Skip to Content
logologo
AI Incident Database
Open TwitterOpen RSS FeedOpen FacebookOpen LinkedInOpen GitHub
Open Menu
Discover
Submit
  • Welcome to the AIID
  • Discover Incidents
  • Spatial View
  • Table View
  • List view
  • Entities
  • Taxonomies
  • Submit Incident Reports
  • Submission Leaderboard
  • Blog
  • AI News Digest
  • Risk Checklists
  • Random Incident
  • Sign Up
Collapse
Discover
Submit
  • Welcome to the AIID
  • Discover Incidents
  • Spatial View
  • Table View
  • List view
  • Entities
  • Taxonomies
  • Submit Incident Reports
  • Submission Leaderboard
  • Blog
  • AI News Digest
  • Risk Checklists
  • Random Incident
  • Sign Up
Collapse

Report 1980

Associated Incidents

Incident 1446 Report
YouTube's AI Mistakenly Banned Chess Channel over Chess Language Misinterpretation

Loading...
AI mistakes ‘black and white’ chess chat for racism
independent.co.uk · 2021

Online discussions about black and white chess pieces are confusing artificial intelligence algorithms trained to detect racism and other hate speech, according to new research.

Computer scientists at Carnegie Mellon University began investigating the AI glitch after a popular chess channel on YouTube was blocked for “harmful and dangerous” content last June.

Croatian chess player Antonio Radic, who goes by the online alias Agadmator, hosts the world’s most popular YouTube chess channel, with more than 1 million subscribers.

On 28 June, 2020, Radic was blocked from YouTube while presenting a chess show with Grandmaster Hikaru Nakamura, though no specific reason was given by the Google-owned video platform.

Radic’s channel was reinstated after 24 hours, leading the chess champion to speculate that he had been temporarily banned for a referral to “black against white”, even though he was talking about chess at the time.

YouTube’s moderation system relies on both humans and AI algorithms, meaning any AI system could misinterpret the comments if not trained correctly to understand context.

“If they rely on artificial intelligence to detect racist language, this kind of accident can happen,” said Ashiqur KhudaBukhsh, a project scientist at CMU’s Language Technologies Institute.

KhudaBukhsh tested this theory by using a state-of-the-art speech classifier to screen more than 680,000 comments gathered from five popular chess-focussed YouTube channels.

After manually reviewing a selection of 1,000 comments that had been classed by the AI as hate speech, they found that 82 per cent of them had been misclassified due to the use of words like “black”, “white”, “attack” and “threat” – all of which commonly used in chess parlance.

The paper was presented this month at the Association for the Advancement of AI annual conference.

Read the Source

Research

  • Defining an “AI Incident”
  • Defining an “AI Incident Response”
  • Database Roadmap
  • Related Work
  • Download Complete Database

Project and Community

  • About
  • Contact and Follow
  • Apps and Summaries
  • Editor’s Guide

Incidents

  • All Incidents in List Form
  • Flagged Incidents
  • Submission Queue
  • Classifications View
  • Taxonomies

2024 - AI Incident Database

  • Terms of use
  • Privacy Policy
  • Open twitterOpen githubOpen rssOpen facebookOpen linkedin
  • e1b50cd