Towards Human-AI Interaction in Medical Emergency Call Handling

Simple item page
dc.contributor.authorMaletzki, Carsten
dc.contributor.authorElsenbast, Christian
dc.contributor.authorReuter-Oppermann, Melanie
dc.date.accessioned2023-12-26T18:40:15Z
dc.date.available2023-12-26T18:40:15Z
dc.date.issued2024-01-03
dc.identifier.doi10.24251/HICSS.2023.407
dc.identifier.isbn978-0-9981331-7-1
dc.identifier.otherc36d7c3f-855e-45ef-b008-2f2bc83b8af3
dc.identifier.urihttps://hdl.handle.net/10125/106790
dc.language.isoeng
dc.relation.ispartofProceedings of the 57th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectDecision Support for Healthcare Processes and Services
dc.subjecthybrid intelligence
dc.subjectmedical emergency calls
dc.subjectmental picture
dc.subjectmental workload
dc.titleTowards Human-AI Interaction in Medical Emergency Call Handling
dc.typeConference Paper
dc.type.dcmiText
dcterms.abstractCall-takers in emergency medical dispatch centers typically rely on decision-support systems that help to structure emergency call dialogues and propose appropriate responses. Current research investigates whether such systems should follow a hybrid intelligent approach, which requires their extension with interfaces and mechanisms to enable an interaction between call-takers and artificial intelligence (AI). Yet unclear is how these interfaces and mechanisms should be designed to foster call handling performances while making efficient use of call-taker's often strained mental capacities. This paper moves towards closing this gap by 1) deriving required artifacts for human-AI interaction and 2) proposing an iterative procedure for their design and evaluation. For 1), we apply the guidelines for human-AI interaction and conduct workshops with domain experts. For 2), we argue that performing a full evaluation of the artifacts is too extensive at earlier iterations of the design process, and therefore propose to enact use-case-driven lightweight evaluations instead.
dcterms.extent10 pages
prism.startingpage3374

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
0331.pdf
Size:
689.1 KB
Format:
Adobe Portable Document Format
Download

Collections

Decision Support for Healthcare Processes and Services