You may encounter various grey areas when considering how to use AI-based tools to support your learning. The line between using them appropriately versus using them to gain an unfair academic advantage may not always be clear. As discussed, following York’s policy guidelines by citing and/or documenting when you have used them helps to generate trust in the academic community.
Keep in mind that AI-based tools should be used to enhance your learning and not used to complete work on your behalf. If your instructor has not prohibited the use of these tools, consider ways that you can use them to expand your understanding of course material. Think about how they can support your academic work instead of undermining it. Again, if you’re unsure about what is acceptable, review theBeing Responsible for Academic Integrity section to learn how you can identify the expectations in a particular course, and how to reach out to your instructor.
Click the sections below to learn about evaluating AI-generated output.
At times, AI content generators may provide information that is incorrect. They can generate false information or leave out important information. They are also known to provide false references. Furthermore, AI-generated content is not neutral: having been trained on a large amount of data from many different sources, embedded in its output are specific viewpoints and biases.
As a student, you are responsible for the work you submit, and if you are relying on any AI-generated output, you are required to critically evaluate this information. Part of this critical evaluation involves verifying information, identifying any missing information, and uncovering any embedded viewpoints and biases. As you do so, you are developing and strengthening your critical analysis skills, which are important skills that you will apply throughout university and beyond.
Critically Evaluating AI Output
With most non-AI sources, such as scholarly books or articles, you can evaluate the accuracy or credibility of the content by following up on the “clues” that are provided within the publication. For example, following up on the bibliographic citations provided is an excellent way to learn more about certain information included within a source. Or, if you are accessing a website that does not include references, some “clues” to follow up on can include the author’s name, title, affiliation, the publication, etc., which can help you determine the credibility of the work.
However, AI-generated output typically lacks these clues. You may find that the output does not clearly indicate when information from outside sources has been included. Instead, information from outside sources may be combined and citations may not be provided. Or, if citations are included, they may be incorrect. Instead, to determine the accuracy of the content provided, you will need to:
identify which pieces of information require further scrutiny;
obtain other, reputable sources from the scholarly work in your field or your course material;
review the information you find
A final, important step of critical evaluation is exercising your own judgement: based on what you have learned from other sources, and based on what you already know, can the AI-generated output be trusted, or should you discount it?
Again, as a student, you are responsible for the work that you submit. If you use information from any AI-based tools, critically evaluating the information these tools provide is essential and an important part of the scholarly process.
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Objectifs du module
Ce module sur la compréhension des travaux fournit des stratégies pour :
vous familiariser avec les exigences générales d’un travail de recherche universitaire;
déterminer le but d’un travail afin de vous guider dans le processus de rédaction;
reconnaître les différents types de travaux de recherche et les mots-indicateurs qui y sont associés;
appliquer noter des approches disciplinaires différentes
identifier le public cible et tenir compte de son rôle dans le travail.
