Designing Chatbots with Black Americans with Chronic Conditions: Overcoming Challenges against COVID-19
dc.contributor.author | Kim, Junhan | |
dc.contributor.author | Muhic, Jana | |
dc.contributor.author | Robert, Lionel + "Jr" | |
dc.contributor.author | Park, Sun Young | |
dc.date.accessioned | 2022-01-13T17:02:56Z | |
dc.date.available | 2022-01-13T17:02:56Z | |
dc.date.issued | 2022-01-13 | |
dc.identifier.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 . | en_US |
dc.identifier.uri | https://doi.org/10.1145/3491102.3502116 | |
dc.identifier.uri | https://hdl.handle.net/2027.42/171296 | en |
dc.description.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. | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | CHI 2022 | en_US |
dc.subject | Black American community | en_US |
dc.subject | COVID19 | en_US |
dc.subject | COVID | en_US |
dc.subject | participatory design | en_US |
dc.subject | chronic condition | en_US |
dc.subject | chatbot | en_US |
dc.subject | Race and ethnicity | en_US |
dc.subject | healthcare | en_US |
dc.subject | Black American communities | en_US |
dc.subject | marginalized groups | en_US |
dc.subject | marginalized groups healthcare | en_US |
dc.subject | Artificial Intelligence | en_US |
dc.subject | Artificial Intelligence Healthcare | en_US |
dc.subject | conversational agents | en_US |
dc.subject | mental illnesses | en_US |
dc.subject | healthcare inequality | en_US |
dc.subject | human computer healthcare | en_US |
dc.subject | Health Care Technology | en_US |
dc.subject | Healthcare Technology | en_US |
dc.subject | mHealth | en_US |
dc.subject | COVID-19 challenges | en_US |
dc.subject | health services | en_US |
dc.subject | healthcare access | en_US |
dc.subject | Human-centered computing | en_US |
dc.subject | marginalized populations | en_US |
dc.subject | mobile health technology | en_US |
dc.subject | healthcare literacy | en_US |
dc.subject | mental health | en_US |
dc.subject | Artificial Intelligence Trust | en_US |
dc.subject | COVID-19 pandemic | en_US |
dc.subject | personalized health recommendations | en_US |
dc.title | Designing Chatbots with Black Americans with Chronic Conditions: Overcoming Challenges against COVID-19 | en_US |
dc.type | Conference Paper | en_US |
dc.subject.hlbsecondlevel | Information Science | |
dc.subject.hlbtoplevel | Social Sciences | |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.contributor.affiliationum | Information, School of | en_US |
dc.contributor.affiliationum | Robotics Institute | en_US |
dc.contributor.affiliationumcampus | Ann Arbor | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/171296/1/Kim et al. 2022 CHI22.pdf | |
dc.identifier.doi | 10.1145/3491102.3502116 | |
dc.identifier.doi | https://dx.doi.org/10.7302/3808 | |
dc.identifier.source | 2022 Conference on Human Factors in Computing Systems | en_US |
dc.identifier.orcid | 0000-0002-1410-2601 | en_US |
dc.description.filedescription | Description of Kim et al. 2022 CHI22.pdf : Preprint | |
dc.description.depositor | SELF | en_US |
dc.identifier.name-orcid | Robert, Lionel P.; 0000-0002-1410-2601 | en_US |
dc.working.doi | 10.7302/3808 | en_US |
dc.owningcollname | Information, School of (SI) |
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