Content moderation systems
Systems that detect and act on policy-violating content—human+ML hybrids with appeals. Literacy on design tradeoffs, not a how-to evade.
What it is
Systems that detect and act on policy-violating content—human+ML hybrids with appeals. Literacy on design tradeoffs, not a how-to evade.
Why it matters
AI both creates moderation load and powers classifiers. Errors censor speech or leave harm up.
How it works (plain)
Policies → detectors → queues → human review → enforcement → appeals → audits for bias. Transparency reports help accountability.
Try it
Write a 5-line policy for a community forum; mark what needs humans.
Myths
- ⚠️ Myth: Full automation is neutral and complete.
- ✓ Reality: Context and culture need humans and appeals.
Sources
- Course 19 bias; Course 20 society; NIST AI RMF
- https://www.nist.gov/itl/ai-risk-management-framework ↗