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AI governance

What is AI governance?

AI Governance is the set of frameworks, rules, and best practices to ensure responsible adoption and usage of artificial intelligence. This framework encourages organizations to curate and use bias free data, consider societal and end-user impact, and produce unbiased models; the framework also enforces controls on model progression through deployment stages. AI Governance is critical for organizations to realize the maximum value out of AI projects while mitigating risks. It enables organizations to not only develop AI projects in a responsible way, but also ensure that there is consistency and transparency across the entire organization.'s AI governance with H2O AutoInsights's AI governance framework recommends four stages and a total of 11 topics. Organizations are encouraged to adopt the topics and processes most relevant to their unique needs. The's AI governance framework is discussed in the following guide: Guidelines for Effective AI Governance with Applications in H2O AI Cloud.

For example, based on the guide's content, H2O AutoInsights is a valuable tool for AI Governance as it enables organizations to ensure data quality, privacy, and security while promoting collaboration and communication between different teams. By adhering to these best practices, organizations can develop responsible AI that aligns with regulatory and industry standards.

In particular, H2O AutoInsights can help with AI governance in one of the following ways:

  1. Data quality assurance: H2O AutoInsights can help ensure data accuracy, completeness, and consistency by providing statistical and machine learning analyses that detect data anomalies, outliers, and missing values. By identifying and addressing these issues, organizations can improve the quality of their data, which is critical for building accurate and reliable AI models.
  2. Data privacy and security: H2O AutoInsights can help organizations adhere to data protection regulations by providing tools for anonymizing or pseudonymizing sensitive data. This feature is essential for protecting individuals' privacy and complying with data protection laws such as the General data protection regulation (GDPR) and the California consumer privacy act (CCPA).
  3. Thorough data exploration: H2O AutoInsights provides visualization tools for in-depth data exploration, enabling data scientists, domain experts, and stakeholders to gain insights and detect anomalies. By promoting collaboration and communication between different teams, organizations can ensure a shared understanding of data implications and make informed decisions regarding AI development.
  4. Regular auditing: H2O AutoInsights can help organizations conduct periodic audits to ensure compliance with governance policies and regulations. Organizations can demonstrate transparency and accountability in their AI development processes by maintaining clear records of data sources, transformations, and preprocessing steps.