Ethical Implications of AI in Neuroscience-Discussing the Challenges and Responsibilities of using AI in Brain Disease Research

Abstract

The modern era of brain disease research has begun with the introduction of artificial intelligence (AI) into neuroscience, opening the door to previously unheard-of breakthroughs in the identification, management, and understanding of intricate neural disorders. However, there are also certain ethical difficulties with this integration. The ethical implications of utilizing AI in neuroscience are looked at in this work, with particular attention dedicated to important concerns including data privacy, prejudice, and responsibility. Concerns regarding patient confidentiality and permission are raised by the sensitive nature of neurological data, especially in light of the possibility that AI systems will process enormous volumes of personal and medical data. The necessity for fair and open AI systems is further highlighted by the possibility that algorithmic prejudice in AI models could result in differences in treatment outcomes. Accountability for AI-driven decisions in a profession where incorrect diagnoses or treatments could have catastrophic consequences is another important topic covered. This study highlights the need for academics, developers, and legislators to carefully consider these ethical issues in order to guarantee that AI advancements in neuroscience put the welfare, accuracy, and equity of individuals first.