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How you avoid that bias is removing ethnicity, age, and sex as parameters in the training data, but that should be fucking obvious to any data scientist with even the slightest hint of commercial awareness.

But with neural nets and so on you can't necessarily do this easily because you don't directly control what the computer factors into its decision. Removing age as a parameter is okay but the computer might still be biased to, say, long CVs, because all your employees are old and have had a lot of different jobs. Or, if all of your employees went to Eton, it might pick up on that word in the application text and weight Etonian applicants higher.

Or it might pick up on language differences between male/female/white/BAME applicants, etc.