Implementing recruitment assessment models directly on candidate devices reduces the need to send personal information to cloud servers. On-device ML supports privacy preservation and inclusivity by enabling real-time, personalized evaluation with minimal exposure of sensitive data, which is particularly important for marginalized communities wary of data misuse.
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