Information session: How might we create trauma-informed AI: Introducing TIAKIT

Learn how to use trauma-informed principles in AI supported service delivery

About the session:

AI and automation is expanding in social service sector with potential for enhanced services. At the same time, AI supported service delivery can generate or retrigger trauma. This presentation introduces participants to the Trauma Informed AI Assessment Toolkit (TIAKIT, www.tiakit.com), which has been co-designed with social service professionals using trauma-informed principles. It is designed to assist organisations self-assess to future or current use of AI and automation. 

This session will cover: 

• the trauma-informed principles underpinning TIAKIT
• how AI systems can shape service-user experiences
• live demonstrations of TIAKIT in action; and
• how to apply the toolkit prompts in individual service contexts.

Participants will also hear about opportunities to pilot TIAKIT, access implementation support, contribute feedback, and engage in ongoing research.

Download the one-pager on the TIAKIT.

About the facilitators

• Dr Lyndal Sleep (CQU) works in the Qld Centre for Domestic and Family Violence Research, and studies the intersection of technology, policy and service delivery.
• Associate Professor Suzanna Fay (Criminology, UQ) is interested in comparative aspects of crime and has perceptions of child maltreatment and abuse and its consequences for reporting, monitoring, and court outcomes for children and families.
• Professor Paul Henman (Sociology/Social Policy, UQ) has long studied the role of digital technologies in social policy making and social service delivery.
• Dr Awais Hameed Khan (Designer, UQ) works on human-computer interaction projects, developing participatory design tools and methods.
• Suvradip Maitra (ANU) is a PhD student Suvradip and is interested in combining legal and ethical theories with social science research methods to understand the impact of algorithmic systems on marginalised populations, particularly CALD populations and First Nations Peoples.