AI in Education Community

Update on FE AI literacy working group

AI is of course much more than just generative AI, and a full discussion around AI literacy would need to cover more traditional AI uses too, for example predictive models, adaptive learning, image recognition, recommendation engines and many other tools and techniques.  Generative AI is the hot topic now though, so the groups discussion focused on AI literacy around generative AI.

We started by reviewing some strawman definitions created by ChatGPT, Copilot and Google Gemini and Jisc to kickstart our discussion.   We focused on what was important to include for all FE staff.

We discussed the need to differentiate between expected levels of ability and one of the options was the AI Skills for Business Competency Framework as a useful way of segmenting skills needs within our sector:

  • AI Citizen – core skills that everyone needs.
  • AI worker – skills for those expected to use generative AI tools to as an augmentation tool
  • AI professional – skills for those whose core responsibilities include data and AI

We agreed from this that we would initially focus on the definition of AI literacy for generative AI at the basic level, an approach we thought would work for all staff, and should not be limited to teaching staff.

We tried to focus on keeping things simple and clear rather than overly technical and came up with the below draft for feedback.

AI Literacy for Generative AI: Basic Level

Generating Relevant Content Efficiently: This involves understanding how to leverage generative AI tools 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: AI literacy requires a foundational knowledge 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: A fundamental component of AI literacy is the ability to use generative AI technologies in a safe and responsible manner. This includes understanding the implications of generative AI tools, such as privacy concerns, data security, and the potential for bias. Individuals should be aware of the societal impacts of Generative AI and strive to use generative AI responsibly.

Critically Evaluating Generative AI Outputs: Being AI literate means being 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.

We welcome feedback on this definition and anticipate it needs further refinement.  Please do get in touch if you are interested in joining the collaborative working group focused on this definition.


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