ABSTRACT
Authors examine the multifaceted role of artificial intelligence in cognitive neuroscience, clinical practice, and education, highlighting both opportunities and responsibilities. In cognitive neuroscience, AI enables the decoding of brain signals, the alignment of computational models with neural data, and the large-scale analysis of complex cognitive patterns, offering unprecedented insight into brain function. In clinical workflows, AI supports early risk detection, decision-making assistance, and conversational agents that augment patient interaction, potentially improving outcomes through timely intervention and continuous monitoring. In education, AI facilitates adaptive tutoring, personalized learning, and support for learners with special needs, enhancing engagement and responsiveness. While these applications offer substantial benefits – earlier detection of cognitive or health issues, individualized learning, and scalable monitoring – they also introduce critical requirements for clinical validity, safety, human oversight, and robust data protection. To navigate these challenges, the chapter proposes “extended-mind” practices, in which AI performs computational pattern recognition while clinicians and educators retain interpretive authority, ethical judgment, and empathetic engagement. By combining computational innovation with human judgment and values, the chapter presents a framework for responsible, effective, and ethically grounded AI integration that enhances insight, decision-making, and educational support while safeguarding trust and human-centered practice.
