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Description

The study explores translating ethical principles, such as fairness, into practical AI governance processes. The research focuses on defining AI governance at the organizational level and its integration into the existing governance structure alongside corporate governance, IT governance, and data governance. By investigating these aspects, the paper aims to lay the foundation for comprehensive AI governance frameworks and facilitate the implementation of responsible AI practices across organizations.   We evaluate a set of open-source LLMs by prompting them with various tasks and measuring the time taken to generate responses. Additionally, we assess their ability to maintain coherence and relevance to the provided context through qualitative analysis. Our findings aim to provide developers and researchers with insights into the trade-offs between speed and context-awareness when choosing open-source LLMs for their applications.   Defining Organizational AI Governance" delves into the critical need for robust AI governance frameworks within organizations to effectively manage the advantages and risks associated with AI systems.