VIRTUAL Prague Research & Teaching Conference

Abstract

This research examined the ethical and moral implications of integrating Large Language Models (LLMs) in mental health contexts. Through comprehensive literature review and ethical analysis, we identified a complex landscape of benefits and challenges. LLMs demonstrated potential for expanding access to mental health support, reducing stigma through perceived anonymity, and providing consistent supplementary care between traditional therapy sessions. However, significant limitations emerged, including inadequate emotional intelligence, instances of harmful misinformation, substantial privacy and data security concerns, persistent algorithmic biases, and inability to effectively manage crisis situations. Our ethical analysis, framed within established bioethical principles of autonomy, beneficence, non-maleficence, and justice, revealed critical gaps in the current regulatory framework, particularly regarding classification of these tools, liability attribution, informed consent processes, and clinical validation standards. The research found that while LLMs show promise as complementary tools in mental health care, they cannot ethically replace human practitioners. This study represents the first phase of our investigation; subsequent research will include practitioner interviews, user experience surveys, and case studies of existing implementations to develop comprehensive guidelines for the responsible integration of AI in mental health care settings.