Need Of AI Literacy In Academia

The emergence of large language models (LLMs) such as ChatGPT, DeepSeek, and Gemini has initiated substantial discussions among educators, policymakers, administrators, and students vis-à-vis their pros and cons. While some admire the positivity they bring about, others have expressed concerns about the probable abuses of these tools. Some research supports the fact that LLMs can draft essays, generate and debug codes, solve mathematical calculations, and simulate human-like conversations. They argue that students use these tools to brainstorm ideas for their assignments, to verify data, to solve problems faster, and to explore complex topics. For the teachers, these tools are helpful in grading, designing personalised learning experiences, and suggesting new pedagogical approaches.

These advantages are not free of risks, however. Students may use AI-generated content to bypass learning. They can submit assignments without understanding the underlying concepts. Instructors, on the other hand, may unsuspectingly accept AI-written work as original. Moreover, unregulated use of AI tools can perpetuate biases embedded in the data these models are trained on, which results in ethically questionable outputs. These challenges show the need to equip users with the critical skills to distinguish between proper use and harmful dependency on AI. Despite these ongoing debates, there is very little discussion about AI literacy among instructors and the learners. This lack of oversight and understanding can worsen these issues and result in an erosion of academic integrity and trust within educational communities.

In simple terms, ‘AI literacy’ refers to the knowledge of how artificial intelligence works, the way it impacts daily life, what is considered acceptable in using it, and what is not. It also means responsible and effective usage of the AI tools in a manner that delivers desirable results, acknowledging their limitations and ethical issues. However, with the rapid advancement of AI, which has now become both complex and essential, its management will need to be well thought out and strategic. These challenges necessitate a collective effort on the part of all stakeholders. But unfortunately, research has evidenced that many students are using AI tools for academic purposes, but they are not literate enough to decide what is ethical use of AI and what is not. Also, many academic institutions across the world even today have not developed comprehensive AI policies and guidelines. 

Ethical guidance

Academic institutions’ role is very significant in bridging this gap. They can support AI literacy among their students and instructors through multiple approaches, such as integrating AI literacy into curricula, providing educators’ training, and developing clear AI policies. Courses on AI ethics, its practical applications, and its limitations will help students to use these tools responsibly. Such courses must also include practical projects in which students explore AI tools in real-world scenarios and gain better knowledge of the benefits and limitations of these tools. In the same regard, educators need training to understand the advantages and limitations of AI for better guidance of students. Regular workshops are further helpful in reaching this goal.

Equally important is the development of very clear guidelines on what constitutes acceptable and unacceptable uses of AI tools for academic work; this would help encourage use but discourage abuse. The guidelines should emphasise transparency and encourage both students and instructors to declare when and how AI tools are used. Such open practice will help reduce misuse and encourage positive experimentation with AI technologies. Moreover, institutions can organise panel discussions in which students, educators, and AI experts share experiences and ideas as a way of understanding the role of AI in education.

 Collaborative innovation

Despite these challenges, instructors and students should not look at it as a threat, but rather it should be taken as a collaborative partner. For example, students may use LLMs for brainstorming ideas for essays, which they would then refine using their critical thinking and insights, while instructors might use AI to design lesson plans or create innovative teaching strategies.

Co-creative potential in such a case acknowledges one fact— the wheels of scientific and technological progress cannot be undone. Any attempt to discourage AI in the present scenario is impractical and unproductive. The potentials of AI, instead, need to be coupled with its potential in a manner aimed at uplifting and upgrading human capabilities rather than belittling them. With AI embedded within collaborative learning models, an institution can develop a mindset whereby technology is perceived as an enabler but not a crutch. This approach encourages a culture of continuous learning and adaptation and prepares for forthcoming technological developments in the future.

Future empowerment

These tools will be of productive use in an AI-literate academic community. Understanding the mechanics and ethics of AI inspires innovative applications that go beyond simple, repetitive tasks. For example, students might use LLMs to analyse historical texts, simulate scientific experiments, or create creative projects. Instructors, in turn, would concentrate on teaching higher-order concerns (HoCs) such as critical thinking and problem-solving, areas where AI still lags behind human expertise.

AI literacy is not limited to academic boundaries. The ability to have thoughtful interaction with AI will continue to give AI literacy an edge in both industries and society at large. Industry, companies, and organisations have begun to integrate AI into their service delivery, and those who possess AI literacy will better enjoy this increasing opportunity. This broader societal reality indicates an urgency of embedding AI literacy into educational frameworks sooner.

While LLMs continue to evolve, the influence they will have on education will equally grow. If users lack proper literacy in using such technologies, then misuse and dependency offset the benefits of such tools. With strategic development and integration of AI literacy, however, academic institutions can turn this technological challenge into an opportunity for their growth.

Therefore, in the present context, the discussion is not on a choice that must be made between humans and machines, but to find a balance where one complements the other. Once its stakeholders become AI literate, they navigate this new opportunity with confidence and integrity so that the tools of today direct the way for a meaningful tomorrow.

(Baral is an assistant professor at Tribhuvan University and currently pursuing PhD from the University of Texas at El Paso, USA.)