Artificial Intelligence and Environmental Justice: A Critical Review of Social Work Literature

Background and Purpose: Artificial Intelligence (AI) has transformed our everyday lives, though few are aware of how it works, where it comes from, and the extent of its global reach. For example, AI’s environmental impact is profound and growing. AI data centers account for over 3% of global greenhouse gas emissions - potentially exceeding 14% by 2040. AI requires extraordinary amounts of electricity, water, and rare minerals, contributing to environmental distress and human rights abuses. And it is fueled by numerous underpaid gig workers, working long hours in substandard conditions . Given social work’s Grand Challenge to “urgently advance climate and environment justice” while centering vulnerable populations, it is crucial for social workers to seriously engage with this aspect of AI’s rapid growth.

There has been a proliferation of social work literature focused on AI in the last five years. Mirroring the broader discourse, many social workers are optimistic about AI’s impact on practice, research and education. Some, however, worry about the potential for AI to exacerbate existing injustices. The purpose of this integrative literature review was to examine recent social work discourse regarding AI and determine the manner and the extent to which social workers are grappling with AI’s environmental justice (EJ) implications.

Methods: An integrative literature review is a form of secondary research, contributing to a topic’s knowledge via synthesis and critique. We conducted a critical integrative review of social work literature guided by 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 EJ impacts of AI?

We reviewed 52 pieces of literature focused on AI and social work practice, education, or research, published between 2020-2025. The literature included peer-reviewed academic articles as well as gray literature, which is inclusive of, but not limited to, podcasts, online journals, and blogs. Each piece of literature was read thoroughly and summarized in detail by at least two researchers. Summaries were then analyzed for themes.

Findings: The analysis revealed a core theme that we called Proceed (with caution), which reflects a prevailing optimism about AI in social work; tempered by some notes of concern. Subthemes included innovation, efficiency, benefits to clients, and the need for social work perspective. Concerns about AI, which were often noted but not emphasized, primarily focused on ethical dilemmas that may result in negative downstream effects on social workers and clients. There was almost no acknowledgement of the nature of AI itself or its environmental impact.

Conclusion and Implications: The findings suggest several pathways for future social work research and practice. While the literature touts many potential benefits of AI, more research is needed to substantiate those claims and identify unintended consequences. Additionally, social workers need to engage in a more robust discussion of the ethical concerns raised in the literature, which were often not explored in depth. Finally, social work’s commitment to social justice cannot be met without engaging with all aspects of AI, including its environmental and social impact.