Aug 2026· International Journal of Technology and Emerging Research· 0 citations· 11 references
TL;DR
It is recommended that Generative AI can revolutionize mental care but can't be a direct substitute for mental health professionals.
Abstract
Mental health conditions are one of the most pressing public health issues globally, impacting people of all ages and making it difficult for people to operate in health care systems around the world. As Generative Artificial Intelligence (GenAI) evolves quickly, it offers novel solutions for mental health care, like AI-powered chatbots, virtual assistants, emotion recognition systems, and personalized digital support platforms. This paper is an analysis of recent studies on the use of generative AI in mental health care which will compare the advantages, drawbacks, and ethical considerations of generative AI. The studies reviewed suggest that AI tools can help with greater accessibility of mental health supports, offer around-the-clock support, increase self-awareness, and decrease loneliness through personalized interactions. However, there are a number of issues to contend with: emotional reliance on AI companions, misinformation, privacy and security concerns, algorithmic bias, and a lack of clinical validation. This paper highlights insights from various studies on the current impact of Generative AI on mental health care and pinpoints areas where research is currently missing. The analysis recommends that Generative AI can revolutionize mental care but can't be a direct substitute for mental health professionals. Moving forward, it is crucial to promote responsible implementation of AI, ethical guidelines, transparency, and robust regulations to maintain safe and reliable mental health care services.
Keywords: mental health; Ethical AI; emotion detection; Privacy; Generative Artificial Intelligence; AI Chatbots; Digital Healthcare; Mental Healthcare
To maximise the health benefits for the public, AI should be used to construct an auxiliary triage system that supports human clinicians and enables appropriate referrals when needed, and presents a dual-edged nature of AI.
Qin Gu· Frontiers in Humanities and...· 0 citations
The International Workshop on AI for Cognitive and Mental Health Support is proposed, a half-day interdisciplinary forum that brings together researchers and practitioners from data mining, machine learning, NLP, NLP, HCI, healthcare, and social sciences to advance trustworthy, effective, and socially responsible AI solutions for cognitive and mental health support.
Xiangmeng Wang, Haoyang Li, Chen Li et al.· Proceedings of the 32nd ACM...· 0 citations
The rapid rise of generative AI chatbots has extended their use beyond task-based assistance into the realms of emotional support, companionship, and informal mental health care. This article examines how individuals engage with general-purpose and companion-oriented AI systems such as ChatGPT and Replika to support their mental well-being. Drawing on qualitative interviews with AI users, supplemented by computational analysis of Reddit discussions, we show that many experience these systems as companions that meet unmet needs for advice, companionship, understanding, and non-judgmental self-disclosure. These relationships are multi-functional, blending emotional expression, advice-seeking, entertainment, identity exploration, and a felt sense of ‘being cared for’. Notably, perceived mental health benefits arise not despite AI’s non-human qualities, but because of them. Users consistently emphasise AI’s availability, patience, emotional safety, and freedom from judgement as preferable to aspects of human therapy. We argue that contemporary AI use reflects a shift from tool-based human–machine interaction toward forms of companionship that offer meaningful psychological support. Recognizing companionship as central to AI’s mental health role requires expanding debates beyond a focus on clinical efficacy to encompass the relational and affective dimensions of care, attachment, and everyday emotional life.
Vincent Miller, Mark J. Hill, Tiago Moreira· Communication and Change· 0 citations
Artificial Intelligence (AI) is rapidly transforming healthcare by supporting clinical decision-making, patient monitoring, documentation, education, research, and personalized care. Mental health nursing is an important area in which AI has the potential to improve early identification of mental health problems, continuous monitoring, therapeutic support, risk assessment, and access to care. Recent advances in machine learning, natural language processing, predictive analytics, conversational agents, and generative AI have expanded the possibilities for supporting individuals experiencing depression, anxiety, psychosis, substance-use disorders, and other mental health conditions. Evidence suggests that AI-based systems can assist in detecting symptoms, predicting clinical risks, monitoring changes in behaviour and mood, and providing accessible digital interventions. However, the use of AI in mental health also creates significant ethical and professional concerns, particularly regarding privacy, confidentiality, informed consent, algorithmic bias, transparency, accountability, patient safety, therapeutic relationships, and the risk of over-reliance on automated systems. Mental health nurses are uniquely positioned to ensure that AI remains person-centred and clinically appropriate because they combine continuous patient observation with therapeutic communication and holistic assessment. This article reviews the major applications and opportunities of AI in mental health nursing, discusses ethical and professional challenges, and proposes future directions for education, research, clinical practice, and policy. AI should be regarded as a supportive technology rather than a replacement for professional nursing judgment or human therapeutic relationships.
Payal Sharma, Milan Agravat, Pranali Mackwan et al.· Adolescência e Saúde· 0 citations
A list of eight best practices was created to assist developers with designing AI systems in a way that would reduce the overall risk of harm for users attempting to use their AI for mental health cases.
Joshua Frankenfield, Briana M. Sobel, Barbara Chaparro· Proceedings of the Internati...· 0 citations
Artificial intelligence is no longer standing outside the doors of mental healthcare. It is entering psychological practice through chatbots, digital therapeutics, AI assisted assessments, symptom monitoring, and virtual mental health assistants. AI can recognize patterns, generate responses, identify possible symptoms, and provide psychological support. But as technology becomes increasingly capable of responding to human distress, a deeper question emerges: Can AI care, or can it only simulate the appearance of care?
This paper examines the ethical challenges emerging at the intersection of artificial intelligence and psychological practice, focusing on privacy, informed consent, algorithmic bias, transparency, accountability, high risk mental health situations, and the therapeutic relationship. It also explores the changing role of psychologists in an increasingly digital mental healthcare system.
The paper argues that AI may assist in delivering mental healthcare, but technological capability cannot be equated with ethical responsibility. If AI influences a psychological decision, who remains responsible when something goes wrong?
To address these concerns, the paper proposes the HUMAN AI Framework, centred on Human Oversight, Understanding and Informed Consent, Mental Health Data Protection, Accountability, Non Discrimination, Assessment of Risk, and Integrity of Clinical Practice. The framework emphasizes that AI should enhance psychological care without displacing human judgment, ethical responsibility, and the relational foundations of meaningful care.
Ultimately, the future of mental healthcare should not be humans versus AI, but humans using AI responsibly.
D. Jahagirdar, Sanskruti Tare· International Journal of Lat...· 0 citations
