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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.

H2O.ai's AI governance with H2O Hydrogen Torch​

H2O.ai'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 H2O.ai'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 content of the guide, H2O Hydrogen Torch can help with AI governance in one of the following ways:

  1. Interpretability: H2O Hydrogen Torch offers a Grad-Cam to shed light on the decision-making process of image classification models. Grad-CAM pinpoints the image regions that influenced the model's prediction, fostering trust and transparency. This enhances interpretability, a vital aspect of AI governance, as it helps build trust and ensure AI systems align with organizational values and expectations. By providing clear explanations, organizations can maintain accountability and oversight in AI deployments. Interpretability is a crucial component of responsible AI and an integral part of AI governance frameworks.

  2. Model selection and promotion: H2O Hydrogen Torch can be used to validate model selection or promotion. By comparing the performance of different models on various datasets, organizations can ensure that the chosen model is robust, reliable, and fair, thereby promoting better governance.

  3. Hyperparameter tuning: H2O Hydrogen Torch allows users to experiment with hyperparameters to tune model performance quickly. This can lead to more accurate models, an essential aspect of AI governance, as accurate models tend to make better decisions and reduce the risk of undesirable outcomes.

H2O Hydrogen Torch can help organizations implement AI governance by improving model interpretability, selecting and promoting models, and facilitating hyperparameter tuning.

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