Importantly, algorithmic biases likely impose long-term psychological impacts on teenagers, many of whom spend almost every waking minute online: A 2018 Pew Research Center study found that 95 percent of teens have access to a smartphone, and 45 percent describe themselves as being online “almost constantly.” Hispanic teens, in particular, spend more time online than their white peers, according to the same study. Given America’s reliance on remote learning during the pandemic, adolescents are likely spending even more time on the internet than they did before.
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Research suggests that being on the receiving end of discrimination is correlated with poor mental-health outcomes across all ages. And when youth of color experience discrimination, their sleep, academic performance, and self-esteem might suffer. Experiencing discrimination can even alter gene expression across the life span.
Algorithmic racism frequently functions as a type of technological microaggression—those thinly veiled, prejudiced behaviors that often happen without the aggressor intending to hurt anyone. But the algorithmic variety differs from human microaggressions in several ways. For one, a person’s intent might be hard to pin down, but the computational models imbued with algorithmic bias can be exponentially more opaque. Several common machine-learning models, such as neural networks, are so complex that even the engineers who design them struggle to explain precisely how they work. Further, the frequency at which technological microaggressions occur is potentially much higher than in real life because of how much time teens spend on devices, as well as the automatic, repetitive nature of programmed systems. And everyone knows that human opinions are subjective, but algorithms operate under the guise of computational objectivity, which obscures their existence and lends legitimacy to their use.
Teens of color aren’t the only ones at risk of computer-generated racism. Living in a world controlled by discriminatory algorithms can further segregate white youths from their peers of color. TikTok’s content-filtering algorithm, for example, can drive adolescents toward echo chambers where everyone looks the same. This risks diminishing teens’ capacity for empathy and depriving them of opportunities to develop the skills and experiences necessary to thrive in a country that’s growing only more diverse.
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Algorithmic racism exists in a thriving ecosystem of online discrimination, and algorithms have been shown to amplify the voices of human racists. Black teens experience an average of five or more instances of racism daily, much of it happening online and therefore mediated by algorithms. Radicalization pipelines on social platforms such as YouTube can lead users down rabbit holes of videos designed to recruit young people, radicalize them, and inspire them to commit real-world violence. Before the internet, parents could discourage their kids from spending time with bad influences by monitoring their whereabouts. Today, teens can fraternize with neo-Nazis and spread eugenics propaganda while just feet away from a well-intentioned but unaware parent. Part of the problem is that parents don’t see the underlying structures of popular platforms, such as YouTube, Facebook, and Reddit, as strangers that can take the hand of a teenager and guide them deeper and deeper into disturbing corners of the web. There is no “stranger danger” equivalent for a recommendation engine.