Human services organizations and the responsible integration of AI: Considering ethics and contextualizing risk(s)

TL;DR

This paper proposes a nuanced, risk-based framework for ethically integrating AI into human services organizations, emphasizing context-specific evaluation, responsible implementation, and empirical assessment to balance benefits and ethical concerns.

Contribution

It introduces a dimensional risk assessment approach tailored for AI in human services, moving beyond binary adoption models to consider context-specific ethical and practical factors.

Findings

Risk varies significantly with application context

Local large language models can support responsible AI use

Empirical evaluation starting with low-risk applications is recommended

Abstract

This paper examines the responsible integration of artificial intelligence (AI) in human services organizations (HSOs), proposing a nuanced framework for evaluating AI applications across multiple dimensions of risk. The authors argue that ethical concerns about AI deployment -- including professional judgment displacement, environmental impact, model bias, and data laborer exploitation -- vary significantly based on implementation context and specific use cases. They challenge the binary view of AI adoption, demonstrating how different applications present varying levels of risk that can often be effectively managed through careful implementation strategies. The paper highlights promising solutions, such as local large language models, that can facilitate responsible AI integration while addressing common ethical concerns. The authors propose a dimensional risk assessment approach that considers factors like data sensitivity, professional oversight requirements, and potential impact on client wellbeing. They conclude by outlining a path forward that emphasizes empirical evaluation, starting with lower-risk applications and building evidence-based understanding through careful experimentation. This approach enables organizations to maintain high ethical standards while thoughtfully exploring how AI might enhance their capacity to serve clients and communities effectively.