Researchers from the University of Cornell discovered that artificial intelligence systems designed to identify offensive “hate speech” flag comments purportedly made by minorities “at substantially higher rates” than remarks made by whites.
Several universities maintain artificial intelligence systems designed to monitor social media websites and report users who post “hate speech.” In a study published in May, researchers at Cornell discovered that systems “flag” tweets that likely come from black social media users more often, according to Campus Reform.
The study’s authors found that, according to the AI systems’ definition of abusive speech, “tweets written in African-American English are abusive at substantially higher rates.”
The study also revealed that “black-aligned tweets” are “sexist at almost twice the rate of white-aligned tweets.”
The research team averred that the unexpected findings could be explained by “systematic racial bias” displayed by the human beings who assisted in spotting offensive content.
Stacey Abrams hit with subpoena in alleged campaign finance violations saga: ‘No one is above the law’
Members of Congress using online prediction markets? Don’t bet on it
Breaking: UAE Has Been Secretly Striking Iran, Fighting Alongside US and Israel
John Cornyn under fire from MAGA base over anti-Trump post
San Antonio Spurs Superstar Ejected After Vicious Hit – Should the NBA Suspend Him?
Trump ‘seriously considering’ plan to make Venezuela and its $40 trillion in oil permanent part of USA
Watch: Military Veteran Scores the Biggest Payday in ‘Price Is Right’ History
Mega-mansion built on Manson murder site now a luxury rental after years of failing to find buyer
Unions’ ‘Astonishing’ Attack Ad Against LA Republican Spencer Pratt Actually Helps His Case
Maine progressive says he won’t back Schumer even after Democrats unite behind Collins challenger
Trump Scorches 2 SCOTUS Justices by Name: ‘Democrats don’t really need to “PACK THE COURT”‘
More than 25 charged in nationwide Tren de Aragua crackdown involving guns, drugs and cash
Watch: Trump Blasts NFL Over Possible Amazon, Netflix Deal – Says Many Fans ‘Don’t Make Enough Money to Pay’
ActBlue scrutiny fuels new GOP bills to tighten election donation rules
Alabama AG makes Supreme Court play that could deal decisive blow in redistricting war
“The results show evidence of systematic racial bias in all datasets, as classifiers trained on them tend to predict that tweets written in African-American English are abusive at substantially higher rates,” reads the study’s abstract. “If these abusive language detection systems are used in the field they will, therefore, have a disproportionate negative impact on African-American social media users.”
One of the study’s authors said that “internal biases” may be to blame for why “we may see language written in what linguists consider African American English and be more likely to think that it’s something that is offensive.”
Automated technology for identifying hate speech is not new, nor are universities the only parties developing it. Two years ago, Google unveiled its own system called “Perspective,” designed to rate phrases and sentences based on how “toxic” they might be.
Shortly after the release of Perspective, YouTube user Tormental made a video of the program at work, alleging inconsistencies in implementation.
According to Tormental, the system rated prejudicial comments against minorities as more “toxic” than equivalent statements against white people.
Google’s system showed a similar discrepancy for bigoted comments directed at women versus men.
Story cited here.
