Abstract

The emergence and popularity of private generative AI models such as ChatGPT have the potential to empower research managers by automating manual and time consuming tasks. By embracing Generative AI, RMAs have the potential to upskill, establish more efficient ways of working and contribute to the sustainability of our careers.

However, there is a lack of clarity on the ethical uses of these tools and guidance on how to use them without unwittingly jeopardising intellectual property, privacy and succumbing to the inherent biases of these models.

The poster will propose guidance to aid decision-making to evaluate and mitigate the risks associated with the use of private generative AI models in research development.

The guide will enable RMAs to assess different factors, including data privacy, model transparency, potential biases, and environmental impacts. The aim is to guide RMAs to identify and help address potential risks when considering the use of private Generative AI models in their day-to-day work.

By addressing these factors, the poster aims to promote the responsible use of AI in research management, fostering an environment where innovation is balanced with ethical considerations and risk management.

The proposed guidance will be validated through a case study of using a private Generative AI model (ChatGPT/Mistral) in proposal development to ensure its practical applicability and effectiveness in real-world scenarios.

This work contributes to the broader discussion on responsible AI in research management and provides a practical framework for navigating the complex landscape of AI integration into research management. It is anticipated that this guidance will be a valuable resource for research managers attending the INORMS 2024 conference, facilitating informed decision-making and responsible AI adoption.