Key Points from “Empowering Social Service with AI”
Overview
The document presents a participatory design study focused on integrating Generative AI (GenAI) into social service practices. The study involved workshops and contextual inquiries with social service practitioners, exploring how AI can alleviate administrative burdens and improve decision-making while addressing concerns about algorithmic bias and practitioner identity.
Findings
1. Opportunities for AI Integration
Participants identified several areas where GenAI could enhance their work:
- Documentation Efficiency: AI tools could assist in automating the creation of standardized reports, allowing practitioners to convert rough notes into formal documents quickly. This would mitigate the repetitive nature of documentation, freeing up time for more client-focused activities.
- Case Assessments and Intervention Planning: GenAI can help in synthesizing information to produce comprehensive client assessments and suggest intervention plans based on established therapeutic models. This capability is particularly beneficial for junior workers who may lack experience in formulating effective interventions.
- Supervision Support: AI can aid supervisors by generating discussion points and questions for case reviews, enhancing the overall quality of supervision and mentoring for junior staff.
2. Concerns and Risks
Despite the potential benefits, several concerns were raised:
- Privacy and Data Security: Protecting sensitive client information is paramount, and there are fears that AI tools could inadvertently expose or mishandle this data.
- Overreliance on AI: There is a significant concern that practitioners, especially those new to the field, may become overly dependent on AI outputs, potentially diminishing their critical thinking and analytical skills.
- Quality of AI Outputs: Participants noted that while AI can assist in many tasks, its outputs are not always reliable. Inaccurate or contextually inappropriate suggestions could lead to poor decision-making, especially in high-stakes situations.
Conclusions
The study concludes that while GenAI presents promising opportunities for enhancing social service practices, careful implementation is crucial. Practitioners generally view the integration of AI positively, seeing it as a tool to alleviate administrative burdens and improve service delivery. However, to ensure effective use, organizations must address the highlighted concerns regarding data privacy, the quality of AI-generated content, and the risk of overreliance.
The findings suggest that AI should not replace human judgment but rather act as a complementary tool that enhances the capabilities of social service practitioners. Future research should focus on optimizing AI tools for social service contexts, ensuring they are tailored to meet the unique needs of practitioners while safeguarding the essential human elements of the profession.
In summary, the study emphasizes a balanced approach to AI integration, advocating for systems that augment human capabilities without undermining the critical thinking and ethical considerations that are fundamental to social work.
Source: Yugin Tan, Soh Kai Xin, Zhang Renwen, Lee Jungup, Meng Han, Biswadeep Sen, and Lee Yi-Chieh. 2025. Empowering Social Service with AI: Insights from a Participatory Design Study with Practitioners. In Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (CHI EA ’25), April 26-May 1, 2025, Yokohama, Japan. ACM, New York, NY, USA, 10 pages. https://doi.org/10.1145/3706599.3719736
