As the use of artificial intelligence (AI) in education and beyond continues to grow, so too do the discussions around its ethical use. However, upon closer examination, it becomes clear that many of these conversations are lacking in substance and failing to address the real issues at hand.
Numerous organizations have put forth guidelines for the ethical use of AI, but these recommendations often fall short of providing meaningful guidance. Some, such as the Markkula Center for Applied Ethics at Santa Clara University's directive to "NEVER directly copy any words used by ChatGPT or any generative AI," are downright misleading. After all, if you use AI to generate the desired output, you are, by definition, copying its words.
Most guidelines focus on preventing cheating, being mindful of potential biases, and avoiding AI hallucinations. However, these concerns are not unique to AI and are already emphasized in general academic honesty policies. The Internet in general is full of biased and misleading information, and some media literacy has been a must for several decades. So why the need for new, AI-specific guidelines?
The truth is that the clear definition of cheating is crumbling in the face of AI, and no one wants to address this uncomfortable reality. Clearly, the laxy prompt practice is bad. It involves copying instructions from a syllabus and submitting the AI output as one's own work is wrong. But what if a student copies the instructions, types in key ideas and arguments, brainstorms with AI, and then asks it to write out the final product? Is this still cheating? What if theidea is actually brilliant? The answer depends on the skill being assessed. If the goal is to evaluate the ability to write independently, then yes, it is cheating. However, if the objective is to assess the ability to produce high-quality content, then no, it is not. Let's not pretent the things are clear-cut; they are not.
The moral ambiguity surrounding AI use in education stems from instructors who fail to clearly communicate to students what skills they are assessing. Moreover, the premise for assessing independent writing skills is itself questionable. In an AI-driven future, who will need this skill? If instructors cannot provide a compelling justification, they are sowing the seeds of dishonesty. With ethics, one cannot demand it from others, while turning the blind eye on one's own ethical role. It is a two-way street in educational relation as it is in any other one.
Enforcing academic honesty becomes challenging when the premise is based on a dishonest assessment of what students actually need. Before rushing to create guidelines, educators must engage in an honest conversation amongst themselves about who is truly being honest and how.
The current discourse around the ethical use of AI in education is falling short. Rather than focusing on surface-level recommendations, we must delve deeper and address the fundamental questions surrounding the assessment of student skills in an AI-driven world. Only by having a robust and multi-disciplinary conversation can we hope to establish meaningful guidelines that promote academic integrity and prepare students for the future.
