Jan. 11, 2012 at 10:43am with 10 notes
Reblogged from slavin
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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.
The important thing isn’t the exact number of calories that you are eating, says Kamal, it’s the changes over time. “We don’t care what you had for lunch today. The questions is: Are you eating better this week than you ate last week?” It’s about tracking and encouraging marginal changes and transforming habits.
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.”
It’s an intriguing approach, and one reminiscent of how Google, that biggest of big data companies, tamed the web. Rather than trying to create a top-down directory, PageRank found signals in the chaotic noise of the network. Similarly, Massive Health’s approach is to gain insights from the idiosyncratic activity of its users. Both companies also see the value in hiding all of that information behind a very simple interface.
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.
The important thing isn’t the exact number of calories that you are eating, says Kamal, it’s the changes over time. “We don’t care what you had for lunch today. The questions is: Are you eating better this week than you ate last week?” It’s about tracking and encouraging marginal changes and transforming habits.
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.”
It’s an intriguing approach, and one reminiscent of how Google, that biggest of big data companies, tamed the web. Rather than trying to create a top-down directory, PageRank found signals in the chaotic noise of the network. Similarly, Massive Health’s approach is to gain insights from the idiosyncratic activity of its users. Both companies also see the value in hiding all of that information behind a very simple interface.
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chrishamby reblogged this from slavin and added:
Trying it this week, we’ll see how it goes
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