Abstract
As Artificial Intelligence (AI) continues to permeate various sectors, its integration into social work practice,
particularly in identifying at-risk families, demands a nuanced understanding and ethical engagement from
future social workers. This paper presents an account of a simulation-based learning exercise conducted with
Masters in Social Work [MSW] students at an Irish university. Through role-playing as different stakeholders,
students engaged with a fictional scenario that involved the deployment of an AI algorithm in Ireland for
identifying at-risk families. The exercise illuminated diverse perspectives on the implications of AI in social
work, highlighting key ethical dilemmas, regulatory challenges and the need for comprehensive education on
AI technologies. The findings support the effectiveness of simulation-based learning as an effective way to
prepare social work students for the ethical, practical, and policy complexities of integrating AI into their
future practice.
particularly in identifying at-risk families, demands a nuanced understanding and ethical engagement from
future social workers. This paper presents an account of a simulation-based learning exercise conducted with
Masters in Social Work [MSW] students at an Irish university. Through role-playing as different stakeholders,
students engaged with a fictional scenario that involved the deployment of an AI algorithm in Ireland for
identifying at-risk families. The exercise illuminated diverse perspectives on the implications of AI in social
work, highlighting key ethical dilemmas, regulatory challenges and the need for comprehensive education on
AI technologies. The findings support the effectiveness of simulation-based learning as an effective way to
prepare social work students for the ethical, practical, and policy complexities of integrating AI into their
future practice.
| Original language | English (Ireland) |
|---|---|
| Title of host publication | Ubiquity Proceedings |
| Subtitle of host publication | EDEN Conference, Graz, Austria |
| Publisher | Ubiquity Press |
| Number of pages | 9 |
| DOIs | |
| Publication status | Published - 2024 |
| Event | EDEN (European Digital Education Network) 2024: Learning in the Age of AI: Towards Imaginative Futures - University of Graz, Graz, Austria Duration: 16 Jun 2024 → 18 Jun 2024 https://eden-europe.eu/event/eden-2024-annual-conference/ |
Conference
| Conference | EDEN (European Digital Education Network) 2024 |
|---|---|
| Abbreviated title | EDEN2024 |
| Country/Territory | Austria |
| City | Graz |
| Period | 16/06/24 → 18/06/24 |
| Internet address |
Name of Affiliated ATU Research Unit
- HEAL - Health and Biomedical Research Centre
