Transforming artificial intelligence into artificial wisdom

Abstract

A rapidly expanding behavioral epidemic of loneliness is profoundly affecting mental and physical health of individuals and communities worldwide. Empirical research shows that, unlike intelligence, human wisdom can mitigate loneliness and promote mental well-being. However, there is a severe global shortage of mental healthcare workforce required to support population-level well-being. Although artificial intelligence is advancing rapidly, it lacks core attributes of wisdom, including compassion, self-reflection, emotional regulation and acceptance of diverse perspectives. The development of artificial wisdom systems could operationalize wisdom-related functions and provide scalable tools to promote mental well-being without implying machine consciousness or subjective experience. While wisdom presents substantial conceptual challenges for computational implementation, recent large language models have demonstrated emerging capabilities in domains previously considered uniquely human. Progress toward artificial wisdom will require new computational frameworks, including mixture-of-experts architectures and agentic systems designed to model human psychosocial needs. Key challenges include ethical and safety considerations requiring rigorous evaluation, validated grounding data, longitudinal assessment and privacy protection. Close collaboration among experts in mental health, technology and ethics is crucial. A strategic shift from artificial intelligence toward artificial wisdom, at both individual and population levels, is critical for advancing global mental health and well-being.