In this section, you learn to scope AI projects by identifying key objectives, ensuring a clear understanding
of project goals, and aligning them with strategic business priorities.
You explored how to map AI risks by identifying potential internal and external threats, emphasizing
the importance of a proactive approach to risk assessment.
Developing risk mitigation strategies for AI projects was highlighted where you learned to devise comprehensive
plans to address identified risks ensuring robust and resilient AI implementations.
You gained insights into constructing a harms matrix for AI risk assessment, a crucial tool for systematically
evaluating the potential negative impacts of AI systems.
Conducting algorithm impact assessments was another focus, where you learned to analyze the broader
implications of AI algorithms on stakeholders and society.
Engaging stakeholders in AI risk management was underscored, emphasizing the necessity of involving
diverse perspectives to enhance the robustness and ethical soundness of AI projects.
Moreover, the importance of data provenance, lineage, and accuracy in AI systems was discussed,
ensuring that data integrity and reliability are maintained throughout the AI lifecycle.
Overall, this section equipped you with a holistic understanding of managing AI projects, from scoping
and risk assessment to stakeholder engagement and data management, providing a foundation for implementing
responsible and effective AI solutions.