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title: "AI and Compliance- Bias and Fairness"
canonical: "https://support.mercell.com/space/MSF/196215505062/AI%20and%20Compliance-%20Bias%20and%20Fairness"
format: markdown
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### Finnish Coming Soon

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# 🇬🇧 AI and Compliance- Bias and Fairness

### Bias Mitigation


**What steps are being taken to identify and mitigate any biases in the AI model’s training data and outputs?**

To identify and mitigate biases, the following steps will be taken:

- **Data Diversity:** Ensuring that the training data includes a diverse range of tenders from various sectors and regions to prevent skewed outputs.
- **Regular Updates:**Regularly updating the training data to include new and varied tenders, reducing the risk of outdated or biassed information.
- **Human Oversight: **Incorporating human oversight in the review process to catch and address any biases that automated tools might miss.