The general use of wearable devices such as smartwatches, smart glasses and even smart rings is on the rise, meaning that more personal data is collected and stored every second by private companies. While 72% of Americans believe that companies should face stricter regulations, the reality of data regulation is much more complicated.
Grant Scherling is a freshman studying business entrepreneurship. According to him, understanding the potential risks of sharing personal data has not actually affected his behavior much.
"Data privacy isn't an issue that really is of much concern unless it stares you in the face," Scherling said.
Even though he is aware of issues such as online fraud, like many people he usually still connects to unsecured Wi-Fi networks.
Over 400 terabytes of digital data are collected every day worldwide. Not all of this is collected from wearable sensors, however, the modes of data collected by private companies include audio, images, geospatial data, biometric data and internet activity.
Yanjie Fu is a professor at the School of Computing and Augmented Intelligence who specializes in data mining and artificial intelligence. As he points out, personal data encompasses a wider range than people realize, including data that was not intentionally given by the consumer.
"When you're talking to me (over Zoom), If you don't blur your background, I can quickly find your (region) from your background," Fu said.
One concern for mass data collection is how large language models can attack private stores of personal data for access, even with anonymization techniques that are commonly used to protect the personal data.
"Some researchers want to investigate or research ... how can we attack privacy?" Fu said. "On the other hand, a lot of researchers are trying to research ... how can we defend (against) that?"
Federal privacy laws are one defense against the misuse of data, however, they also have their drawbacks.
Aurel Coza is a center director and professor of practice who specializes in wearable devices. He said that in one case study researchers were able to identify early signs of Parkinson's disease combing through social media, however, these individuals could not legally be informed.
"(They might know) years before they actually get sick ... but they cannot tell their clients, because you don't have the FDA approval," Coza said.
Further adding to the complicated nature of these laws is the fact that data privacy applies to every step of data analysis, from collection to application.
After data is collected, it is anonymized and stored in cloud platforms such as Hadoop, an open-source data framework with servers distributed around the world. From there, patterns in the data can be identified through software and statistical analysis, transforming the data into a form that researchers can use.
In industry applications, this data is often used for marketing purposes, but researchers like Coza believe there is untapped potential to use that data in academia.
"Nobody by themselves can actually utilize or analyze that vast amount of data," Coza said. "They would need help from universities."
While data privacy is increasingly complex with the development of wearable devices and generative AI, collaboration between academia and industry is crucial to protecting individual data.
Edited by River Graziano, Sophia Braccio and Madeline Schmitke.
Reach the reporter at jnolas77@asu.edu.
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