2026-03-07
Michael Massey, Ian Williams, Grace Polistina, Eathan Breaux
Section: Literature Reviews Keywords: social work, artificial intelligence, AI, social work ethics, structural social work, environmental justice, critical data studies, political economy INTRODUCTION : Social work discourse regarding artificial intelligence (AI) in practice, research, and education has proliferated over the last 5 years, reflecting both excitement over its potential and ambivalence about its ethical challenges. However, the extent to which social work is fully engaging with the structure of AI and its enormous impacts on the environment, labour, and distribution of power remains unclear. METHODS : An integrative review of social work literature from 2020–2024 was conducted to address two research questions: 1) What is the nature of the social work discourse related to AI? 2) To what extent is the discourse addressing the structural aspects of AI? Integrative review is a methodology used to summarise empirical/theoretical/gray literature to provide a comprehensive understanding of a phenomenon and assess current themes, tensions, and gaps. FINDINGS: The literature overwhelmingly touted AI’s potential benefits for social work practice, research, and education. Discussions of ethical challenges, which often lacked depth and detail, narrowly focused on the downstream impacts of AI. The literature was almost entirely devoid of structural perspectives on AI. CONCLUSION: Findings suggest that social workers tend to view AI as an area of computation rather than a vast political, financial, and social system that impacts the experiences, opportunities, and lived environments of social workers and clients. Social workers will be better positioned to use AI responsibly and influence its development if they engage with AI from a structural perspective, committed to sustainability and justice.
2026-03-07
Andreas Møller Jørgensen
Section: Original Articles Keywords: Radicalisation, Metaphor, Social media INTRODUCTION: There is growing concern and empirical evidence that AI based harms are related to systemic problems and injustices. But it is not clear how this relation can be conceptualised. The article develops and presents a metaphor of a carnival mirror as a theoretical framework for empirical analysis. METHODS: The carnival mirror metaphor frames the relation between AI system and systemic issues regarding distorted reflections. The metaphor directs the analytical focus on how AI systems reflect an assemblage of discourses and practices and how these reflections can become vehicles for critical learning and experimentation. The metaphor is applied in a case study based on interviews, observation notes, and documents of the development of radicalisation-prevention measures in a Danish social service department that uses AI and algorithms to detect hate speech on social media. FINDINGS: The case study reveals how the AI system distortedly reflects cultural and professional assumptions about social media use, data, radicalisation, vulnerability, and democracy. It illustrates how such reflections can create space for learning about democratic and political engagement, young people at risk of radicalisation, social media use, and a sense of belonging and community. CONCLUSIONS: The article contributes with a metaphor for understanding how AI systems can be a vehicle for self-reflective and experimental critiques and offers recommendations for practice. Learning from AI systems is important lest we risk stifling government responses and reproducing potentially problematic and counterproductive strategies and practices.
2026-03-07
Taruvinga Muzingili
Section: Original Articles Keywords: Crisis intervention, artificial intelligence, social work practice INTRODUCTION: This study aimed to explore how social workers experience and make sense of AI use in crisis intervention, focusing on what AI misses and how practitioners respond. METHODS: Using a descriptive-phenomenological design, 12 Zimbabwean social workers with international experience in technologically advanced settings in the UK and the US) were purposively sampled. Data were collected through semi-structured interviews and analysed using Giorgi’s phenomenological method, supported by MAXQDA software. FINDINGS: Findings revealed five key themes: (1) AI’s inability to capture relational knowing in emotionally charged encounters; (2) discomfort with the opaque logic behind algorithmically generated outputs; (3) tensions between data efficiency and human dignity; (4) reassertion of professional judgment through ethical reflexivity; and (5) the emotional labour of working alongside AI in crisis contexts. Participants consistently described AI as helpful for structure but limited in its support for the trauma-informed, culturally responsive, and ethically attuned dimensions of crisis care that exceed the capacity of current systems to process. CONCLUSIONS: The study concludes that AI cannot replace the embodied, intuitive, and relational dimensions of social work in crisis settings. Implications for practice include the need for human-centred AI design, transparent decision-support systems, and frameworks that preserve professional discretion. A relational and reflexive approach to AI integration is essential to ensure that technological innovation enhances rather than undermines the dignity and care at the heart of crisis social work.
2026-03-07
Emily Keddell, Neil Ballantyne
Section: Editorial Editorial for issue 38(1)
2026-03-07
Mercedes Muriel Saiz, Maribel Martín Estalayo, Xoán Lombardero-Posada, Virginia Páez Izquierdo
Section: Original Articles Keywords: Social work, social services, mass media, image, stereotype INTRODUCTION: The purpose of this article is to examine the images, identity, and publicperception of social work in the media and how these affect the everyday professional practice of social workers. This has been a concern for the profession since its origins, given the implications it holds for establishing a helping relationship and its direct or indirect influence on the configuration of social policies. The research addresses the following questions: (1) what are the dominant discourses about social work and social workers in the media? (2) how do these discourses influence public perceptions and professional relationships? (3) how do social workers interpret and respond to these representations? METHOD: We conducted a qualitative case study in a city near Madrid, drawing on 22 semi-structured interviews with social workers in primary and specialised public social services and one focus group ( n = 6). FINDINGS: The results point to a stereotyped image of the social work profession. Misinformation, bias, and some of the negative representations analysed affect both public perception and the relationship with service users. This highlights the need for the social work profession to adopt a more active role in managing its public image. CONCLUSIONS: Media portrayals were seen as stereotyped and sensationalised, often linking social work to crisis, negligence, and social control, undermining trust and practice relationships. Findings indicate a need for proactive, coordinated communication, through professional bodies, journalists, and digital channels, to support fairer public understanding.