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How to Avoid Being Eaten

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Using AI for study, research and writing – without breaking our academic integrity rules

AI: Important Limitations, Important Problems Current AI tools are limited in the capacity to create meaning that is true, accurate, critical and responsive. You must judge any outputs from AI tools with scepticism, suspicion and a critical eye.  Key problems with AI include:  AI gets things wrong. AI will produce incorrect (and sometimes nonsensical) outputs. AI does not know right/correct from wrong, and will present all outputs as if they are equally valid and true. AI is biased. AI tools reflect, prioritise and enhance biases and stereotypes.   AI is not rational and does not understand the complexities around the information available on the internet. It therefore cannot judge inaccurate, offensive statements. AI makes things up.  Called 'hallucinations', some AI tools will make up false references to texts that do not exist. While these references often look to be real, a quick search will reveal that the supposed reference or data does not exist. This is because AI tools are simply predicting the most likely next word each time – think of it like asking your phone to write a sentence based on clicking the next autocorrect word each time. AI tools cannot access all the necessary data and information. AI tools cannot access anything behind a paywall. For your academic work, the University Library subscribes to a massive collection of academic texts. AI cannot access these paid resources, and so it does not have the ability to reproduce any information from those texts. Many AI tools also do not have access to the current state of the internet, and therefore will not be trained on the most recent information.