The increasing popularity of the concept of responsible AI has sparked discussions about it in various contexts. The terms accountability, ethicality, transparency and fairness have been repeatedly discussed as elements of responsible AI. Within the discussions, the definition of the concept of responsible AI has been broadly applied. Considering the variety of GenAI tools, their multifarious capabilities, and the different contexts in which they are used, there is a need for contextually relevant definitions of GenAI-related concepts, such as responsible AI. As what is responsible AI in one context or for one stakeholder may not be the same for another, this paper aims to provide a contextually relevant definition of responsible AI in the Australian Higher Education sector. Through the application of LLMs such as NotebookLM and AI-powered NVivo, the meanings attributed to responsible AI in datasets within the Tertiary Education Quality and Standards Agency (TEQSA) AI Knowledge Hub and those submitted to the Senate Inquiry on the Adoption of AI are analysed. Findings separate the meaning of accountability into developer responsibility, government responsibility, deployer responsibility and user responsibility. Ethical usage means alignment with Australian values, equitable access to GenAI tools and sustainable usage. Fairness is seen as AI safety for all, avoiding bias or discrimination by GenAI Tools, and ensuring a balance of interests for all parties impacted by GenAI decisions. The meaning attributed to transparency is providing clear information and full disclosure of GenAI usage and explaining processes of GenAI functionalities, capabilities and usage.