WATCHLINEAI PROCTORING · CASE 01
Illustrative classroom data

One exam. Two kinds of fairness.

To catch a cheater,
should we watch everyone?

You are the student being watched. Configure a policy and see what higher detection asks you to give up.

Configure a policy
Live simulation CAM 04 · 10:16:05
Live ethics readoutBalanced policy
Cheating detection76%Potential violations found
False-flag rate17%Normal behaviour flagged
Privacy retained49%Personal space not collected
Current readingHuman review required

Detection improved, but false flags and privacy costs can no longer be ignored.

Accuracy is never free

When surveillance grows,
who pays the price?

Choose a policy, or adjust your own above. These illustrative values show the direction of a trade-off; they are not product claims.

Cheating detectionEthical cost
Level of impactPermissions and sensitivity →

Return the decision to people

Would you approve this policy?

The question is not only whether a school can do this, but whether it should.

Choose a position to reveal a classroom discussion prompt.