Social media and students’ privacy: What schools and districts should know

For many schools and school districts around the United States, a Facebook page or Twitter account serves as a tool for updating the community about events, highlighting the accomplishments of staff and students, and, especially during a pandemic or other crisis, sharing essential information (Michela et al., 2021; Rosenberg & Nguyen, 2021). Because their purpose is to reach the community, official school social media accounts are often fully accessible to the public. But what does this mean for student privacy, especially in a time when rapid technological advancements allow for increasingly sophisticated analyses of social media and image data? While some research on social media use has focused on privacy (e.g., Fiesler & Proferes, 2018), no research to our knowledge has investigated it in the context of K-12 educational institutions. We have made some initial steps into building a research base by examining the extent to which students are identifiable in Facebook posts of public schools and districts and pinpointing the potential risks of that data (Burchfield et al., 2021).

Over the past year, we have explored how schools and school districts use social media to communicate, and we have been impressed by the unabashedly positive and uplifting messages K-12 educational institutions shared on their accounts. However, many of these public posts included the names and faces of students, and because these were posts by schools and districts, the photos were implicitly tied to a particular place. Those who create these posts doubtless want to recognize or even celebrate individual students — indeed, many posts were to announce students’ accomplishments — but they could be unintentionally compromising students’ privacy in unseeable and often unknowable ways.

While school districts may not have reason to think that individuals or organizations may use these posts of students for nefarious ends, it is hard to predict how identifiable photos of students could be used now or in the future. We already know that facial recognition algorithms exist that use images to predict such characteristics as political identity (Kosinski, 2021) or sexual orientation of individuals from facial images (Wang & Kosinski, 2018). It is not beyond the pale to imagine using photos to make such predictions (correctly or incorrectly) in ways that could result in personal, educational, or employment-related discrimination. While the validity and ethical integrity of such algorithms are still contested, their existence demonstrates how technological advancements pose unknown risks to individuals with publicly available personal data.