📃
AI Big World
  • To Sort
  • Ethics
  • Amazon and Google employees oppose Project Nimbus
  • Fairness is often about consistent rules
  • Interpretable Machine Learning with Python
  • Trustworthy AI - from Trustworthy Computing
  • EU 백서
  • Reimagining Trust in AI - Jiaying Wu
  • PIPL (Personal Information Protection Law)
  • Algorithmic Accountability Act
  • Trustworthy AI: The EU's New Regulation on a European Approach on Artificial Intelligence
  • Bias
  • Racial Justice with NLP: TakeTwo - a tool to remove racial bias
  • Ethical Issues
  • GDPR
  • Google AI Principles
  • Embedded EthiCS
  • EU needs to reform GDPR to remain competitive
  • DAIG
  • AI 신뢰성
  • 인공지능 학습용 데이터 품질관리
  • 인공지능 윤리, 인공지능법 제정안
  • AI Ethics Framework
  • Z-Inspection
  • AI
    • Deep Learning for AI
    • AI & Jobs
    • XAI Tutorials
    • Tools
    • CTO Connection
    • Deidentification
    • AI
      • AI in Korea
      • AI in Taiwan
      • TensorFlow 五個範例
      • Morioh
      • Reading List
      • AI Learning Resources
      • AI Blogs & Websites
      • Interesting GAN Projects
      • Computer Vision
      • AI & Humanities
      • Reinforcement Learning
      • AI News
      • NeurIPS 2020
  • 허예찬 - RL Korea
  • AI 프렌즈
  • Neurodiversity
  • Freelance sites
  • Interpretability
  • Appropriate Technology
  • Visualization
  • AI Events
    • SNU AI Summer School
    • Untitled
    • In pursuit of interpretability
    • CVPR 2021
      • Papers
  • MLOps
    • MLOps
    • AI for Quality Inspection
    • Behavioral Testing of ML Models
Powered by GitBook
On this page

Was this helpful?

Racial Justice with NLP: TakeTwo - a tool to remove racial bias

LogoGitHub - Call-for-Code-for-Racial-Justice/TakeTwo: TakeTwo solution provides a quick and simple tool for media creators and media consumers to be more vigilant to detect and eliminate racial bias (both overt and subtle) in their contentGitHub

PreviousBiasNextEthical Issues

Last updated 3 years ago

Was this helpful?