International Journal of Education and Social Science

The convergence of Artificial Intelligence (AI) and Neuroscience is substantially expanding the possibilities for understanding, predicting, and clinically addressing human brain functions. The increasing use of algorithmic systems, Big Data, neuroimaging, and brain–computer interfaces, however, is creating a new landscape of neuroethical challenges in which technological capability does not necessarily imply ethical acceptability.
This study investigates perceptions of the potential of AI in Neuroscience, the bioethical and neuroethical dilemmas arising from the use of AI algorithms and Big Data, and the role of physicians in algorithmically supported by clinical decision-making.
The study involved 427 participants from different academic disciplines and levels of study. Data were collected using the “AI, Neuroscience and Bio(ethical) Dilemmas” instrument, developed based on the international literature. The instrument explores three interrelated domains: the perceived potential of AI in Neuroscience, emerging neuroethical dilemmas, and the role of physicians in AI-assisted clinical decision-making. Descriptive and implicative statistical methods were employed to analyse the data.
The findings reveal positive perceptions of AI’s potential to influence cognitive and perceptual functions and contribute to the management of psychiatric, neurological, and other brain-related disorders. At the same time, a coherent constellation of neuroethical concerns emerges around individual autonomy, neural-data privacy, human rights, algorithmic bias, transparency, and accountability. The findings further highlight the importance attributed to preserving physicians’ clinical judgment and responsibility rather than transferring therapeutic decision-making exclusively to algorithmic systems.

The integration of AI into Neuroscience should not be understood solely as a technological advancement, but also as a challenge of neuroethical governance. Responsible and sustainable integration requires a human-centred framework in which algorithmic innovation complements rather than displaces human judgment. Such a framework should safeguard autonomy, dignity, privacy, fairness, transparency, and clinical accountability while enabling the benefits of AI-driven neuroscience to be translated responsibly into research and clinical practice.