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It is here that Massive Health, led by CEO Sutha Kamal sees a design opportunity. "Your body is the ultimate interface problem," says the company’s website. "Sometimes, it just doesn’t give you the feedback you need."
The company envisions a range of well-designed products that can improve those feedback loops and help improve the daily habits of their future customers. By "well designed" I don’t just mean "nice looking," though that’s a part of it. At its heart, Massive Health is a big data company and the real design work they are doing is marrying a simple front end to a surprisingly deep back end. Speaking with Kamal, you quickly understand that there is a layered long-term plan being implemented in phases. To start, they’ve set their sights on your terrible eating habits and the diet industry’s routine failure to fix them. Their first foray is called The Eatery (Massive Health Experiment 01) and it’s an iPhone app that lets you take pictures of everything you eat.
The food diary is a common strategy used by doctors and nutritionists helping their patients eat better. There’s a lot of research that shows that getting someone to record everything they eat drives change, says Kamal. The Eatery is what happens when you take a food diary and connect it to a social network and a massive back end.
Here’s how it works: You snap a photo of your meal and caption it. The app guesses where you are (you can adjust this as well as your portion size) and then you drag the picture onto a sliding scale from "Fit" to "Fat" based on how healthy you think the food is. You are then given the anonymous images of a few other people’s meals to similarly rate. After awhile, the crowd will have rated your meal. Every week, you can go back and track trends with a nice set of visualizations. If this seems like a kind of wishy-washy way to track your eating habits, Kamal wants you to know that this is on purpose. Most diet apps, he says, try to provide extremely specific information by pulling calorie counts and other data from online sources and previously entered meals. But the burrito you are eating probably has almost nothing in common with the burrito your search pulls up. It’s false precision.
There is a tradeoff that must be made when gathering data. High-fidelity data like exact portion sizes and other details of your meals might be useful, but the time and effort required to gather that information means that most people won’t do it. The Eatery chooses instead to make it really easy to record your meal, going for high density of data instead. "I get way more meals, even though I know less about each individual meal."
The goal is not only that you will start eating better, but that over time, you will get better at figuring out what’s healthy. By quietly testing you, Massive Health can begin to find out if that’s working. They can see how far you deviate from their expected answer and see if that deviation eventually improves. Some eagle-eyed users have filed bug reports where they notice they’ve been asked to rate the same image more than once. "It’s actually not a bug," says Kamal. "It’s interesting to see: how consistently are you rating over time?"
As Massive Health continues to run the service and gather users’ data, they begin to be able to do more interesting computation on it. Kamal says that over the next few months, we can expect to see all kinds of new features rolling out that exploit what they’ve learned, to give users nudges in the right direction. "Imagine if you could have a personal trainer who knew you and cared about you who could show up for 30 seconds 10 times a day," says Kamal. The emphasis is on small regular interventions instead of asking for longer deep engagement from the users.