As organizations become more data-driven and rely more on AI, ensuring that the AI can be trusted becomes increasingly important. Steps that organizations can take to ensure that the AI they rely on can be trusted are:
- Transparent and Explainable: The AI models should be transparent and explainable so that people can understand how the models make decisions. It is important to ensure that the AI models are not black boxes that cannot be understood or explained.
- Data Quality and Bias: The quality of data used to train the AI models should be high, and the data should be free from biases. Organizations should take measures to identify and mitigate any biases in the data to ensure that the AI models do not contain and maintain any biases.
- Testing and Validation: AI models should be tested and validated to ensure that they are reliable and accurate. Organizations should invest in testing and validation methods to ensure that the AI models perform as expected.
- Ethical and Legal Considerations: AI models should be developed and deployed in accordance with ethical and legal considerations. Organizations should consider the potential impact of AI models on people, society, and the environment, and ensure that the AI models are developed and deployed in an ethical and responsible manner.
- Human Oversight: Finally, organizations should ensure that there is human oversight of the AI models. Humans should have the final say in decisions made by the AI models, and the AI models should not be used to replace human decision-making entirely.
At Nubovi we continuously stay focused on all the above aspects. It is fully embedded in our code of conduct. With regard to the last bullet point: we do not automatically execute our recommendations; it always requires a human at your organization to implement them, by following the easy to execute steps in our recommendations.
To learn more about how the advanced machine learning models of Nubovi can help you control and forecast cloud spend, and helps you improve it using our recommendation engine, have a look at our white paper or watch this short explainer video.