Responsible AI refers to the practical implementation of principles and processes that ensure AI systems are designed, developed, and deployed in ways that are accountable, transparent, and aligned with regulations and societal values. It emphasizes risk management, compliance, and monitoring AI systems throughout their lifecycle.
Examples:
- Auditing an AI hiring system to ensure it doesn’t discriminate against any demographic group.
- Implementing explainability tools to help doctors understand how an AI diagnosed a patient.
- Regularly updating an AI-powered chatbot to address biases or inaccuracies in its responses.
While Ethical AI defines the vision and values, Responsible AI focuses on putting those principles into action to ensure safe and trustworthy AI in real-world use.