Show simple item record

ICIS 2019 SIGHCI Workshop Panel Report: Human Computer Interaction Challenges and Opportunities for Fair, Trustworthy and Ethical Artificial Intelligence

dc.contributor.authorRobert, Lionel
dc.contributor.authorBansal, Gaurav
dc.contributor.authorLütge, Christoph
dc.date.accessioned2020-06-30T14:50:07Z
dc.date.available2020-06-30T14:50:07Z
dc.date.issued2020-06-30
dc.identifier.citationRobert, L. P., Gaurav, B., & Lütge, C. (2020). ICIS 2019 SIGHCI Workshop Panel Report: Human–Computer Interaction Challenges and Opportunities for Fair, Trustworthy and Ethical Artificial Intelligence. AIS Transactions on Human-Computer Interaction, 12(2), pp. 96-108en_US
dc.identifier.urihttp://aisel.aisnet.org/thci/vol12/iss2/3
dc.identifier.urihttps://hdl.handle.net/2027.42/155874
dc.description.abstractArtificial Intelligence (AI) is rapidly changing every aspect of our society—including amplifying our biases. Fairness, trust and ethics are at the core of many of the issues underlying the implications of AI. Despite this, research on AI with relation to fairness, trust and ethics in the information systems (IS) field is still scarce. This panel brought together academia, business and government perspectives to discuss the challenges and identify potential solutions to address such challenges. This panel report presents eight themes based around the discussion of two questions: (1) What are the biggest challenges to designing, implementing and deploying fair, ethical and trustworthy AI?; and (2) What are the biggest challenges to policy and governance for fair, ethical and trustworthy AI? The eight themes are: (1) identifying AI biases; (2) drawing attention to AI biases; (3) addressing AI biases; (4) designing transparent and explainable AI; (5) AI fairness, trust, ethics: old wine in a new bottle?; (6) AI accountability; (7) AI laws, policies, regulations and standards; and (8) frameworks for fair, ethical and trustworthy AI. Based on the results of the panel discussion, we present research questions for each theme to guide future research in the area of human–computer interaction.en_US
dc.language.isoen_USen_US
dc.publisherAIS Transactions on Human-Computer Interactionen_US
dc.subjectTrustworthy and Ethical Artificial Intelligenceen_US
dc.subjectArtificial Intelligenceen_US
dc.subjectTrustworthy Artificial Intelligenceen_US
dc.subjectEthical Artificial Intelligenceen_US
dc.subjectFair Artificial Intelligenceen_US
dc.subjectAI Fairnessen_US
dc.subjectHuman-Computer Interactionen_US
dc.subjectHuman-Computer Interaction Artificial Intelligenceen_US
dc.subjectEthics in the information systemsen_US
dc.subjectAI biasesen_US
dc.subjectTransparent Artificial Intelligenceen_US
dc.subjectExplainable Artificial Intelligenceen_US
dc.subjectArtificial Intelligence Accountabilityen_US
dc.subjectArtificial Intelligence Governanceen_US
dc.subjectDesigning Artificial Intelligenceen_US
dc.subjectImplementing Artificial Intelligenceen_US
dc.subjectArtificial Intelligence Deployingen_US
dc.subjectArtificial Intelligence Policyen_US
dc.subjectAlgorithmic Biasen_US
dc.subjectAlgorithmic Fairnessen_US
dc.subjectArtificial Intelligence Trusten_US
dc.subjectArtificial Intelligence Ethicsen_US
dc.subjectArtificial Intelligence policiesen_US
dc.subjectArtificial Intelligence regulationsen_US
dc.subjectArtificial Intelligence standardsen_US
dc.subjectEthical frameworksen_US
dc.subjectArtificial Intelligence and Human Interactionsen_US
dc.subjectHuman Interactions with Artificial Intelligenceen_US
dc.subjectGlobal Coordination Artificial Intelligenceen_US
dc.titleICIS 2019 SIGHCI Workshop Panel Report: Human Computer Interaction Challenges and Opportunities for Fair, Trustworthy and Ethical Artificial Intelligenceen_US
dc.title.alternativeHuman Computer Interaction Challenges and Opportunities for Fair, Trustworthy and Ethical Artificial Intelligenceen_US
dc.typeArticleen_US
dc.subject.hlbsecondlevelInformation and Library Science
dc.subject.hlbtoplevelSocial Sciences
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumInformation, School ofen_US
dc.contributor.affiliationumRobotics Instituteen_US
dc.contributor.affiliationotherUniversity of Wisconsinen_US
dc.contributor.affiliationotherTechnical University of Munichen_US
dc.contributor.affiliationumcampusAnn Arboren_US
dc.description.bitstreamurlhttps://deepblue.lib.umich.edu/bitstream/2027.42/155874/1/Robert et al. 2020.pdf
dc.identifier.doi10.17705/1thci.00130
dc.identifier.sourceAIS Transactions on Human-Computer Interactionen_US
dc.identifier.orcid0000-0002-1410-2601en_US
dc.identifier.name-orcidRobert, Lionel P.; 0000-0002-1410-2601en_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.