GenAI can assist us in our daily lives (e.g., creating an email draft, providing a list of ideas for Christmas presents, or breaking tasks down into manageable steps). However, as with any tool, using GenAI has ethical implications, and you should use your critical thinking skills before using it.
If you use ChatGPT to create content that you do not engage with or modify in meaningful ways, you limit you own development of knowledge and skills that will serve you in the future.
Using text produced by GenAI may constitute plagiarism. To avoid this, cite GenAI as you would any other source (check out our citing GenAI page for specific tips to cite GenAI). For more on plagiarism, check out our Academic Integrity guide.
GenAI is unable to identify where specific information comes from, and therefore cannot produce a good list of resources as a result. GenAI is known to create “Hallucinations” (i.e. a fake or inaccurate references), which is why verifying any citation provided by GenAI is crucial.
Bias can easily become an integral part of a GenAI program. The biases of GenAI creators, datasets, and GenAI's interpretations of its training materials can all become embedded into the program, intentionally or unintentionally. Bias is often harmful to marginalized populations, and good academic writing strives to avoid bias.
Like other digital tools, generative AI tools collect and store data about users. Signing up to use generative AI tools allows it to collect data on you. This user data is used to make changes to the tools to keep you engaged.
Be aware that user data has the potential to be sold or given to third parties for marketing or surveillance purposes. For more about privacy online, check out our Online Privacy guide.
Building, training, and using GenAI models requires significant energy use, and contributes to carbon emissions. Researchers and companies are exploring ways to make GenAI more sustainable, but it is still important to consider whether your use of GenAI is worth the environmental impact, and to use GenAI tools as efficiently as you can.
Data sourced to train GenAI models was typically gathered without permission from the copyright holders. Furthermore, because GenAI doesn't paraphrase well, the output can be very similar to the original content.
Generative AI presents complex challenges for rights management. The technology is moving quickly, and regulatory activity needs time to respond to and reflect these changes. One example of this issue relates to artists and writers whose content has been used to train generative AI.
By submitting content to AI platforms through prompts or uploads, you may grant an AI tool the right to reuse and distribute this content, and that might result in a breach of copyright or privacy. You should use caution when submitting content, especially information or data that you did not create, to AI platforms. For more information, see the University of Toronto Libraries’ Generative AI tools and Copyright Considerations FAQ.
Attribution: This list has been adapted from the University of Alberta's Using Generative AI guide "Ethical Considerations"
This TedTalk discusses the environmental impact of AI models (including GenAI models), and encoded bias in AI models (particularly in image generation).
This video by the University of Amsterdam explores some ethical issues of GenAI found in the bias, training data (esp. copyright, accessibility, privacy), environmental impact, and social impact.
The material in this guide is based on material from Using generative AI by Deakin University (2023). Content has been adapted for the NWP Learning Commons in July 2024. This work is licensed under a Creative Commons BY NC SA 4.0 International License.
All icons on these pages are from The Noun Project. See individual icons for creator attribution.