Document Type
Editorial
Publication Title
Journal of Biosensors and Bioelectronics Research
Abstract
This editorial discusses the merging of AI-driven neurofeedback with brain-computer interfaces (BCIs) to create a new model for effortless, unconscious learning. By interpreting and reinforcing specific neural patterns, these technologies can enable users to acquire skills without traditional instruction, making them especially valuable in fast-evolving industries. They also offer powerful tools for individuals with physical impairments by enabling control through thought alone. However, the author emphasizes the importance of ethical oversight, particularly around cognitive autonomy, data privacy, and consent. As the field matures, ongoing research and regulation will be essential to ensure responsible development and widespread, beneficial use.
Publication Date
4-12-2025
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Recommended Citation
Hutson, James, "Integrating AI-Driven Neurofeedback with Brain-Computer Interfaces: A Paradigm for Effortless Learning and Workforce Transformation" (2025). Faculty Scholarship. 727.
https://digitalcommons.lindenwood.edu/faculty-research-papers/727