ML model to detect malicious use of TakeTwo crowdsourced labeling

[demilolu]

Background on the problem the feature will solve/improved user experience

As an open-source, data crowdsourced solution, there is potential for malicious use/contributions

Describe the solution you'd like

Develop an ML model(s) that detects malicious use such as:

• seeking to spam
• alter what is considered by racist, by making offensive racist terms seem less racist or identifying non-racist, benign terms as racist with the intent of making the api useless (by classifying everything as racist)

Tasks

Description of the development tasks needed to complete this issue, including tests,

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.

[github-actions]

👋 Hi! This issue has been marked stale due to inactivity. If no further activity occurs, it will automatically be closed in 14 days.

[demilolu]

reopening - not yet complete.

[github-actions]

👋 Hi! This issue has been marked stale due to inactivity. If no further activity occurs, it will automatically be closed in 14 days.