Musubi Resources:
Insights & Best Practices
How to audit your fixed ML classifier
Four signs that a fixed ML Classifier might not be working for your Trust & Safety operations. What the symptoms are, how to diagnose, and what might work instead.
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How Feeld used AiMod to block scams faster
Dating app case study: How Feeld's moderation team makes 500x faster decisions with 89% fewer mistakes. Covers bot detection, automation, and human-in-the-loop systems.
The Future of T&S is Better Collaboration
Most companies treat T&S like a cost center staffed by disposable contractors. Here's how to position T&S as strategic partners: building exec relationships, demonstrating ROI, and creating collaborative workflows with product/legal/ops. Includes implementation playbook.
Can LLMs moderate nuanced policies?
With strong prompts and diverse training data, LLMs can distinguish harassment from banter, sexual content from sex ed, and satire from hate speech. Requires context examples, edge case coverage, policy engineering, and human calibration. Practical guide with real examples.
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