A Wizard-of-Oz Interface and Persona-based Methodology for Collecting Health Counseling Dialog

By William R. Kearns, Neha Kaura, Myra Divina, C. Vo, Dong Si, T. Ward, Weichao Yuwen. 2020

20 citations recorded by the source corpus.

Health dialog collection is the primary bottleneck for the training and deployment of conversational agents into clinical practice. Current tools for the development of dialog systems are primarily focused on writing intent-slot schemas for natural language understanding and finite-state models of dialog management. However, this is a time-consuming process that can be opaque for clinical teams and the limitations of both approaches are well understood. The health domain presents additional barriers including access to patients and concerns about exposing personal health information. The contribution of this work is two-fold. First, it describes an interface designed to augment the ability of clinicians to efficiently engage in high-quality and empathetic health counseling dialog with their patients. Second, it presents a WOZ protocol for collecting this dialog using standardized patient actors each playing a role from a pool of caregiver personas.

Subfields: Artificial Intelligence, Natural Language Processing, Dialogue & Conversational AI, Human-Computer Interaction

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Citations in the corpus

Symbolic Knowledge Distillation: from General Language Models to Commonsense Models (2021, background): “…including interactive learning through a conversational interface (Arabshahi et al., 2021), persona-and affect-aware conversation models (Kearns et al., 2020), ﬁgura-tive language understanding (Chakrabarty et al., 2020, 2021), story telling (Ammanabrolu et al., 2021a) and fantasy games…”
Neural Theory-of-Mind? On the Limits of Social Intelligence in Large LMs (2022, background): “empathy, interlocutor perspective, and social intelligence (Kearns et al., 2020; Sharma et al., 2021).”
COMET-ATOMIC 2020: On Symbolic and Neural Commonsense Knowledge Graphs (2020, background): “This flexibility allows them to be used out-of-the-box, and they have been applied to new, previously unexplored tasks, such as sarcastic comment generation (Chakrabarty et al. 2020), therapy chatbots (Kearns et al. 2020), and automated story plot generation (Ammanabrolu et al. 2020).”
The Participatory Turn in AI Design: Theoretical Foundations and the Current State of Practice (2023, background): “[114] leveraged actors trained to role-play as patients to explore the possible needs of caregivers.”