Block, Siteadmin, SkipCaptcha, Upload, Automoderated users, delete, edit, move, nsTeam2RO, nsTeam2RW, nsTeam2_talkRO, nsTeam2_talkRW, protect, rollback, Administrators, template
293,094
edits
Changes
Jump to navigation
Jump to search
Line 52:
Line 52: − +
→Hate speech
===Hate speech===
===Hate speech===
''[[Vox]]'' Recode reported: {{Facebook, YouTube, and Twitter are banking on developing [[artificial intelligence]] technology to help stop the spread of hateful speech on their networks. The idea is that complex algorithms that use natural language processing will flag [[racist]] or [[violent]] speech faster and better than human beings possibly can. Doing this effectively is more urgent than ever in light of recent mass shootings and violence linked to hate speech online.
''[[Vox]]'' Recode reported: {{quotebox|Facebook, YouTube, and Twitter are banking on developing [[artificial intelligence]] technology to help stop the spread of hateful speech on their networks. The idea is that complex algorithms that use natural language processing will flag [[racist]] or [[violent]] speech faster and better than human beings possibly can. Doing this effectively is more urgent than ever in light of recent mass shootings and violence linked to hate speech online.
But two new studies show that AI trained to identify [[hate speech]] may actually end up amplifying racial bias. In one study, researchers found that leading AI models for processing hate speech were one-and-a-half times more likely to flag tweets as offensive or hateful when they were written by [[African American]]s, and 2.2 times more likely to flag tweets written in African American English (which is commonly spoken by black people in the US).<ref>https://www.vox.com/recode/2019/8/15/20806384/social-media-hate-speech-bias-black-african-american-facebook-twitter</ref>}}
But two new studies show that AI trained to identify [[hate speech]] may actually end up amplifying racial bias. In one study, researchers found that leading AI models for processing hate speech were one-and-a-half times more likely to flag tweets as offensive or hateful when they were written by [[African American]]s, and 2.2 times more likely to flag tweets written in African American English (which is commonly spoken by black people in the US).<ref>https://www.vox.com/recode/2019/8/15/20806384/social-media-hate-speech-bias-black-african-american-facebook-twitter</ref>}}