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In this section, you learn to scope AI projects by identifying key objectives, ensuring a clear understanding

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of project goals, and aligning them with strategic business priorities.

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You explored how to map AI risks by identifying potential internal and external threats, emphasizing

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the importance of a proactive approach to risk assessment.

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Developing risk mitigation strategies for AI projects was highlighted where you learned to devise comprehensive

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plans to address identified risks ensuring robust and resilient AI implementations.

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You gained insights into constructing a harms matrix for AI risk assessment, a crucial tool for systematically

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evaluating the potential negative impacts of AI systems.

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Conducting algorithm impact assessments was another focus, where you learned to analyze the broader

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implications of AI algorithms on stakeholders and society.

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Engaging stakeholders in AI risk management was underscored, emphasizing the necessity of involving

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diverse perspectives to enhance the robustness and ethical soundness of AI projects.

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Moreover, the importance of data provenance, lineage, and accuracy in AI systems was discussed,

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ensuring that data integrity and reliability are maintained throughout the AI lifecycle.

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Overall, this section equipped you with a holistic understanding of managing AI projects, from scoping

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and risk assessment to stakeholder engagement and data management, providing a foundation for implementing

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responsible and effective AI solutions.