Designing Chatbots with Black Americans with Chronic Conditions: Overcoming Challenges against COVID-19
Kim, Junhan; Muhic, Jana; Robert, Lionel + "Jr"; Park, Sun Young
2022-01-13
Citation
Kim, J., Muhic, J., Robert, L. P. and Park, S. Designing Chatbots with Black Americans with Chronic Conditions: Overcoming Challenges against COVID-19, Proceedings of the 40th ACM Conference on Human Factors in Computing Systems (CHI 2022), April 30 - May 6 2022, New Orleans, LA .
Abstract
Recently, chatbots have been deployed in health care in various ways such as providing educational information, and monitoring and triaging symptoms. However, they can be ineffective when they are designed without a careful consideration of the cultural context of the users, especially for marginalized groups. Chatbots designed without cultural understanding may result in loss of trust and disengagement of the user. In this paper, through an interview study, we attempt to understand how chatbots can be better designed for Black American communities within the context of COVID-19. Along with the interviews, we performed design activities with 18 Black Americans that allowed them to envision and design their own chatbot to address their needs and challenges during the pandemic. We report our findings on our participants’ needs for chatbots’ roles and features, and their challenges in using chatbots. We then present design implications for future chatbot design for the Black American population.Publisher
CHI 2022
Deep Blue DOI
Other DOIs
Subjects
Black American community COVID19 COVID participatory design chronic condition chatbot Race and ethnicity healthcare Black American communities marginalized groups marginalized groups healthcare Artificial Intelligence Artificial Intelligence Healthcare conversational agents mental illnesses healthcare inequality human computer healthcare Health Care Technology Healthcare Technology mHealth COVID-19 challenges health services healthcare access Human-centered computing marginalized populations mobile health technology healthcare literacy mental health Artificial Intelligence Trust COVID-19 pandemic personalized health recommendations
Types
Conference Paper
Metadata
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