Zaroukian, Erin, Bakdash, Jonathan Z., Preece, Alun David  ORCID: https://orcid.org/0000-0003-0349-9057 and Webberley, William
2017.
Automation bias with a conversational interface: user confirmation of misparsed information.
Presented at: IEEE Conference on Cognitive and Computational Aspects of Situation Management,
Savannah, GA, USA,
27-31 March 2017.
Cognitive and Computational Aspects of Situation Management (CogSIMA), 2017 IEEE Conference on.
IEEE,
10.1109/COGSIMA.2017.7929605
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Abstract
We investigate automation bias for confirming erroneous information with a conversational interface. Participants in our studies used a conversational interface to report information in a simulated intelligence, surveillance, and reconnaissance (ISR) task. In the task, for flexibility and ease of use, participants reported information to the conversational agent in natural language. Then, the conversational agent interpreted the user’s reports in a human- and machine-readable language. Next, participants could accept or reject the agent’s interpretation. Misparses occur when the agent incorrectly interprets the report and the user erroneously accepts it. We hypothesize that the misparses naturally occur in the experiment due to automation bias and complacency because the agent interpretation was generally correct (92%). These errors indicate some users were unable to maintain situation awareness using the conversational interface. Our results illustrate concerns for implementing a flexible conversational interface in safety critical environments (e.g., military, emergency operations).
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Date Type: | Completion |
| Status: | Published |
| Schools: | Schools > Computer Science & Informatics Research Institutes & Centres > Crime and Security Research Institute (CSURI) |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Publisher: | IEEE |
| Date of First Compliant Deposit: | 28 April 2017 |
| Date of Acceptance: | 20 March 2017 |
| Last Modified: | 21 Oct 2022 07:07 |
| URI: | https://orca.cardiff.ac.uk/id/eprint/99164 |
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