Skip to Content
Silicon Valley

Google’s algorithm for detecting hate speech is racially biased

August 13, 2019
A man holds a smartphone
A man holds a smartphoneGetty

AI systems meant to spot abusive online content are far more likely to label tweets “offensive” if they were posted by people who identify as African-American.

The news: Researchers built two AI systems and tested them on a pair of data sets of more than 100,000 tweets that had been annotated by humans with labels like “offensive,” “none,” or “hate speech.” One of the algorithms incorrectly flagged 46% of inoffensive tweets by African-American authors as offensive. Tests on bigger data sets, including one composed of 5.4 million tweets, found that posts by African-American authors were 1.5 times more likely to be labeled as offensive. When the researchers then tested Google’s Perspective, an AI tool that the company lets anyone use to moderate online discussions, they found similar racial biases.

A hard balance to strike: Mass shootings perpetrated by white supremacists in the US and New Zealand have led to growing calls from politicians for social-media platforms to do more to weed out hate speech. These studies underline just how complicated a task that is. Whether language is offensive can depend on who’s saying it, and who’s hearing it. For example, a black person using the “N word” is very different from a white person using it. But AI systems do not, and currently cannot, understand that nuance.

The risk: By rushing to use software to automatically weed out offensive language, we risk silencing minority voices. Moderating online content is a traumatizing, difficult job, so tech companies are keen to rely on AI systems instead of human beings (they’re also much cheaper). This study shows the huge risks inherent in that approach.

Sign up here for our daily newsletter The Download to get your dose of the latest must-read news from the world of emerging tech.

Keep Reading

Most Popular

10 Breakthrough Technologies 2024

Every year, we look for promising technologies poised to have a real impact on the world. Here are the advances that we think matter most right now.

Scientists are finding signals of long covid in blood. They could lead to new treatments.

Faults in a certain part of the immune system might be at the root of some long covid cases, new research suggests.

AI for everything: 10 Breakthrough Technologies 2024

Generative AI tools like ChatGPT reached mass adoption in record time, and reset the course of an entire industry.

What’s next for AI in 2024

Our writers look at the four hot trends to watch out for this year

Stay connected

Illustration by Rose Wong

Get the latest updates from
MIT Technology Review

Discover special offers, top stories, upcoming events, and more.

Thank you for submitting your email!

Explore more newsletters

It looks like something went wrong.

We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at customer-service@technologyreview.com with a list of newsletters you’d like to receive.