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dc.contributor.authorKashima, Hisashien
dc.contributor.authorOyama, Satoshien
dc.contributor.authorArai, Hiromien
dc.contributor.authorMori, Junichiroen
dc.contributor.alternative鹿島, 久嗣ja
dc.date.accessioned2025-06-11T01:53:30Z-
dc.date.available2025-06-11T01:53:30Z-
dc.date.issued2024-12-
dc.identifier.urihttp://hdl.handle.net/2433/294621-
dc.description.abstractHuman computation is an approach to solving problems that prove difficult using AI only, and involves the cooperation of many humans. Because human computation requires close engagement with both “human populations as users” and “human populations as driving forces, ” establishing mutual trust between AI and humans is an important issue to further the development of human computation. This survey lays the groundwork for the realization of trustworthy human computation. First, the trustworthiness of human computation as computing systems, that is, trust offered by humans to AI, is examined using the RAS (reliability, availability, and serviceability) analogy, which define measures of trustworthiness in conventional computer systems. Next, the social trustworthiness provided by human computation systems to users or participants is discussed from the perspective of AI ethics, including fairness, privacy, and transparency. Then, we consider human–AI collaboration based on two-way trust, in which humans and AI build mutual trust and accomplish difficult tasks through reciprocal collaboration. Finally, future challenges and research directions for realizing trustworthy human computation are discussed.en
dc.language.isoeng-
dc.publisherSpringer Natureen
dc.rightsThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.en
dc.rightsThe images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material.en
dc.rightsIf material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.en
dc.rightsTo view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.en
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/-
dc.subjectHuman-in-the-loop AI/MLen
dc.subjectReliability/availability/serviceability of human computationen
dc.subjectAI Ethicsen
dc.subjectCollaborative intelligenceen
dc.titleTrustworthy human computation: a surveyen
dc.typejournal article-
dc.type.niitypeJournal Article-
dc.identifier.jtitleArtificial Intelligence Reviewen
dc.identifier.volume57-
dc.identifier.issue12-
dc.relation.doi10.1007/s10462-024-10974-1-
dc.textversionpublisher-
dc.identifier.artnum322-
dc.relation.urlhttps://dblp.uni-trier.de/db/journals/air/air57.html#KashimaOAM24-
dcterms.accessRightsopen access-
dc.identifier.pissn0269-2821-
dc.identifier.eissn1573-7462-
出現コレクション:学術雑誌掲載論文等

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