While Generative AI can be a useful tool, it is important to always evaluate and assess the content it produces before relying on it. You can assess the output by examining it for accuracy, bias, comprehensiveness, currency, sources, and copyright.
REACT framework from Loyola Marymount for evaluating and assessing GenAI tools. It uses the following criteria: Relevance, Ease of Use, Accessing DEIA, Currency, and Transparency & Accuracy. Check REACT Framework - accessible version.
Note: KPU has developed a guide on Assessing Generative AI Content. AI content should be evaluated for Accuracy, Bias, Comprehensiveness, Currency, Sources, and Copyright.
It can be difficult to know how if the content AI produces is from a valid source that can be used for research. The Association of College & Research Libraries (ACRL) provides these steps on evaluating sources found from AI tools.
"1. Are the citations actually real? Does such a journal/website/book exist? State which are not real, and which are real. State whether any website used in a real citation where you found it is credible and why.
2. State where those specific real citations are available in full text (check our library databases too). List the names of the places you found them (for example, name of such-and-such website, name of database, etc...).
3. Check the credentials of the lead author by doing a Google search of their name in quotes. Are they trained in the field of the topic? State their credentials and/or academic degrees.
4. Now run their name (in quote marks) in a library database (like ProQuest or EBSCOhost), use a drop-down to search for AUTHOR - do they appear? IF YES, what are their other article/s (provide the permalink URLs) about?
5. Now search for the topic you have chosen in a library database. What are the top four most relevant (provide the four permalink URLs)? Note if they match any of the original four generated.
“Vetting ChatGPT Sources | ACRL Framework for Information Literacy Sandbox.” Retrieved January 22, 2024, from Vetting ChatGPT sources | ACRL Framework for Information Literacy Sandbox
ROBOT test from Concordia/McGill -a tool developed to help critically evaluate text generated by AI. It includes the following considerations: Reliability, Objectiveness, Bias, Ownership, and Type.
Using Ai Accurate-LE - developed by University of Saskatchewan
Generative AI tools like ChatGPT are able to produce a lot of different content, from quick answers to a question to cover letters, poems, short stories, outlines, to complete essays and reports. However, the content created should be carefully checked, as it may contain errors, false claims, or plausible sounding, but completely incorrect or nonsensical answers.
Generative AI can also be used to create fake images or videos so well that they are increasingly difficult to detect, so be careful which images and videos you trust, as they may have been created to spread disinformation.
Generative AI relies on the information it finds on the internet to create new output. As information is often biased, the newly generated content may contain a similar kind of bias. Example of potential bias include gender-bias, racial bias, cultural bias, political bias, religious bias, and so on. Scrutinize AI generated content closely for inherent biases.
AI content may be selective as it depends on the algorithm which it uses to create the responses, and although it accesses a huge amount of information found on the internet, it may not be able to access subscription based information that is secured behind firewalls.
Content may also lack depth, be vague rather than specific, and it may be full of clichés, repetitions, and even contradictions.
AI tools may not always use the most current information in the content they create. In some disciplines it is crucial to have the most recent and updated information available. Think, for example, about the recent pandemic. Research was going at a very fast pace and it was important to have not only the most comprehensive and most reliable data available, but also the most recent. Technology is another area that is constantly changing, and information that is valid one year, may not be valid the next. There are many other examples, and it is important that you check the publication dates for any sources of information that are used in AI-generated texts.
Generative AI tools don't always include citations to the sources of information. It is also known to create citations which are incorrect and to simply make up citations to non-existent sources (sometimes referred to as AI Hallucination).
Not crediting sources of information used and creating fake citations are both cases of plagiarism, and therefore breaches of Academic Integrity.
Generative AI tools rely on what they can find in their vast knowledge repository to create new work, and a new work may infringe on copyright if it uses copyrighted work for the new creation.
For example, there have been several lawsuits against tech companies that use images found on the internet to program their AI tools. One such lawsuit in the United States is by Getty Images which accuses Stable Diffusion of using millions of pictures from Getty's library to train its AI tool. They are claiming damages of US $1.8 trillion.
There is much debate about the ownership of copyright to a product that was created by AI. Is it the person who wrote the code for the AI tool, the person who came up with the prompt, or is it the AI-tool itself? Although currently in Canada, AI-generated works are not copyright protected, this may change in the future. Also note that laws in other countries may differ from that in Canada.