AI prompting training in social work education: An environmental scan and proposed framework
Monte-Angel RichardsonBackground
As generative artificial intelligence (AI) becomes increasingly harnessed in the helping professions, social workers are considering the usefulness of these tools while navigating how AI use aligns with their profession's values. AI prompting is the practice of crafting strategic questions, instructions, or context cues to guide large language models (LLMs) in producing outputs. AI prompting competency involves the ability to design, refine, and evaluate prompts to generate useful and professionally aligned outputs. Despite its growing usage and presence, AI prompting competency in social work settings often lacks standardized training, raising ethical concerns regarding how its use aligns with the profession's core tenets.
Objective
This paper explores the potential introduction of AI prompt training in social work education.
Method
This paper presents the results of an environmental scan of scholarship on AI literacy and prompting training in social work and related fields. The results of this scan are then used to inform a proposed conceptual framework to guide AI prompting training in the field of social work, presented with a case study.
Results
The conceptual model is presented as a starting point in educational settings that can be refined and problematized by researchers and educators to standardize prompting training in the field of social work.
Conclusions
It is essential that the social work profession develops consistent competencies and training for prompting and ethical decision-making which enhance AI literacy. This paper employed a conceptual framework to serve as a bridge between AI prompting skill development and social work ethical decision-making.