Fillerguy
Veteran
Google's hate speech-detecting AI is biased against black people
The scientists examined how humans had annotated a database of over 100,000 tweets that had been used to train anti-hate speech algorithms, according to yet-unpublished research. They found that the people responsible for labeling whether or not a tweet was toxic tended to flag tweets written in African-American Vernacular English (AAVE) as offensive — a bias that then propagated down into the algorithms themselves
The team then tested algorithms, including Perspective, on a database of 5.4 million tweets, the authors of which had disclosed their race. The algorithms ranged from being one-and-a-half to twice as likely to flag posts written by people who identified as African-American in the database for being toxic, New Scientist reports.
That means that automated content moderation tools will likely take down a lot of benign posts based on the ethnicity of their posters, leading to silencing and suppression of certain communities online.
The team then tested algorithms, including Perspective, on a database of 5.4 million tweets, the authors of which had disclosed their race. The algorithms ranged from being one-and-a-half to twice as likely to flag posts written by people who identified as African-American in the database for being toxic, New Scientist reports.
That means that automated content moderation tools will likely take down a lot of benign posts based on the ethnicity of their posters, leading to silencing and suppression of certain communities online.
