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Transferring AI Explainability to User-Centered Explanations of Complex COVID-19 Information
24th International Conference on Human-Computer Interaction, HCII 2022 ; 13518 LNCS:441-460, 2022.
Article in English | Scopus | ID: covidwho-2173820
ABSTRACT
This paper presents a user-centered approach to translating techniques and insights from AI explainability research to developing effective explanations of complex issues in other fields, on the example of COVID-19. We show how the problem of AI explainability and the explainability problem in the COVID-19 pandemic are related as two specific instances of a more general explainability problem, occurring when people face in-transparent, complex systems and processes whose functioning is not readily observable and understandable to them ("black boxes”). Accordingly, we discuss how we applied an interdisciplinary, user-centered approach based on Design Thinking to develop a prototype of a user-centered explanation for a complex issue regarding people's perception of COVID-19 vaccine development. The developed prototype demonstrates how AI explainability techniques can be adapted and integrated with methods from communication science, visualization and HCI to be applied to this context. We also discuss results from a first evaluation in a user study with 88 participants and outline future work. The results indicate that it is possible to effectively apply methods and insights from explainable AI to explainability problems in other fields and support the suitability of our conceptual framework to inform that. In addition, we show how the lessons learned in the process provide new insights for informing further work on user-centered approaches to explainable AI itself. © 2022, The Author(s).
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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 24th International Conference on Human-Computer Interaction, HCII 2022 Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 24th International Conference on Human-Computer Interaction, HCII 2022 Year: 2022 Document Type: Article