Critical participatory action for technology that can support transformative justice and change

INTRODUCTION: As artificial intelligence, algorithms, and data-driven technologies become more embedded in social services, education, health care, and justice systems, concerns continue to grow about how these tools may reproduce existing social inequities. METHODS: From a critical social work perspective, this article examines the ways in which artificial intelligence (AI) development and implementation can reinforce racism, ableism, classism, and other forms of structural oppression particularly through predictive and surveillance-based decision-making practices. The article explores how data-collection practices and algorithmic design are shaped by historical and institutional bias, despite frequent claims that these technologies are neutral or objective. Drawing on examples from criminal justice, child welfare, and health settings that utilised custom-built enterprise models, the analysis highlights the risks of opacity, universalisation, and feedback loops that can deepen harm for marginalised individuals and communities. FINDINGS: In response, the article advances an intersectional power analysis and proposes a critical participatory practice approach to technology development. By centring the knowledge, experiences, and leadership of those most impacted by AI-driven systems, this approach positions technology as a potential tool for transformational justice rather than social control. CONCLUSION: The article concludes by arguing that ethical engagement with AI in social work requires ongoing reflexivity, political accountability, and meaningful community participation.