Responsible AI Best Practices

As an aspiring responsible AI practitioner, ensuring the safe application and use of AI to meet enterprise goals and improve workflow is paramount. Developing AI systems can be tedious, but whether you plan to adopt traditional or generative AI, incorporating responsible AI at every step is critical. One thing I have found resourceful is that the safe application of AI should always be a top priority. Responsible AI initiative emphasizes practices and principles ensuring AI systems are transparent, reliable, and trustworthy, mitigating potential risks and adverse outcomes. These standards should be implemented throughout the entire AI application lifecycle, including the design, development, deployment, monitoring, and evaluation phases.

The eight core dimensions of responsible AI are transparency, privacy and security, safety, governance, fairness, explainability, veracity and robustness, and controllability. Adopting these dimensions helps build AI systems that stakeholders can trust and rely upon. Additionally, AI service cards are valuable tools for understanding the wide variety of stakeholders and considerations in responsible AI design and implementation and ensuring best practices. These cards cover four fundamental sections: understanding service features, use cases and limitations, responsible AI design considerations, and guidance on deployment and performance optimization. By leveraging AI service cards, practitioners can ensure a comprehensive approach to responsible AI, aligning their systems with best practices and fostering a trustworthy AI environment.

Dr. Vincent Njoku