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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AI in Practice

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You probably encounter versions of ‘artificial intelligence’ every day in all walks of life – from chat bots to email assistance, from Google maps monitoring traffic to banking fraud detection, from Amazon or Netflix recommendations to new features on smartphones offering to help.  Two of the best-known examples which have been around for a while are the predictive text features on smartphones and Google Translate offering the ability to read (or generate) text with varying degrees of accuracy in a large number of languages.

What is meant in these pages by ‘AI’ is the more limited application of ‘large language models’ or ‘generative AI’ (sometimes generative image AI or text gen AI) which produce text or images in response to user inputs, or prompts.  Some will accept speech input as well as typed text.  These hit the headlines and gained millions of users when ChatGPT 3.5 was released in November 2022.  Others followed, for example Bard and Gemini.  These generative AIs can have the appearance of chatting with you or writing fully fledged answers or essays, but it should always be remembered that LLMs in reality have simply processed a lot of text and have good statistical models on what words are likely to go with other words.  Or, in the case of images, have been trained on billions of images in order to generate pictures which can look photorealistic.

Such generative AI is developing quickly and they have the potential to change how we work, create and even think.  It’s likely that a digital Jeeves (a clever and resourceful butler in P.G. Wodehouse novels) is coming to a device near you very soon if it’s not already there.  Learning how to prompt such AIs to get useful results will become increasingly important.

It should always be remembered that generative AI is in no way being genuinely creative. Ted Chiang reminds us that such tools have no actual intention to communicate. In an excellent essay on the subject which is worth reading [1] he points out "it’s by living our lives in interaction with others that we bring meaning into the world. That is something that an auto-complete algorithm can never do".

 

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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