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There has been a lot of buzz around artificial intelligence (AI) and how it can be both beneficial and harmful to our everyday lives. One sector that has seen a lot of discussion about AI is higher education. AI presents benefits and harms to higher education, and we’ll explore both sides here. However, before we tumble down that rabbit hole, we first must define what we mean by the term “AI.”
Let’s use a simple definition for AI in this context. AI refers to a machine that provides a service to humans and that’s tailored to that human or to that space. The keyword in my discussion on AI is “tailored.” By that, I mean that, if two different humans use the same product with the same input, the output would be different. This also holds true if the same product is placed into two different spaces: The output would be tailored to each space.
Now that we have an understanding of the meaning and context of AI, let’s look at the harms and benefits of AI in higher-education settings.
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Let’s start with potential harms that AI might cause to higher education. When you boil AI down to its root, it is still based on binary math. What that means is it is either 0 or 1, yes or no, correct or wrong, etc. In short, there’s no real reading between the lines.
Predictive work: Predictive work can be an exam, a quiz or an assignment that is taken on an AI system. The idea behind this is that the AI system will continue to give you work in areas that you are struggling with. For example, if you were given an assignment on animals and you really knew your reptiles but did not know mammals, you would get more questions on mammals and fewer on reptiles. The issue with this type of AI, as alluded to above, is that it boils things down to correct or incorrect. This is based on variables put into the AI system. For a simplified example, if a question arose asking you to name a mammal that hangs upside down inside caves and you typed in “bat,” but the expected answer was “bats,” the AI system might mark it wrong. By contrast, a human would realize that you knew the answer.
Learning the basics: We all need to learn to crawl before we can learn to walk. This is building the base of our knowledge before moving on to more advanced skills. As AI enters our education system, we are losing the baseline knowledge and skills that are required to cultivate more advanced skills. Students are now using AI systems to write papers, find answers to questions and even attend their virtual classes; in the process, they’re missing the opportunity to develop those baselines.
I predict that, as AI becomes ingrained in our daily lives, the old arguments we’ve heard about students using calculators will be transmuted into arguments about AI. Before smartphones became so widely used, teachers used to say, “You won’t always have a calculator wherever you go.” But now, we whip out our phones, enter an equation into the calculator and have our answer within a matter of seconds. The teacher was wrong — we will always have that calculator. We don’t need to show our work, and we didn’t need to get paper to work out the problem.
The downside here comes back to gaining the knowledge to understand whether the answer is correct. If you ask an AI system to write a paper for you, how do you know whether it’s correct? How do you know the spelling is correct? How do you know the grammar is correct? How do you know whether the subject is presented accurately? Without baseline knowledge, no one will know if the information presented is correct or incorrect.
Of course, there are just as many benefits to using AI. Now, we turn to those.
Predictive work: Earlier, we discussed how predictive work could be detrimental. However, predictive systems can be beneficial, as well. If there is a classroom full of students, we know that each of those students has a different level of understanding of the subject matter. There might be a student who really understands the subject, whereas another is struggling. It is very difficult for a human teacher to structure their lesson so that it’s at the right pace and level for each and every student. An AI-based predictive system can be that teacher, giving each student the pace and level that they need to fully understand the subject.
Enhance student engagement and access to learning: Using AI in tools like an online chat bot can help students in areas in which they struggle. For example, if a student is at home and stuck on an assignment, they don’t have to wait until the next class to get help with that problem. They can access the AI chat bot, present their issue and get help. Not only will the AI chat bot provide the answer, but, in addition, it can explain why the answer is right. This will help the student who runs into a problem at home, and it’ll help the student who is too shy to speak up in class. Such a student can use the AI chat bot to get help understanding a subject without having to fear speaking up in front of the class.
No Straightforward Answer
Ultimately, AI can be both helpful and harmful in the context of higher education. It would be naive to imagine that the use of AI systems won’t continue to grow everywhere; higher education certainly won’t be an exception. Currently popular AI tools like ChatGPT can provide quick answers for students who are struggling, but, equally, they can dismantle the education foundation that we need. That’s why it’s essential for higher education to take the proper steps to limit how much harm AI can do, even while leveraging all its benefits.
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To illustrate the power of AI, I went to ChatGPT and entered the following statement: “Tell me how AI can be helpful in higher education.” Within 30 seconds, the AI spit out the information shown in Figure 1.
I also asked ChatGPT how integrators and technologists should prepare for the increased use of AI in higher education. Interestingly, it provided the correct advice and cautions for us all: “Technology integrators should stay informed about the latest developments in AI in higher-education technologies. They should also be familiar with the specific needs and goals of the institutions they are working with, as well as the current limitations of AI technologies. Additionally, they should have a strong understanding of the ethical considerations surrounding the use of AI in education and be able to communicate effectively with stakeholders about these issues. Finally, they should be open to ongoing learning and professional-development opportunities to stay up to date with the latest advancements in the field.”
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