EthicAlly: a Prototype for AI-Powered Research Ethics Support for the Social Sciences and Humanities

TL;DR

EthicAlly is a prototype AI system designed to assist social science and humanities researchers in ethics assessment, addressing gaps in tailored ethics support and reducing the burden on human review committees.

Contribution

This paper introduces EthicAlly, a novel AI-powered ethics support system tailored for social sciences and humanities, leveraging constitutional AI and collaborative prompt development.

Findings

EthicAlly provides structured ethics assessments incorporating universal principles and contextual factors.

The system demonstrates potential to support researchers in ethical research design.

EthicAlly can ease the workload of institutional review boards without replacing human oversight.

Abstract

In biomedical science, review by a Research Ethics Committee (REC) is an indispensable way of protecting human subjects from harm. However, in social science and the humanities, mandatory ethics compliance has long been met with scepticism as biomedical models of ethics can map poorly onto methodologies involving complex socio-political and cultural considerations. As a result, tailored ethics training and support as well as access to RECs with the necessary expertise is lacking in some areas, including parts of Europe and low- and middle-income countries. This paper suggests that Generative AI can meaningfully contribute to closing these gaps, illustrating this claim by presenting EthicAlly, a proof-of-concept prototype for an AI-powered ethics support system for social science and humanities researchers. Drawing on constitutional AI technology and a collaborative prompt development methodology, EthicAlly provides structured ethics assessment that incorporates both universal ethics principles and contextual and interpretive considerations relevant to most social science research. In supporting researchers in ethical research design and preparation for REC submission, this kind of system can also contribute to easing the burden on institutional RECs, without attempting to automate or replace human ethical oversight.