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dc.contributor.author | Kashima, Hisashi | en |
dc.contributor.author | Oyama, Satoshi | en |
dc.contributor.author | Arai, Hiromi | en |
dc.contributor.author | Mori, Junichiro | en |
dc.contributor.alternative | 鹿島, 久嗣 | ja |
dc.date.accessioned | 2025-06-11T01:53:30Z | - |
dc.date.available | 2025-06-11T01:53:30Z | - |
dc.date.issued | 2024-12 | - |
dc.identifier.uri | http://hdl.handle.net/2433/294621 | - |
dc.description.abstract | Human 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.iso | eng | - |
dc.publisher | Springer Nature | en |
dc.rights | This 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.rights | The 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.rights | If 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.rights | To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. | en |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | - |
dc.subject | Human-in-the-loop AI/ML | en |
dc.subject | Reliability/availability/serviceability of human computation | en |
dc.subject | AI Ethics | en |
dc.subject | Collaborative intelligence | en |
dc.title | Trustworthy human computation: a survey | en |
dc.type | journal article | - |
dc.type.niitype | Journal Article | - |
dc.identifier.jtitle | Artificial Intelligence Review | en |
dc.identifier.volume | 57 | - |
dc.identifier.issue | 12 | - |
dc.relation.doi | 10.1007/s10462-024-10974-1 | - |
dc.textversion | publisher | - |
dc.identifier.artnum | 322 | - |
dc.relation.url | https://dblp.uni-trier.de/db/journals/air/air57.html#KashimaOAM24 | - |
dcterms.accessRights | open access | - |
dc.identifier.pissn | 0269-2821 | - |
dc.identifier.eissn | 1573-7462 | - |
出現コレクション: | 学術雑誌掲載論文等 |

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