Explanation of the triple safeguard mechanism
The system has established a comprehensive quality control system to address possible bias in AI scoring:
- Algorithmic transparency: Each rating comes withDetailed Explanatory Report, e.g. 'Language score 8.5: 5 technical terms are used, but there are 2 grammatical errors'
- Manual calibration channel: HR is available at all timesModification of score weightsThe system records these adjustments for model iteration.
- Deviation Detection System: Built-in fairness algorithms flag assessments that may have gender/race-sensitive terminology
In the transnational use case, the platform is used throughLocalized assessment modelsAddressing cultural differences. For example, when evaluating Japanese candidates, the weighting of demerit points for direct negatives is reduced. Testing showed that after 3 months of calibration, the system's rate of difference in scoring candidates of different ethnicities decreased from 151 TP3T to 3.21 TP3T.
This answer comes from the articleEquip AI Interviews: automate candidate interview screeningThe
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