Cyclical Shifts in Female Perception
Do Companies Buying Data from Menstrual Cycle Tracking Apps Know More than You?
by Ashley Beatty
This project is a satirical app with two goals:
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Demonstrate the personal value and utility of menstrual cycle awareness.
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Raise awareness of ethical issues in technology. Big Data has reduced us to algorithms. Are we complicit?
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Abstract
Estrogen and progesterone are potent neuromodulators with different and opposing functions. The shift of these hormones over the menstrual cycle creates two distinct frameworks that motivationally bias perception.
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For example, an MRI study by D. Van Vugt published in 2010 demonstrated considerable shifts in appetite and food consumption across the menstrual cycle. During the follicular phase, when estrogen is dominant, women showed increased brain activity in response to images of low calorie foods and simultaneously showed a behavioral preference for low calorie foods and ate smaller meals. During the luteal phase, when progesterone is dominant, women showed increased brain activity in response to images to high calorie foods, showed a behavioral preference for high calorie food and ate larger meals. While women may be socially conditioned to notice an increase in chocolate cravings during the brief premenstrual phase, the majority of women are likely not cognizant of these broader perceptual changes.
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Imagine you are a vegan raw food company selling dehydrated kale chips. Would it not be advantageous to only target women in the follicular phase? Would Cheesecake Factory be better off targeting women in the luteal phase? If you use a fertility or menstrual cycle tracking app, your data is for sale. If this type of data profiling is not happening already, it will soon. Modern neuroscience is busily decoding and quantifying human behavior. Once we understand the parameters, it is a short step to plug data points into automatic algorithms in the service of advertisers. Not only is this a privacy issue, it elucidates the growing concern that our technology knows us better than we know ourselves.
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Three popular fertility and menstrual cycle tracking apps, the new generation of advertising strategies and the menstrual cycle.
Project Proposal
My proposed app will function as a usual fertility tracking app, collecting user input such as the date of a woman’s last menstruation, daily basal body temperature, cervical mucus consistency, illness, alcohol consumption, mood, and sexual activity and then use this data to predict fertile periods and pending menstruation. But it will also have two additional parallel outputs:
One—Delivery of fun facts about brain function changes particular to the cycle phase the app determines the user is in (utilizing the affordance of targeted timing). Topics would include shifts in motivation / reward sensitivity, social preferences, fear, pain, stress / anxiety and digestion / appetite.
Two—Prompt the user with specific data requests, such as:
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“Send Ben and Jerry’s the anticipated date of your next period? Reply YES or NO.”
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“Send Ebay the date range your dopamine levels (correlated to gambling and binge shopping) are predicted to be highest? Reply YES or NO?”
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“Send BlueCross BlueShield the number of drinks you had this month and which days you had sex? Reply YES or NO”
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“Send your boss the date range your self esteem is predicted to be lowest so he can schedule discussions regarding your recent promotion request? Reply YES or NO”
As the user’s neuroscientific knowledge grows with the fun facts, the complexity of the data request prompts would become increasingly invasive and insidious – just how much CAN you infer about future behavior? The app will also source data collected on the user (Google search history, Amazon purchase history, social media interactions) and plug it back into the app to point out social and consumer patterns the user may not be aware of. A cautionary sci-fi AR component that allows the user to “see” the cycle phase of every female around them would further drive home the privacy concern.
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Project execution
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A menstruating woman’s basal body temperature shifts just after ovulation, marking the transition between the follicular (estrogen dominant) and luteal (progesterone dominant) phase. Daily basal body temperature inputs are necessary for accurate cycle phase calculation. In order to make a fully integrated app, I first need a wireless thermometer.
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Materials
Capacitor
Resistor (2)
Conductive Thread
Fabric
Battery
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Programs
Arduino 1.8.7
Touch Designer
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Services
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The circuit was initially worked out with a SparkFun Inventors Kit using these pinout, wiring and coding instructions. When moving to the Feather Huzzah32, updating to Arduino 1.8.7 was key along with the addition of a capacitor.
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The board and components were then stitched into a soft circuit on fabric using conductive thread.
Once the sensor was functional, Touch Designer was used to retrieve the wireless sensor data from the Feather, and transfer the data to Dweet.io, a webservice similar to Twitter, but for devices.
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Results and Conclusion
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I enjoy the puzzle of electronics! My input device is functional but needs some calibration. Though I am excited to branch into coding and electronics, I am not sure this is the best form for my project. The concept is there, and apps can be useful and fun, but they are already a tired medium. So, back on the hunt for an intriguing and effective way to communicate cyclic perceptual shifts…
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