Artificial Intelligence (AI) is becoming more widely prevalent in social work practice (Reamer, 2023). AI uses computer science to replicate human intelligence to enable problem-solving while using machine learning that uses historical data to predict and shape new outputs. Generative AI is a subset of AI technology that has the capacity to create generative images, text, audio, and videos based on pre-trained data sets. As AI technologies continue to evolve and integrate into social work practice, it's crucial to examine the impact on the profession. This article explores the benefits and risks associated with AI in social work, as well as the important ethical considerations and responsible use.
Potential Benefits
The integration of AI in social work offers several potential opportunities and benefits that could enhance the efficiency and effectiveness of social work services for clients, organizations, and communities (Reamer, 2023). It can be used across micro, mezzo, and macro practices including direct service, case management, supervision, community assessments, community organizing, grant writing, research, and policy.
Specifically, generative AI tools can help social workers with administrative tasks allowing them to have more time for direct practice services (Tomita et al., 2024). For example, ChatGPT can create and generate client notes, create psychoeducation materials, and develop treatment plan goals (Goldkind et al., 2023). There are also AI behavioral health chatbots like Woebot that can stimulate therapeutic conversations and Wysa is an AI chatbot service that uses evidence-based cognitive behavioral techniques to assist people (Reamer, 2023). Predictive AI Analytics, known as data forecasting, can also be used to enhance decision-making and service delivery (Goldkind, 2021).
Potential Risks
Despite these potential benefits and opportunities, utilizing AI can also pose some risks for social workers (Goldkind et al., 2023; Reamer, 2023). One risk of utilizing AI tools is that they are inherently biased. AI is dependent on machine learning that uses very large existing data sets of human knowledge and information which may not be fully representative of social workers’ clients (Reamer, 2023). As a result, AI algorithms may be biased related to gender, ethnicity, sexual orientation, and other underrepresented identities (Patton et al., 2023).
AI tools are also known to make mistakes and can hallucinate generating fictitious information (Alkaissi & McFarlane, 2023). Therefore, social workers must utilize their social work expertise and knowledge when reviewing the content generated by AI tools and make the necessary edits when appropriate. AI should never replace social work knowledge (Meilvang, 2023); instead, AI technology should be used as a tool alongside social work practitioners.
Ethical Considerations
The integration of AI in social work raises several important ethical considerations that must be carefully addressed. Social workers should exercise professional competency when using AI tools (Pascoe, 2023). This includes attending trainings and building their knowledge about AI tools to ensure responsible practices. Responsible and ethical practice includes clients being fully informed about how AI is being used in their care and having the right to opt out of AI-driven services if they choose (Reamer, 2023). Social workers should also ensure that the AI tools they are using have data encryption and data security to the greatest extent when possible (Reamer, 2023). Social workers should also not enter any identifiable or confidential information into the generative AI chatbots for ethical and responsible practice.
Social work agencies and organizations should develop comprehensive AI guidelines for their staff to ensure the ethical and effective use of AI in practice. In clinical supervision, it is equally important for supervisors and supervisees to discuss and explore how AI can be integrated as a teaching and training tool, enhancing the overall supervision experience for social workers for transparency and accountability. Currently, the National Association of Social Workers (NASW) has not established specific ethical guidelines for the use of AI in social work practice. The last ethical standards for technology use and social work practice were published in 2017 (NASW, CSWE, ASWB, & CSWA, 2017). This was published before generative AI technologies. Therefore, it is recommended that agencies and practitioners take proactive steps to develop their own ethical frameworks for AI use, ensuring that AI is applied responsibly and in alignment with social work values.
Conclusion: Future Considerations
Social work education and training programs will need to evolve to include teaching AI literacy to make sure that future social workers are equipped to use these technologies effectively (Hodgson et al., 2022). Additionally, interdisciplinary collaboration between social workers and technologists will be essential (Patton et al., 2023) in developing AI tools for social workers that ensure ethical practice.
Overall, the integration of AI in social work presents opportunities, risks, and ethical considerations. While AI has the potential to enhance social work services and save time for administrative tasks, it also raises concerns about bias and ethical implications. It’s crucial to approach this integration responsibly and ethically. AI should not replace the human aspect of social work practice; instead, our professionals should still promote and practice interpersonal interaction, genuine communication, and empathy (O’Leary & Tsui, 2023).