In this section, you learned about the pivotal methods and tools for conducting AI audits, ensuring
compliance and ethical standards are met.
You explored various approaches to evaluate AI's societal impact through metrics and methodologies designed
to quantify both positive and negative outcomes.
The importance of tracking AI system performance post-deployment was emphasized, highlighting the need
for continuous monitoring to maintain efficacy and safety.
You examine strategies for remediating AI system failures and mitigating negative impacts, focusing
on proactive and reactive measures to address issues as they arise.
Additionally, the lessons covered effective ways to report and communicate AI system risks to stakeholders,
stressing transparency and clarity in conveying potential challenges and solutions.
You learned how to create ethical AI impact reports that thoroughly inform stakeholders about the AI's
performance implications and areas for improvement.
Preparing AI systems for continuous evaluation and updates was also discussed, underscoring the necessity
of adaptability in evolving technological landscapes.
Overall, these lessons equipped you with comprehensive knowledge and practical skills for managing
AI systems responsibly.
You now understand the critical importance of ongoing assessment, clear communication, and ethical
considerations in the life cycle of AI technologies.
This foundation enables you to contribute to the development and deployment of AI systems that are both
innovative and aligned with societal values.