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Generative AI Literacy for FE Staff

At the start of the year, we asked for volunteers to join a working group to explore FE AI literacy, with the group deciding to focus specifically on generative AI literacy. The aim is to provide staff with reference for their journey to becoming literate with generative AI. In our previous blog post, we discussed the initial steps of our journey, including reviewing preliminary definitions and considering the AI Skills for Business Competency Framework. You can read more about that process in our blog post: Update on FE AI literacy working group.

 

Since then, we have made significant progress and are now ready to share the final definition of generative AI literacy for FE staff. Our focus has been on ensuring that this definition is comprehensive and accessible to all staff, not just those in teaching roles. We chose to focus our definition at a fundamental level to provide a strong foundation with generative AI literacy. 

Generative AI literacy: Fundamental level

Introduction 

Generative AI is a type of artificial intelligence that can create content like text, images, or code. These four steps aim to provide a fundamental level of generative AI literacy – to develop professional practice and support learners effectively. 

Generating relevant content efficiently: The first step is knowing how to use AI to produce content that meets specific requirements. It requires awareness of the variety of AI technologies available and the ability to select the most appropriate tool for a given task. This skill set also includes knowing where to look for information and how to use generative AI tools to create useful and relevant outputs.

Understanding generative AI’s foundations: Secondly, we recommend understanding the basics of how generative AI systems operate. This includes recognising the capabilities and limitations of generative AI. This knowledge allows individuals to effectively use these tools, grasping their strengths and limits, which is vital for realistic applications and expectations of generative AI across tasks.

Responsible generative AI use: The third and fundamental step is knowing how to use generative AI safely, ethically and responsibly. This includes understanding the importance of respecting consent, privacy, and data security at both ends of using AI: prompts and output.

Critically evaluating generative AI outputs: Lastly, it is important to be able to assess and critically evaluate the outputs produced by generative AI systems. This involves discerning the accuracy, relevance, and potential biases in the information or content created by generative AI. It also includes the ability to identify errors or inaccuracies that may arise due to the limitations of the generative AI system being used. This skill is crucial for ensuring that the use of generative AI does not compromise the quality and integrity of decisions or content. 

Contributors:

Bryony Evett – Coleg Sir Gar

Roddy Peters – Windsor Forest Colleges Group

Michele Smith – UHI Moray

Mark Ludlam – Gower College Swansea

Sylvia Davies – Grŵp Llandrillo Menai

Rebena Sanghera – World Skills UK

Claudia Boerescu – Newham College

Sue Attewell – Jisc

Paddy Shepperd – Jisc

James Hodgkinson – Jisc

What’s next?

The working group feels that the natural next step is to create a generative AI literacy definition for learners. We will publish our progress and invite thoughts and feedback.

 


Find out more by visiting our Artificial Intelligence page to view publications and resources, join us for events and discover what AI has to offer through our range of interactive online demos.

For regular updates from the team sign up to our mailing list.

Get in touch with the team directly at AI@jisc.ac.uk

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