Barbara Hiltz
Biographic Data
| ID | 6615358 |
|---|---|
| NAME | Barbara Hiltz |
| GIVEN NAMES | Barbara |
| FAMILY NAME | Hiltz |
| SIGNATURE | HILTZ B |
| AFFILIATIONS | University of Michigan |
| VERIFIED | No |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 1 |
| WORKS AS AUTHOR | 4 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 1 |
AI-Enhanced Social Work
This article introduces the application of retrieval-augmented generation (RAG) technology, aiming to enhance decision making and client support through artificial intelligence (AI)–enhanced tools. RAG addresses the critical challenge of ensuring accuracy and reliability in AI-generated content by integrating generative AI with domain-specific knowledge bases. Through a case study, we explore the development and assessment of a RAG-powered tool d…
Introducing Generative Artificial Intelligence Into the MSW Curriculum
The most recent Council on Social Work Education’s Educational Policy and Accreditation Standards (EPAS) demands that social workers develop competence in the ethical and professional deployment of technology. Arguably, artificial intelligence has become a critical element in the technological landscape, most recently with the advent of Generative Artificial Intelligence (GenAI). Beginning in late 2022, there has been an explosion of interest in …
Computerized Suicide Prevention Clinical Training Simulations
Preliminary findings indicate simulated training with virtual clients is promising and suggest the three suicide prevention simulations may be useful, scalable, and effective in social work training programs and beyond
Teaching Note—Data Science in the MSW Curriculum
Recent and rapid technological advances have given rise to an explosive growth of data, along with low-cost solutions for accessing, collecting, managing, and analyzing data. Despite the advances in technology and the availability of data, social work organizations routinely encounter data-related problems that have an impact on their opportunities for making data-driven decisions. Although training in research methods and statistics is important…
Computerized Suicide Prevention Clinical Training Simulations
Preliminary findings indicate simulated training with virtual clients is promising and suggest the three suicide prevention simulations may be useful, scalable, and effective in social work training programs and beyond
Teaching Note—Data Science in the MSW Curriculum
Recent and rapid technological advances have given rise to an explosive growth of data, along with low-cost solutions for accessing, collecting, managing, and analyzing data. Despite the advances in technology and the availability of data, social work organizations routinely encounter data-related problems that have an impact on their opportunities for making data-driven decisions. Although training in research methods and statistics is important…
Computerized Suicide Prevention Clinical Training Simulations
Preliminary findings indicate simulated training with virtual clients is promising and suggest the three suicide prevention simulations may be useful, scalable, and effective in social work training programs and beyond
Introducing Generative Artificial Intelligence Into the MSW Curriculum
The most recent Council on Social Work Education’s Educational Policy and Accreditation Standards (EPAS) demands that social workers develop competence in the ethical and professional deployment of technology. Arguably, artificial intelligence has become a critical element in the technological landscape, most recently with the advent of Generative Artificial Intelligence (GenAI). Beginning in late 2022, there has been an explosion of interest in …
AI-Enhanced Social Work
This article introduces the application of retrieval-augmented generation (RAG) technology, aiming to enhance decision making and client support through artificial intelligence (AI)–enhanced tools. RAG addresses the critical challenge of ensuring accuracy and reliability in AI-generated content by integrating generative AI with domain-specific knowledge bases. Through a case study, we explore the development and assessment of a RAG-powered tool d…
Social Work (4 works) · Medical education (3 works) · Medicine (3 works) · Political science (3 works) · Psychology (3 works) · Artificial Intelligence in Healthcare and Education (2 works) · Computer Science (2 works) · Curriculum (2 works) · Engineering (2 works) · Pedagogy (2 works)