Call-for-Code-for-Racial-Justice / Call-for-Code-for-Racial-Justice/TakeTwo-DataScience

ML model to debias biased content

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#20 4 則留言 0 個 reaction 已指派 0 人 在 GitHub 檢視
design-thinking Machine Learning
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

開啟貢獻指南

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

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