Scoping review reveals limited empirical evidence and prominent ethical challenges for AI in child and youth social work, highlighting the need for responsible human-AI collaboration.
Despite artificial intelligence's (AI) established use in healthcare, its application in social work remains nascent. Therefore, this scoping review examines AI's applications, outcomes or perceived effects, and challenges in social work practice for children and youth, especially regarding human–AI collaboration. Searches across eight databases yielded 17 studies spanning four tiers of evidence, ranging from empirical findings to theoretical discussions. AI's applications centered on identifying service users in the five empirically evaluated studies but varied widely in theoretical accounts. Regarding outcomes, only those five studies provided rigorous evaluations, with mixed results. Across all tiers, AI played a supporting role, while social workers retained professional judgment and final decision‐making authority. Last, AI's challenges ranged from technical limitations to ethical and structural concerns, including algorithmic bias, privacy risks, contextual complexity, and unclear accountability. Such limited, uneven evidence suggests priorities for future research and AI's responsible integration in social work for children and youth.
No takes yet. Share an insight, caveat, or question.
Lifen et al. (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: