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In this section, you learn the importance of building a global AI auditing framework to ensure consistent

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and fair assessment of AI systems across different regions.

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Establishing AI auditing standards and compliance measures was emphasized as crucial for maintaining

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transparency and accountability, helping to mitigate risks associated with AI deployment.

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The concept of accountability in automated decision making systems highlighted the need for clear responsibility

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channels and oversight mechanisms to oversee AI decisions.

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Enhancing AI governance with automated compliance tools was explored as a means to streamline regulatory

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adherence and monitor AI performance in real time.

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You delved into ethical dilemmas in AI governance and deployment, understanding that ethical considerations

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must be integral to the development and implementation of AI to safeguard against misuse and harm.

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The analysis of AI failures such as bias, hallucinations, and errors, underscored the necessity of

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robust testing and ongoing evaluation to identify and rectify issues promptly.

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Managing cultural and behavioural change in AI teams was discussed as vital for fostering an environment

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conducive to innovation.

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Ethical responsibility and collaboration.

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This comprehensive overview provided you with the knowledge and tools to approach AI governance with

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a holistic understanding, ensuring responsible implementation and continuous improvement of AI systems.