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Submitting unwanted data to time-tracking apps does not protect reproductive privacy

Social media users have posted ideas on how to protect people’s reproductive privacy when the Supreme Court Overturned Roe v. Wadeincluding input “junk” data in apps designed for menstrual cycle tracking.

People use time period tracking apps to: predict their next period, talk to their doctor about their cycle and determine when they are fertile. Users log everything from cravings to periods, and apps provide predictions based on these inputs. The app predictions help with simple decisions, such as when to buy tampons next, and provide life-changing observations, such as whether you’re pregnant.

The argument for submitting unwanted data is that it activates the apps’ algorithms, making it difficult or impossible for authorities or vigilantes to use the data to invade people’s privacy. However, that argument does not hold.

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As researchers developing and evaluate technologies that help people manage their health, we analyze how app companies collect data from their users to provide useful services. We know that popular time-tracking applications would require millions of people to enter unwanted data to even give the algorithm a boost.

Junk data is also a form of “noise”, which is an inherent problem developers design algorithms for to be robust against. Even if unwanted data “confused” the algorithm or provided too much data for authorities to investigate, the success would be short-lived as the app would be less accurate for its intended purpose and people would stop using it.

Moreover, it would not solve existing privacy problems, because people’s digital footprints are everywhere, from internet searches for using the phone app and location tracking. This is why the advice is to urge people to delete their period apps well-meaning but not well.

How the apps work

When you first open an app, enter your age, date of your last period, how long your cycle is, and what type of birth control you use. Some apps connect to other apps, such as physical activity trackers. You record relevant information including when your period starts, cramps, discharge consistency, cravings, sex drive, sexual activity, mood and heaviness.

Once you give your data to the app company of the period, it’s unclear what exactly happens to it, as the algorithms are owned and part of the company’s business model. Some apps ask for the user’s cycle length, which people may not know. Indeed, researchers found that 25.3% of people said their cycle had the oft-cited duration of 28 days; however, only 12.4% actually had a 28 day cycle. So if an app has used the data you enter to make predictions about you, it may take a few cycles for the app to calculate your cycle length and more accurately calculate the phases of your cycle.

An app can make predictions based on any data the app company has collected from its users or based on your demographics. For example, the app’s algorithm knows that a person with a higher body mass index can have a 36 day cycle. Or it can use a hybrid approach that makes predictions based on your data, but compares it to the company’s large dataset of all its users to let you know what’s typical — say, a majority of people report having cramps. have just before their period.

What does submitting unwanted data result in

If you regularly use a period-tracking app and provide it with inaccurate data, the app’s personalized predictions, such as when your next period will occur, may also become inaccurate. If your cycle is 28 days and you start logging that your cycle is now 36 days, the app should adapt – even if that new information is incorrect.

But what about the data in total? The easiest way to combine data from multiple users is to average them. For example, the most popular time tracking app, Flo, has an estimated 230 million users. Imagine three cases: a single user, the average of 230 million users, and the average of 230 million users plus 3.5 million users submitting unwanted data.

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