Neuroscience studies the detailed functioning of the brain and nervous system. It bridges the realms of biology and psychology, linking behavior with the underlying brain structures and processes.
The potential applications of this research are profound. Understanding, diagnosis and treatment of mental disorders can be expanded. Increasing ability to interface with the nervous system may allow greater effectiveness of prosthetic devices, from limbs to hearing and vision repair.
While these trends can be seen as positive, many wonder at the potential for neuroscience to create devices that expand the ability of humans, such as directly interfacing with computers. This new frontier is the hardest to define in advance, and will raise the biggest questions. New ethical areas will need to be debated: the risks versus rewards of invasive devices to achieve enhancements, equity issues of access to technology that could produce profound advantages in many situations, and the social impacts of blurring the lines between people and machines.
We have chosen some areas of a vast and complex field of study. The areas we explore are not meant to be exhaustive nor are they necessarily the most important for education. Rather, they provide some ideas of the scope and potential that may be ahead of us.
Many advances in the field of neuroscience can be linked to developments in artificial intelligence. The complexity of the brain makes understanding its function an immensely challenging task. To attempt to observe what is happening inside an active brain requires a large amount of interpretation and deduction, with even the most detailed instruments offering minimal data relative to the scale of the phenomena. AI can play an essential role in parsing the complicated data produced to find non-obvious patterns, allowing greater insight into what is happening inside the brain.
The ability of AI to extract information from measurement tools also plays a role in interfacing people with machines. Experiments have shown significant potential in restoring complex functions to people who have lost them, from hands to speech. Refinements in machine learning will continue to offer human computer interfaces new opportunities.
In the broader and more immediate term, AI will likely play a role in adapting the knowledge gained from neuroscience into useful implementations. As we learn more about how people think, learn and react, improvements can be made to systems that coincide with these actions. The flexibility of AI tools suggests they can be utilized to adapt content and interactions to best suit individual needs.
As education continues to move away from content-based memorization to more holistic and skill-based ideas, interest in neuroscience informed pedagogy will continue to grow. Potentially, this will offer tools to assist with developing pure cognitive processes such as memory, learning, and focus. This shift would support students in obtaining highly transferable abilities, and maintain lifelong learning habits.
Another significant aspect is the ability to develop tools that are highly responsive to induvial student needs. Current developments often focus on cases of physical and mental impairment, but in the future could envelop a much more diverse range of adaptability. New methods to achieve student diversification and equitable access to education can result.
As with other developments in AI and neuroscience, these trends need vigilance to ensure ethical implementation. The same tools that utilize a person’s unique mental traits to offer optimal learning could possibly be used to manipulate them; the data gathered for advanced human computer interfaces will bring questions of data security and privacy to new levels. Similar to other discussions around AI ethics, these are questions that will need to be discussed actively alongside developments in the field.