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 #3: Improving our understanding of the human being while not giving in ontological reductionism
In France and in Portugal, participants highlighted that advances in neurosciences and AI are expected to be able to identify students with learning difficulties notably though neuroimaging and diagnosis. This will allow teachers, parents and counselors to support students and intervene earlier to prevent negative consequences, such as low self-esteem. A better awareness of neurodiversity and identification of a student’s learning difficulties and/or mental pathologies can also lead to adapting learning tools and systems for the student, as allows personalization and AI algorithms.
However, participants expressed that labeling children with mental pathologies or learning difficulties can also lead to discrimination and stigma, and this would be detrimental for the person. In Portugal, participants underline that a better identification of children with low or high cognitive faculties can lead to overfocusing on cognitive performances, to overstimulate or understimulate them with the belief that there is no possibility of improvement and change.
Insights from NHNAI academic network:
Laura Di Rollo (research engineer in cognitive sciences for NHNAI project (UCLy (Lyon Catholic University), UR CONFLUENCE : Sciences et Humanités (EA 1598), Lyon, France) and Juan R. Vidal (associate professor in cognitive neuroscience (UCLy (Lyon Catholic University), UR CONFLUENCE : Sciences et Humanités (EA 1598), Lyon, France)
To avoid reducing a person’s identity to just a few characteristics, we should view these learners’ categories as various ways of functioning (rather than as mental disorders), which may lead different persons to express unique abilities in adapting to specific contexts and environments. These abilities can evolve over time and vary depending on situations. Tests and diagnoses, whether provided by a physician or an AI system, offer insights into a person’s cognitive functioning and this information is valuable for understanding her needs. It may enable to offer her appropriate support. However, technic and technology will always extract data and provide parameter values, but it does not fully grasp an individual’s complexity, and this includes his/her inwardness, such as feelings and affect. Global understanding of a person’s uniqueness and depth cannot be grasped if it weren’t through human relationships and interactions. While machines, tests, and evaluation tools can provide useful data, they fall short in capturing the full integrated spectrum of human singularity and its genuine complexity in which the individual recognizes himself. This also includes knowledge from within the inter-subjective space of interaction. The dimension of relationships, therefore, is essential in an embodied approach to understanding people. Still, this information can be helpful for decision-making, as long as it focuses on helping humans to flourish rather than merely being more productive in a reductive framework of evaluation. Logically, categorization, though indicative, should not lead to an automated decision that could bear discrimination and/or exclusion, but should instead support social inclusion.
Although inclusion is promoted in the 21st century, it also brings challenges and dilemmas. One dilemma, as expressed by Ruth Cigman[1] involves how we handle differences:
We either treat all children as essentially the same, which means treating them as fairly as possible but with the risk of neglecting individual differences. Or we treat them differently, with the consequences that some are better off than they would otherwise have been, but there is a risk of being unfair by devoting more resources or expertise to some than others.
Furthermore, individualization can lead to over-adapting environments to meet the individual needs, as seen with current trends in personalization (like with AI applications). This approach, taken to the extreme, could potentially hinder collective growth and limit people’s ability to learn and adapt to various contexts. If the environment is always tailored to fit individual needs, humans may lose the crucial skill of adapting to different situations, and to display the effort to develop the adaptation skill, a vital ability for thriving in the world, for adaptation does not rise passively in living organisms. Even genetically driven adaptations are to be included in modified behavior. Therefore, we need a balanced approach that considers the socio-environmental constraints (achieving performance?) but also biological constraints (learning through self-driven effort), and a balance that maintains a general standard of equality while still allowing room for differences and (neuro)diversity. Achieving this balance is no simple task.
In short, we need a holistic approach to understanding people as complex beings, each with a unique personality, history, with unique beliefs and desires. Such complexity cannot be known through simple categories or labels. While learner categories can offer helpful insights into a person’s way of functioning in a specific period, they cannot grasp all the potentialities of individuals. Nothing is set in stone, humans evolve, change and can express new potentialities to learn. Moreover, categories can lead to uniformization, while, for instance, there is no single way for conditions like ADHD or Dyslexia (and others) to manifest in individuals.
In past decades, neuroscience often reduced the brain’s functioning to its neurons only, using the computer as a metaphor for brain activity. Through these reduction and metaphors, the brain’s functioning tended to be identified with the execution of a program. This approach, largely coming from cognitive sciences, suggested that the brain operates much like a computer. However, this perspective was criticized as “neuro-centrism” for ignoring the roles of the body and emotions. Nowadays, neuroscience has become more inclusive, recognizing that the brain’s functioning is closely linked to other organs and the rest of the body. For example, research now highlights the importance of the intestine and microbiome’s role in mental health[2] or the influence of breathing and heart rate on brain activity.[3]
[1] Cigman R. ( 2007), Included or Excluded? The Challenge of the Mainstream for Some SEN Children (Oxford Routledge). op. cit., p. 137
Cigman, R., & Davis, A. (Eds.). (2009). New philosophies of learning (Vol. 2). John Wiley & Sons.
[2] Morais, LH., Schreiber, HL, Mazmanian SK (2020). The gut microbiota-brain axis in behavior and brain disorders. Nat Rev Microbiol. 2021 Apr;19(4):241-255. doi: 10.1038/s41579-020-00460-0. Epub 2020 Oct 22.
[3] Engelen, T, Solca M, Tallon-Baudry C (2023) Interoceptive rhythms in the brain. Nat Neurosci.2023 Oct;26(10):1670-1684. doi: 10.1038/s41593-023-01425-1. Epub 2023 Sep 11.
