Call-for-Code-for-Racial-Justice / Call-for-Code-for-Racial-Justice/TakeTwo-DataScience
ML model to debias biased content
- 主要語言
- Jupyter Notebook
- 星號
- 8
- 分支
- 8
- PR 合併指標
- 30 天內沒有已合併 PR
描述
### Background on the problem the feature will solve/improved user experience
People who use TakeTwo might not only want to detect racially biased content but receive help on how to debias their content.
### Describe the solution you'd like
Machine learning models that are able to debias content that is found to be racially biased.
### Tasks
- Confirm this is a real painpoint for others
- gather datasets
- experiments
- TBD
### Acceptance Criteria
Standards we believe this issue must reach to be considered complete and ready for a pull request. E.g precisely all the user should be able to do with this update, performance requirements, security requirements, etc as appropriate.
貢獻指南
研究方向
未指定任何檔案、測試或進入點。先確認問題所在,並定義「debias」應代表什麼,接著找出合適的資料集與實驗。只有在具體的驗收標準描述使用者可見的行為與評估需求後,該 Issue 才算完成。
由索引模型根據 Issue 內容生成。
評估
- 技術堆疊
- jupyter-notebook, machine-learning
- 領域
- data, machine-learning
- Issue 類型
- 功能
- 難度
- 5/5
- 預估耗時
- 一週以上
- 活躍度
- 停滯
- 描述清晰度
- 需要釐清
- 新手友好度
- 18/100