As generative systems continue to become more commonplace in academia (and elsewhere), it is vitally important to set controls and boundaries as to how they are used. This, of course, includes its use in academia. Already there have been well-publicized incidents in numerous universities and academic settings in which students have tried to pass off generative text or images as their own work. The debate as to whether or not using generative systems to produce an assignment entirely constitutes plagiarism is still ongoing. However, the important thing is this: having a generative system complete an assignment for you is cheating.
Certainly these tools have their place as aids for research and academic work (see “Research with Generative Systems” for constructive ways to accomplish this). The prospect of utilizing them as a replacement for critical thinking, rather than as a supplement thereof, is one that runs counter to the requirements and expectations of the college experience. There are many possible specific approaches as to how generative systems can and should be used in an academic setting, but the bottom line is this: always be thinking. Do not accept all information without question, whether it be from a generative system, a textbook, the news, a scholarly article, a colleague, or any other source. Always consult multiple sources when possible; always approach your objectives with an inquisitive and curious mind; always ask questions of the material you are given, and be prepared to further investigate the answers to those questions. In short, again: always be thinking. Don’t allow a generative system, or anything else for that matter, to “think” for you.
For Students
Regardless of what your professors have stated, there are some important general questions you should ask yourself when using a generative system in conjunction with your assignments. Always defer to your professor for more specific usages of generative systems, or to determine what is and isn’t allowed for a particular class or assignment. Keep in mind also that the discourse around generative systems is always changing and evolving, so always be aware of how developments in generative systems will affect how they could potentially be used in a classroom setting. If you decide to use a generative system in your work, ask yourself the following questions:
Question 1: Before using a generative system, ask yourself if your usage thereof is something that is or is not explicitly approved of by classroom materials. Has your professor made any restrictions or specifications about generative systems?
Question 2: Have there been any pre-existing examples of generative system use which could inform your intended use, either from your professor or from other general materials?
Question 3: When using a generative system, is there enough doubt in the finished product that someone reading it might suspect that it was made by a generative system? How different is your work from that of a generative system being given the same assignment (you may want to test this yourself to see if a professor might pick up on this, either by providing a generative system with the same assignment prompt or running your work through a detection service)?
For Faculty
No matter how generative systems are (or are going to be) utilized by students, it is important to establish a definitive stance on their usage in terms of your own work. It is very possible that students will be uncertain about what constitutes appropriate use of generative systems, and that they may look to established classroom materials to offer guidance. Whatever you deem best for your own materials, be sure to communicate any allowances or prohibitions clearly to students, and to impress upon them how such usages are part of the overarching question of academic integrity. In addition, consider the following questions:
Question 1: If you were given one of your own assignments, would you utilize a generative system to aid you? If so, how (i.e. what would constitute an appropriate use)?
Question 2: Put in your assignment prompt to a generative system to see what the result might be, preferably multiple times or in multiple different generative systems. What do you notice about the nature of the responses? Are there similarities or differences between them? How appropriate/inappropriate are they with regards to the assignment?
Question 3: Once you have determined what constitutes appropriate use, ask what an effective use would be. What usage of a generative system would produce the best result for your given assignment without impinging on academic integrity?
Question 4: Are there any changes that need to be made to assignments to account for the use of generative systems?
Here is an example of an exercise in critical thinking which could be of use in a research context. Say that you have a research question, such as "How have attitudes about autism-spectrum disorders in the medical community changed over the past 15 years?" You could simply ask the question of a generative system directly, which may or may not generate a serviceable (if non-specific) result. For example:
However, actually utilizing critical thinking skills with the aid of a generative system requires more detailed inquiry on your part. This involves more thorough inquiries about your research question, and examining the ideas it represents from multiple different perspectives. For example, you could rephrase the question to: "List five different ways that attitudes about autism-spectrum disorders in the medical community have changed in the past 15 years." Doing so might give you a result such as this:
This is not dissimilar to our initial result, but has a clearer sense of differing categories, and may be easier to parse as part of an essay or similar assignment. You can also delve deeper into an individual aspect of your results to determine its relevance to the research topic. In the above example, you could ask a generative system to expound on item number 4, asking, for example, "What are some specific challenges faced by individuals with autism, and why is there now a greater awareness thereof?" One possible answer could look like this:
Now that you have a framework of generalizations about the topic, you may want to ask a generative system for more specifics. Always remember that sources presented by a generative system are not necessarily reliable on their own, and it requires additional research on your own to confirm whether such sources are legitimate and/or trustworthy. With that in mind, here is an example asking a generative system to provide more specific information:
In this case, the resource presented is potentially useful, as evidenced by the collected data entries on the subject available on the website of the CDC (https://www.cdc.gov/ncbddd/autism/addm.html). Again, always follow up on resources yourself; do not trust a generative system entirely to make decisions for you about the suitability (or, indeed, the existence) of resources.
