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ReportI'm currently working on integrating AI-driven customer scoring features within AI in Dynamics 365 (Sales + Customer Insights) and need to ensure that the predictions align with Responsible AI principles.
While configuring the AI models, I’ve noticed inconsistencies in how certain customer segments are being scored—specifically when demographic attributes are indirectly influencing AI predictions, even though those fields are not explicitly used.
While configuring the AI models, I’ve noticed inconsistencies in how certain customer segments are being scored—specifically when demographic attributes are indirectly influencing AI predictions, even though those fields are not explicitly used.
Here are the technical challenges I'm facing:
1. How can I identify hidden or proxy bias within the AI models used by Dynamics 365 (especially those built using Customer Insights or custom Azure ML models)?
2. What is the recommended approach to disable or replace data attributes that may unintentionally skew model outcomes?
3. How can I validate prediction accuracy regularly and enforce monitoring to ensure AI outputs remain compliant with Responsible AI guidelines?
If anyone has implemented Responsible AI practices inside Dynamics 365 or integrated the Azure Responsible AI ecosystem with D365, I’d really appreciate guidance, example setups, or recommended best practices.
Thanks in advance!
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