AI: A Cognitive Crutch or Empowerment?

AI has quickly become an indispensable part of the modern world for students, professionals, and even people unrelated to tech. While the latter uses it primarily for amusement, the younger generation has quickly adopted it as a constant source of information, building more dependence on it by the day.

The argument whether this will hinder the fundamental growth of a young mind, by limiting the learning ability to gain elementary skills through practical endeavours, or will it empower the users to assimilate information at a faster pace, thus allowing them to outgrow the traditional learning pace, is still a question among researchers.

However, the answer might lie in understanding the complexities of human learning. As such, more research has been conducted by many universities, like NC State, USA, into understanding this phenomenon, to help actively reshape pedagogical practices, institutional strategies, and the very definition of learning.

The power of advanced models like GPT-4 to solve complex problems and even grade submissions with a high degree of accuracy presents a fundamental challenge to traditional assessment methods. Exams once considered "unhackable" are now easily compromised, forcing a necessary reimagination of how learning is measured. In response, research is shifting toward the development of novel assessment frameworks. This includes creating instruments to assess new competencies like AI literacy among students and leveraging AI for new evaluation methods, such as using state-of-the-art speech models to assess oral reading fluency in West Africa. Recently, Meta has announced that it will allow AI usage in its assessments.

While the world of AI is moving at an astonishingly fast pace, adopting such a disruptive tech is widely limited to the younger generation of users and budding companies. The resistance to adoption or the inability to make a smooth transition towards machine learning powered systems has been exhibited by teachers, large institutions, and veterans in the technology field. This growing gap between the current infrastructure and the young users will further create barriers in establishing an effective system that can harness the power of AI and not be disrupted by it.

While we are still struggling with these issues, AI promises a personalized learning experience for all, catered to an individual's pace, preference towards a particular tone in the language, and so on. But is it truly providing a unique experience? Since most large-scale AI models are trained on data that is overwhelmingly from Western, English-speaking, and culturally specific sources, their widespread adoption risks creating a "homogenized" and "drastically impoverished" global knowledge commons. This is a critical contradiction. The very tool that can tailor learning to an individual's specific needs could, at a macro level, be narrowing the cultural, linguistic, and intellectual diversity of the knowledge being transmitted. This implies that a core responsibility for future educational policy will be to actively de-bias, diversify, and culturally validate the AI systems deployed in classrooms.

For centuries, the primary function of formal education has been the transmission of a canonical body of knowledge from teacher to student, with success measured by the student's ability to retain and recall that information. The advent of powerful AI has rendered this model obsolete. When any student can access the sum of human knowledge through a simple query, the value of rote memoization plunges, and the educational mission must therefore pivot away from an emphasis on what students know to a focus on what they can do with that knowledge.

So what do we do until there is a cultural, pedagogical, and structural shift in the education industry?
The key is to integrate AI education and AI-based tools to augment the teacher's capabilities. Instead of considering it as a replacement of teachers, which by any way it is not, we must empower the teachers to actively stay ahead of such technical advancements and teach their students how to utilize the AI tools to create more complex projects, scale up quickly and inculcate a deeper curiosity to learn and adapt to more such technical advancements.

Today, it is the LLMs that have taken the world by storm. Tomorrow, it will be another revolution, probably in the field of brain computer interfaces, quantum computing, or physical AI. And, with the help of powerful AI-based tools, all future advancements will also have a stronger push toward their realization.