Inequality is a bigger threat to democracy than polarization.
In fact, polarization is often a sign of a healthy democracy beginning to confront systemic inequalities. And yet scholarship about technology and political communication often frames polarization as the biggest ongoing threat to democracy in the United States. This seeming contradiction, CITAP’s Daniel Kreiss and Shannon McGregor argue, is about race.
In “A review and provocation: On polarization and plaftorms,” Kreiss and McGregor point out that the content of the poles in polarization is both important—and often ignored. Polarization does not account for the crucial differences between, for example, white supremacists and racial justice activists. Black Lives Matter and Stop the Steal are not equally good movements for democracy: as BLM activists explicitly calls for greater equality in a democratic society, Stop the Steal activists seek to overturn elections.
As Kreiss and McGregor put it, “polarization is… the necessary byproduct of the struggle to realize democracy in unequal societies.”
If political communication and media and technology scholars want to understand polarization, they cannot continue to do so from a power-disinterested lens. Polarization and systemic inequality are co-produced. And yet frequently the problems caused by polarization are blamed on those simply calling for justice. Ultimately, scholars frame struggles for justice as “polarizing” because:
our field’s conceptualizations of democracy are so thin, solidarity is so treasured, racial analytics are so rare, and historical memory is so short. It is not polarization, but racial repression that has been far more challenging and destabilizing to democracy over the past 300 years if looked at from a non-White perspective.
Digital trace data can change the study of misinformation, algorithmic bias, and well-being.
In this coauthored article, Deen Freelon joins with scholars across the United States and the Netherlands to discuss methods of digital trace data collection and measurement. Digital trace data (or DTD) are the tracks we leave in the snow of the digital spaces we occupy (e.g., cookies in your browser after an online shopping spree or the log data tracked by social media platforms). Although we commonly think of these kinds of data as privacy violations, they are also an opportunity for researchers to overcome the known limitations of platform-centric and user-centric approaches. Of course, collecting this data, organizing, analyzing, and measuring it in meaningful ways comes with its own challenges. Read on for an in-depth deep dive into the best practices for using DTD.
You can’t understand privacy without understanding power.
When we think about “privacy,” we often think of an individual’s privacy, her individual right to privacy, and individualized strategies for retaining control over private information. This is an ahistorical way of thinking that ignores the ways privacy violations are patterned in ways traceable to marginality and domination. Populations identified as “dangerous,” like Muslims after 9/11 or transgender individuals in the current political climate are disproportionately surveilled, their privacy deemed violable in the interests of other people’s safety.
Unfortunately, as Marwick shows in this paper, such issues of systemic issue are rarely addressed at global conferences about privacy like IAPP and SOUPS. Instead, techno-optimism rules the day, complete with sales booths offering the newest products individuals might use to protect themselves. Privacy isn’t an individual problem for which individual solutions that fiddling with privacy settings will help: privacy violations are gendered (most stalkerware is used against women by current or former male partners) and they are raced (as Black and brown communities in the U.S. are all too aware). Conceptualizing privacy without power is simply inadequate in the current moment.