Artificial Intelligence and Implications for the Australian Social Work Journal

Abstract

Social work is a profession committed to integrity and social justice. The AASW Social Work Practice Standards (AASW, 2023) calls on social workers to be critically reflective, ethical practitioners engaged in lifelong professional development and learning. Equally, social work education seeks to prepare students for research-informed, culturally-responsive practice across a diverse range of contexts, and in this Issue, we showcase critical social work education and practice diversity. However, a different ethical challenge to integrity and practice standards is the focus of this Editorial. Here, we highlight some of the concerns and implications of generative Artificial Intelligence (generative AI) for social work education, research, practice, and scholarly publishing. In November 2022, OpenAI released ChatGPT, a generative AI Large Language Model (LLM) that could generate realistic and natural text outputs from simple prompts. This technology had been in development for some time but had not been released to the public for general use. Since then, there has been a proliferation of different AI models that can generate and augment text, images, video, and audio. Generative AI is being used to perform analytical and interpretive tasks such as language translation; responding to queries on specific data sources, coding, and interpreting code; summarising documents and webpages; and creating case assessments and plans. This technology can be used to construct legal documents; machine learning for facial recognition; and for undertaking medical, mental health, and other diagnostic assessments. These are just some examples. In this fast-moving field, the uses and applications seem endless. The open-sourcing of generative AI models and their underlying architecture means developers are starting to create a myriad of practical applications and tools that rapidly increase the depth and scale of automation, potentially replacing or augmenting many everyday tasks normally performed by humans. The implications for social work education, practice, research, and scholarship are extensive. As with any new technology, there are a range of stances, from early adopters to positions that have resonance with luddism. This adds to the complexities of responding to AI as a whole profession. Nevertheless, what is clear is that the rise and integration of generative AI systems, at scale, will yield a wide range of practical, ethical, and epistemological problems for many professions, including social work. It is to some of these problems we turn our attention below. Beginning with social work education, generative AI will have profound effects on assessment and learning for higher education providers. It is likely to cause educators to re-evaluate their educational practices, assessments, and assumptions about what is core to a social work curriculum. Social work will need to refine and reappraise its ideas about critical thinking, ethical decision making, professional judgement, and reflective practice—all skills that are considered core to effective social work practice as outlined in the AASW Practice Standards (AASW, 2023). How will we ensure students have an educational environment that promotes