Show simple item record

Designing Chatbots with Black Americans with Chronic Conditions: Overcoming Challenges against COVID-19

dc.contributor.authorKim, Junhan
dc.contributor.authorMuhic, Jana
dc.contributor.authorRobert, Lionel + "Jr"
dc.contributor.authorPark, Sun Young
dc.date.accessioned2022-01-13T17:02:56Z
dc.date.available2022-01-13T17:02:56Z
dc.date.issued2022-01-13
dc.identifier.citationKim, 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.urihttps://doi.org/10.1145/3491102.3502116
dc.identifier.urihttps://hdl.handle.net/2027.42/171296en
dc.description.abstractRecently, 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.isoen_USen_US
dc.publisherCHI 2022en_US
dc.subjectBlack American communityen_US
dc.subjectCOVID19en_US
dc.subjectCOVIDen_US
dc.subjectparticipatory designen_US
dc.subjectchronic conditionen_US
dc.subjectchatboten_US
dc.subjectRace and ethnicityen_US
dc.subjecthealthcareen_US
dc.subjectBlack American communitiesen_US
dc.subjectmarginalized groupsen_US
dc.subjectmarginalized groups healthcareen_US
dc.subjectArtificial Intelligenceen_US
dc.subjectArtificial Intelligence Healthcareen_US
dc.subjectconversational agentsen_US
dc.subjectmental illnessesen_US
dc.subjecthealthcare inequalityen_US
dc.subjecthuman computer healthcareen_US
dc.subjectHealth Care Technologyen_US
dc.subjectHealthcare Technologyen_US
dc.subjectmHealthen_US
dc.subjectCOVID-19 challengesen_US
dc.subjecthealth servicesen_US
dc.subjecthealthcare accessen_US
dc.subjectHuman-centered computingen_US
dc.subjectmarginalized populationsen_US
dc.subjectmobile health technologyen_US
dc.subjecthealthcare literacyen_US
dc.subjectmental healthen_US
dc.subjectArtificial Intelligence Trusten_US
dc.subjectCOVID-19 pandemicen_US
dc.subjectpersonalized health recommendationsen_US
dc.titleDesigning Chatbots with Black Americans with Chronic Conditions: Overcoming Challenges against COVID-19en_US
dc.typeConference Paperen_US
dc.subject.hlbsecondlevelInformation Science
dc.subject.hlbtoplevelSocial Sciences
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumInformation, School ofen_US
dc.contributor.affiliationumRobotics Instituteen_US
dc.contributor.affiliationumcampusAnn Arboren_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/171296/1/Kim et al. 2022 CHI22.pdf
dc.identifier.doi10.1145/3491102.3502116
dc.identifier.doihttps://dx.doi.org/10.7302/3808
dc.identifier.source2022 Conference on Human Factors in Computing Systemsen_US
dc.identifier.orcid0000-0002-1410-2601en_US
dc.description.filedescriptionDescription of Kim et al. 2022 CHI22.pdf : Preprint
dc.description.depositorSELFen_US
dc.identifier.name-orcidRobert, Lionel P.; 0000-0002-1410-2601en_US
dc.working.doi10.7302/3808en_US
dc.owningcollnameInformation, School of (SI)


Files in this item

Show simple item record

Remediation of Harmful Language

The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.

Accessibility

If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.