Being human in the time of neuroscience and artificial intelligence involve carefully exploring the nexuses of complexity where valid ideas are nevertheless in tension, manifesting subtleties and challenges that must not be overlooked. Each page expresses the existing tension(s) between ideas and within each theme, which emerged in the collective discussions, and are then complemented by insights from NHNAI network researchers.
Complexity on Education #1: Making quality education accessible while preserving the human development
The cognitive development
The participants evoked the advantages of using AI in education. First, AI can help us to be more productive and efficient, because some tasks are easier and faster to complete with AI (such as synthesis production and taking notes process for students, proofreading for teachers…). Moreover, AI and automation allows us to save time that could be used in other activities to exert our humanity, or to focus on other essential things like relationships (evoked in France and Portugal). Another point is AI can release ourselves from repetitive or uninteresting tasks, that allows us to focus on more profound tasks that need high intellectual activity and might be more interesting/stimulating. Automation can also be a mean to relieve teachers that are tired or when they have a health problem (temporarily) – or relieve them from tiring tasks (permanently).
However, participants are also worried about the risk of cognitive impoverishment and loss of autonomy with AI. Automation supposed to delegate/be dispossessed of a certain knowledge (a know-how) and to become machine-dependant, thus we are certainly losing autonomy when we are not able to realize a task without a machine or by ourselves. Moreover, by freeing ourselves from a task, we no longer call upon the cognitive capacities that enabled us to carry out this task, we no longer call upon the cerebral areas (like it is the case with the systematic use of GPS that impoverishes activity of cerebral areas associated to space orientation and memory) we need for this action/realization of the task. On top of that, certain cognitive faculties need practice to be developed (such as resolving a problem, creativity…), notably by trial-error as we are also learning from our mistakes, things that AI doesn’t make possible if we are always relying on it for the right answer. And finally, sometimes, even if certain tasks are uninteresting or of “lower level,” some of them are holding a lot of values (such as patience, maturity…) or they are important for the development of cognitive faculties.
Insights from NHNAI academic network:
Learning new skills, intellectual and practical, requires practice, and often repetition in order to increase the efficiency and quality of the action regarding its goal in the long-term. This repetition is not possible without displaying effort and often facing frustration when not quiet achieving our goal. If the use of technological devises and AI short-cut these important learning steps, the individual will not acquiere the new capacities and knowledge, and will thus be empoverished. It is this important to evaluate the use of AI through this “effort-for-learning” lens, that should not be viewed as a waste of time, but rather as the time needed to learn-and-keep the knowledge (be it abstract or concrete know-how). Moreover, realizing efforts also conveys sense-making in the learning, which is important for a person’s identity.
It is thus important to think the use of technology and AI as a means to potentiate the learning of human capacities as such, and not only to maximize exclusively his evaluation scores in the education system. AI could be used to help us remind of things we need to do, and not only to do it for us, depriving us of the experiences that enable us to grow and flourish. AI could be used as a motivator instead of only/mainly as a facilitator of complex tasks (that are necessary for learning, especially long-term).
Although there could be several beneficial uses of AI in education that can enhance learning (e.g., using ChatGPT before an exam by answering questions about the lesson, providing initial ideas for starting a writing project…), it might be more tempting for students to use it to complete their academic tasks. Technology such as AI makes tasks easier and appeals to the principle of the “least effort” which, indeed, may be detrimental for cognitive development.
One study shows that excessive use of chatGPT can lead to procrastination, memory loss and poor academic performances (Abbas, Ahmed Jam and Iqbal Khan, 2024). More importantly, the study reveals that it is notably high levels of academic workloads and time pressure that drive students to use ChatGPT to complete their academic tasks (Abbas and al., 2024). According to this study, these pressures are likely to impair cognitive development, by increasing procrastination, memory loss and poor academic performances particularly through the use of ChatGPT. The excessive use of AI is thus only part of a large problem which takes its roots in the model of an economic system that values efficacity, sur-production and sur-consumption.
The beneficial use of technology in education may occurs when AI is used as a complementary tool that does not prevent to make cognitive efforts, rather than being used to complete academic tasks without investing intellectual and cognitive efforts. It is our responsibility to encourage students to strike a balance between technological assistance and personal effort, in order to preserve learning and cognitive development. The challenges posed by the integration and overuse of AI in education force us to reassess our methodologies and critera for student assessment. What do we want to assess? Is it only knowledge? Or should we focus on competencies such as critical thinking, creativity and problem-solving?
We may need to reinvent assignments and activities that cannot be easily solved by AI tools but instead require students to call upon their creativity and critical thinking. Moreover, valuing such activities could motivate students to engage more deeply with the learning process and be more willing to complete tasks on their own (Abbas and al., 2024).
References:
Abbas, M., Jam, F. A., & Khan, T. I. (2024). Is it harmful or helpful? Examining the causes and consequences of generative AI usage among university students. International Journal of Educational Technology in Higher Education, 21(1), 10.
