The Role of Artificial Intelligence (AI) and machine learning in social work practice

Mackline Nuwasiima 1, Metogbe Patricia Ahonon 1 and Caleb Kadiri 2

1 Faculty of Social Work, University of Manitoba, Winnipeg, Canada.
2 Software/Machine Learning Specialist, Morgan State University, Baltimore, Md, USA.
 
Review Article
World Journal of Advanced Research and Reviews, 2024, 24(01), 080–097
Article DOI: 10.30574/wjarr.2024.24.1.2998
 
Publication history: 
Received on 20 August 2024; revised on 28 September 2024; accepted on 30 September 2024
 
Abstract: 
The integration of Artificial Intelligence (AI) and Machine Learning (ML) into social work practice is transforming the landscape of service delivery and decision-making. This paper explores how these technologies enhance case management, predictive analytics, and resource allocation in critical areas such as child welfare, mental health, and substance abuse treatment. Key trends highlighted include the use of AI-based predictive analytics to identify at-risk populations and facilitate early interventions, as well as the deployment of chatbots and virtual assistants for providing accessible mental health counselling and social support. Furthermore, the paper addresses ethical considerations and challenges associated with AI implementation, particularly the potential biases in algorithms that may affect the assessment of social needs. Additionally, the integration of AI tools into social work education and training is examined to prepare future professionals for a technology-driven environment. By analysing the current applications of Natural Language Processing (NLP) for client data analysis, AI-powered software for predictive risk assessments, and automated case management systems, this paper advocates for a balanced approach to AI adoption, ensuring that the core values of social work, such as equity and social justice, remain central to practice. Ultimately, this exploration underscores the potential of AI and ML to enhance social work outcomes while also emphasizing the necessity of ethical frameworks and ongoing training for practitioners.
 
Keywords: 
Artificial Intelligence; Machine Learning; Social Work; Predictive Analytics; Ethical Considerations; Case Management
 
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