ML Systems for Identifying Harmful Content

Requirements Clarification & Assessment

1. End Goal:

   • Objective: The primary goal is to identify and manage harmful content effectively, ensuring compliance with content regulations and maintaining a safe environment for users.
   • Content Types: Clarify the types of harmful content to be detected, such as hate speech, violent imagery, sexually explicit content, etc.
   • Action Post-Detection: Decide whether content should be automatically removed or flagged for human review. Consider the balance between automation and human intervention.

2. Content Scope:

   • Media Types: Determine whether the focus is on text, images, videos, or a combination. Each media type may require different models and approaches.
   • Geographical Scope: Define the regions or countries where the system will operate, considering local regulations and cultural differences.

3. Operational Requirements:

   • Service Level Agreement (SLA): Establish a timeline for action post-detection, e.g., content must be flagged and removed within 5 minutes of posting.
   • User Experience: Ensure the system minimizes false positives to prevent unnecessary user inconvenience.

4. Legal and Ethical Considerations:

   • Compliance: Ensure adherence to privacy laws and content regulations across different jurisdictions.
   • Bias and Fairness: Address potential biases in training data to prevent unfair treatment of any group.