatery asks other users to rate your meal, a system it claims is more reliable than software that estimates calories.
December 1, 2011

Most people have a pretty good idea of what it means to eat healthy foods, but few manage to do it. A new app called the Eatery aims to change that by having users rate one another’s meals and providing slick data visualizations of a person’s habits over time.

Health drive: More than two million meals have been rated for healthiness by users of the Eatery app.

The app’s users have rated more than two million meals so far. When overlaid on maps, this data reveals patterns in healthy eating in cities like New York and San Francisco.

Eatery users snap a photo of a meal, and that photo is automatically tagged for location. After users take a photo of a meal, they are prompted to quickly rate the healthfulness of other users’ meals by looking at their photos, in a quick process intended to be fun. This process ensures that each user’s meals are rated by other Eatery users.

The app uses those meal ratings to provide users with statistics, including changes from week to week in what they ate, the places where they ate the most healthy and least healthy meals, and their best and worst meals of the week.

See images from the Eatery on the following pages.

A day of data from San Francsico shows unhealthy eating clustered in the downtown areas, particularly SoMa, where many startup companies are based. Most of this unhealthy activity happens at lunchtime, when workers may hastily grab something to eat.

“Eating is at the core of what makes us healthy or not,” says Aza Raskin, founder of Massive Health, which created the app. “This app is designed to provide ‘nudges’ that make you able to make actionable decisions about your diet.” Raskin is an interface designer and founded Massive Health. He previously led user experience for Mozilla’s Firefox Web browser. The company has $2.25 million in venture capital funding.

The app gives new users a brief quiz about their diets so the system can decide which kind of meals they are best able to rate. Since multiple people rate any given meal, Massive Health’s system can discount the most extreme ratings. Qualified nutritionists rate a fraction of the meals to provide an anchor to the system.

Raskin says this approach is easier than asking users to manually calculate calories, and says the crowdsourcing is more reliable than software that estimates calories from a photo, usually by a wide margin of error.

New York starts the day with mostly healthy meals.

Users can see the meals recorded by friends inside the app and comment on what they see. “If you want to help a friend with their diet today, you have little option other than nagging when you see them,” says Raskin. “This give a more positive way to step in.”

Raskin describes the Eatery as an “experiment” intended to test how the design of an app can provide people with better insights into their habits and cause them to make improvements. The company’s longer-term goal is to create apps that boost the effectiveness of more conventional medical treatments for chronic conditions such as diabetes.

But Eatery users make less healthy choices in the afternoon.

Raskin says the data collected by the Eatery’s users could also find uses in everything from mobile mapping to public health. For example, someone in search of a lunch spot could be guided toward particular menu items, or guided to a restaurant that had served healthy meals in the past, says Raskin.

“We can start telling cities about food deserts from how people eat when there,” Raskin says, “or the difference that a Whole Foods opening in a neighborhood or the number of Starbucks per square mile has on healthy eating.”

Keep Reading

Most Popular

Large language models can do jaw-dropping things. But nobody knows exactly why.

And that's a problem. Figuring it out is one of the biggest scientific puzzles of our time and a crucial step towards controlling more powerful future models.

OpenAI teases an amazing new generative video model called Sora

The firm is sharing Sora with a small group of safety testers but the rest of us will have to wait to learn more.

Google’s Gemini is now in everything. Here’s how you can try it out.

Gmail, Docs, and more will now come with Gemini baked in. But Europeans will have to wait before they can download the app.

This baby with a head camera helped teach an AI how kids learn language

A neural network trained on the experiences of a single young child managed to learn one of the core components of language: how to match words to the objects they represent.

Stay connected

Illustration by Rose Wong

Get the latest updates from
MIT Technology Review

Discover special offers, top stories, upcoming events, and more.

Thank you for submitting your email!

Explore more newsletters

It looks like something went wrong.

We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at customer-service@technologyreview.com with a list of newsletters you’d like to receive.