HardTechnical screen20 min to answer

How would you build an evaluation suite for content moderation?

1Give yourself 20 minutes

2Answer out loud, not in your head

3Then compare with the answer below

Stuck? Show a way to structure it+

01Clarify objective, users, constraints, and failure tolerance.
02Cover policy taxonomy, multilingual coverage, appeals, adversaries in a causal structure.
03Compare at least two credible approaches.
04Specify evaluation, rollout, monitoring, and rollback.

Reference answer

strong answer

I would begin by defining the target outcome and acceptable failure boundary. For content moderation: evaluation, I would analyze policy taxonomy, multilingual coverage, appeals, adversaries, compare alternatives on quality, latency, cost, and risk, and validate on representative slices before a monitored rollout.

policy taxonomy
multilingual coverage
appeals
adversaries

Requires scenario-specific numbers
Should include relevant personal experience

alternative answer

I would start with the riskiest assumption in content moderation: evaluation, create the cheapest discriminating experiment, then use the evidence to choose an architecture and release threshold.

experimentation
risk-first sequencing
decision clarity

Needs deeper implementation detail

Grade yourself

policy taxonomy

weight 30%

StrongExplains policy taxonomy with mechanisms, trade-offs, and validation.

WeakNames policy taxonomy without operational implications.

multilingual coverage

weight 25%

StrongExplains multilingual coverage with mechanisms, trade-offs, and validation.

WeakNames multilingual coverage without operational implications.

appeals

weight 25%

StrongExplains appeals with mechanisms, trade-offs, and validation.

WeakNames appeals without operational implications.

adversaries

weight 20%

StrongExplains adversaries with mechanisms, trade-offs, and validation.

WeakNames adversaries without operational implications.

Then expect these follow-ups

Which assumption is most likely to invalidate your approach?
Tests: depth
What would you measure offline and in production?
Tests: evaluation
How would your answer change with one-tenth the data or compute?
Tests: adaptability

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