AI’s challenge and dilemma of faculty

IT is now a fact that students at universities are using artificial intelligence (AI) tools to do their assignments and paper-writing. Instead of denying the issue, we need to step up and become more creative and innovative in designing our higher education policies regarding AI usage by both students and faculty. Members of academia do recognise the importance of integrating AI into the curriculum so that their students are ready for the real world. The big issue is about monitoring and controlling this use to ensure that it is not done at the cost of students’ cognitive and critical thinking.

Currently, it is difficult to evaluate students’ work because, in one way or the other, they are using some form of AI to complete it. This is becoming a more pronounced problem in writing-intensive courses, where students need to learn critical writing and showcase their essays and papers at the end of the semester. When students offload their thinking into a large language model (LLM), the output is predictable and flat.

A recent paper published in the journal Trends in Cognitive Science reported that AI models dull users’ thinking, and produce output based on trained data, making it sound like a standard response when all the students are using them. The researchers also argued that when individuals use these chatbots, they exchange their human thinking and cognitive capabilities with LLM output.

Faculty members are trying hard to be as creative as possible to foster equitable and inclusive classroom interactions where students can use their brainstorming skills rather than rely on AI tools. They give their students case studies, pop-up quizzes and other interactive, engaging assign-ments in which students have to shine, or fail to shine, on their own without relying on AI tools.

In the domain of Social Science and Humanities, however, there are writing-intensive assignments, such as research papers, that are crucial for learning about research and theory. So, how do faculty members check, evaluate and verify the authenticity of work when the students claim that it is their own even though AI-detection websites flag it as cent per cent AI-generated? Their argument is that because these websites are free, they are inaccurate and can flag all types of work as written by AI.

There are endless arguments and emails that faculty members must deal with while grading. Faculty members can easily tell that the work is not a freshman’s creation in an undergraduate programme by reading their American English sentences in a Pakistani context, but the arguments never end.

Universities have vague policies in this regard. There are many schools in Pakistan now teaching prompt engineering to young students, which is questionable because it over-emphasises the importance of using AI in academic settings to these young minds. I do not understand what the end goal is. The bigger question is: should we incorporate it, or should we become traditional educators by asking our students to do all their work in their notebooks themselves to get their actual output rather than AI-driven work?

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