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Trauma-informed AI: Developing and testing a practical AI audit framework for use in social services

Focus Areas: Social Services
Research Program: Machines
Status: Active

Artificial Intelligence (AI) is increasingly being used in the delivery of social services. While it offers opportunities for more efficient, effective and personalised service delivery, AI can also generate greater problems, reinforcing disadvantage, generating trauma or re-traumatising service users.

Conducted by a multi-disciplinary research team with extensive expertise in the intersection of social services and digital technology, this project seeks to co-design an innovative AI trauma-informed audit framework to assess the extent to which an AI’s decisions may generate new trauma or re-traumatise.

The value of a trauma-informed AI audit framework is not simply to assess digital technologies after they are built and in operation, but also to inform designs of digital technologies and digitally enabled social services from their inception.

It will be road-tested using multiple case studies of AI use in child/family services, domestic and family violence services, and social security/welfare payments.


Paul Henman

Prof Paul Henman

Lead Investigator,
University of Queensland

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ADM+S Investigator Philip Gillingham

Dr Philip Gillingham

Associate Investigator,
University of Queensland

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Lyndal Sleep profile picture

Dr Lyndal Sleep

Central Queensland University

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Suzanna Fay

Dr Suzanna Fay

Senior Lecturer,
University of Queensland

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University of Notre Dame-IBM Tech Ethics Lab

University of Notre Dame-IBM Tech Ethics Lab

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