Definition
Governance for LLMs refers to the establishment of policies, processes, and controls to manage the development, deployment, and use of large language models responsibly and effectively. It ensures that LLMs align with organizational objectives, ethical standards, and regulatory requirements throughout their lifecycle. This involves defining roles and responsibilities, implementing risk assessment frameworks, and establishing monitoring mechanisms to track performance and identify potential issues. Implementing robust governance is crucial for mitigating risks such as bias, data privacy violations, and security vulnerabilities, thereby fostering trust and ensuring the reliable application of AI. For instance, a financial institution might implement governance to ensure its LLM used for customer service adheres to strict data protection laws and provides accurate, unbiased financial advice. This differs from simple model validation which focuses solely on technical performance metrics. Concepts of LLM governance are increasingly appearing in advanced AI and cybersecurity certification domains.