Fairness - This is the correct answer. To address the issue of the recruitment system consistently selecting candidates from a single demographic group, the development team should focus on fairness. Fairness ensures that the AI system treats all candidates equitably, regardless of their demographic group, and reduces bias in decision-making.
Inclusiveness is about ensuring that diverse perspectives are considered during the development process and that AI systems are accessible to all groups. While important, it is a broader concept and does not directly address the specific issue of bias in selection leading to a lack of diversity.
Transparency refers to making the AI model’s decision-making process understandable and visible to stakeholders. While transparency is important, fairness is the key principle for addressing the lack of diversity in candidate selection.
Accountability involves ensuring that there is oversight and responsibility for the outcomes of AI systems. While important, accountability alone does not directly address the bias in selection processes; fairness is the principle most relevant to correcting this issue.
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Microsoft Azure AI Fundamentals AI-900
Describe Artificial Intelligence Workloads and Considerations
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