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Promoting fairness by removing bias in automation

Promoting fairness by removing bias in automation

You rely on automation, rules, and models in key business processes.

They should not get in the way of treating your customers fairly.

Race, gender, age and other personal characteristics are not fair game.

Including them in decisions can be prejudicial.


Whether you have simple rules, or more complex models, you need to ensure that they are bias free. 

  • How can you be sure that you have identified all sources of potential bias?

  • Have you considered proxy indicators and free text fields?

  • How can you trust that your customers are being treated fairly?


That's where we come in.

We review your rules and models for bias, at various levels of depth (depending on their nature).

Ensuring you can trust that your automation does not promote unfair results.

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