AI Literacy

Why do I need to learn this?

With the rapid development of generative AI, or generative artificial intelligence, since the end of 2022, tools using Large Language Models or generative art have become freely available and offer images and text which students may want to use in their study and their assignments.  You may also find they are increasingly used in the workplace and need to be prepared for that.

It is important to grasp how these AI tools work in order to avoid any possibility of plagiarism.  It is also important to understand whether it is ethical to use them at all for a variety of reasons.

These pages will help you:

  • recognize AI in the world around you and have an appreciation of its impact;
  • recognize different kinds of AIs;
  • understand how AI works at a basic level and how much intelligence AI has;
  • understand AIs’ strengths and weaknesses;
  • better develop your prompt engineering;
  • consider various ethical issues such as hallucinations, bias, accountability, transparency, and reasonable academic use.

See also our Library Guide on Using Generative AI in coursework or research:

 

 

Understanding AI Basics

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• What is AI?

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• The role of data in AI

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• How do AIs learn?

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There are three basic machine learning approaches: supervised learning, reinforcement learning and unsupervised learning.  

Supervised learning - the AI is given labelled training data to learn the relationship between the inputs it receives and what kind of output it should give

Reinforcement learning - the AI software is trained to make the most optimal decisions mimicking the trial and error that humans use

Unsupervised learning - the AI is given data to discover patterns and insights without any human oversight or instruction

 

 

AI in Practice

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Ethical Considerations

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Developing AI Literacy

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Resources and Further Learning

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Referencing work which uses generative AI

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Test Your Knowledge

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The Future of AI

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