Building and Governing AI Systems: Advancing Social Workers' Roles across the Technology Industry, Human Service Organizations, and Policy Institutions

2026-08-04

AI Summary

This study addresses the growing integration of artificial intelligence into social services and the concomitant marginalization of social workers in AI development and governance. Bridging AI governance frameworks, product management methodologies, and the 2022 Educational Policy and Accreditation Standards (EPAS) for social work education, it proposes a cross-disciplinary competency model that systematically identifies critical roles for social workers across five domains: product management, governance, technical leadership, collaboration, and policy. Using product management as an illustrative case, the paper demonstrates a strong alignment between core social work competencies and technical functions, offering the first mapping of social work expertise onto central stages of AI system development and governance. This reframing advances ethical considerations from post-deployment to pre-deployment phases and outlines pathways for cultivating hybrid social work–technology professionals alongside a corresponding research agenda.

Abstract

Artificial intelligence is moving the technology sector into domains social work has long served, including crisis response, mental health care, benefits administration, vocational rehabilitation, and child welfare. Social workers meet technology teams as users of their tools, as subjects in their datasets, and as first responders to what those systems deploy, yet they study these systems from outside the settings where the decisions are made. This paper introduces the standard roles on a technology product team and the decisions each one controls, reviews the disciplines around AI-era technology together with the social work scholarship that meets each, and identifies five groups of technology decision roles social workers can hold across the technology industry, human service organizations, and policy institutions, spanning product, governance, organizational technology leadership, grantee collaboration, and policy work. Product management is our primary example. We set the nine competencies of the 2022 Educational Policy and Accreditation Standards against the tasks that role performs to show where MSW training already teaches the method the job asks for. We then specify the technical understanding these roles require, extend the profession's technology ethics from use to deployment, and close with a research agenda for the profession's technology workforce.

Problem

• artificial intelligence
• social work
• technology governance
• AI ethics
• human service organizations

Innovation

• AI governance
• social work competencies
• technology roles
• ethical deployment
• interdisciplinary collaboration