Artificial Intelligence Algorithms, Bias, and Innovation: Implications for Social Work

Abstract

PURPOSE: Artificial Intelligence (AI) technologies are rapidly expanding across diverse contexts. As the reach of AI continues to grow, there is a need to examine student perspectives on the increasing prevalence of AI and AI-based practice approaches in social work. MATERIALS AND METHODS: In this qualitative study, we conducted structured interviews with 15 students in bachelors and masters social work programs. We developed an interview guide with a list of questions to ask students and no prior knowledge of AI was required by the students. The study was framed based on an interpretive phenomenological analysis approach. RESULTS: Through thematic analysis, five key themes were developed, including 1) Risks associated with AI, 2) Ethical Concerns in AI and Technology Use, 3) Bias and Fairness in AI, 4) Applications and Possibilities of AI in Social Work, and 5) Training and Awareness of AI in Social Work. DISCUSSION: Social workers can help disadvantaged clients by ensuring access to the various AI technologies and facilitating social welfare interventions created using these technologies. There is a need to address the gap in the existing literature about the use of AI in social work practice and education. Social work researchers can explore and conduct future studies that utilize mixed methods methodologies that can evaluate the use of AI in social work domains. CONCLUSION: This study highlights the need to increase awareness of AI in social work education and practice settings given the potential of these technologies to aid various aspects of social work practice.

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