通过以人为中心的人工智能镜头绘制公民科学

J. Rafner, M. Gajdacz, Gitte Kragh, A. Hjorth, A. Gander, Blanka Palfi, Aleksandra Berditchevskiaia, F. Grey, Y. Gal, A. Segal, Mike Wamsley, J. Miller, Dominik Dellermann, M. Haklay, Pietro Michelucci, J. Sherson
{"title":"通过以人为中心的人工智能镜头绘制公民科学","authors":"J. Rafner, M. Gajdacz, Gitte Kragh, A. Hjorth, A. Gander, Blanka Palfi, Aleksandra Berditchevskiaia, F. Grey, Y. Gal, A. Segal, Mike Wamsley, J. Miller, Dominik Dellermann, M. Haklay, Pietro Michelucci, J. Sherson","doi":"10.15346/hc.v9i1.133","DOIUrl":null,"url":null,"abstract":"Artificial Intelligence (AI) can augment and sometimes even replace human cognition. Inspired by efforts to value human agency alongside productivity, we discuss and categorize the potential of solving Citizen Science (CS) tasks with Hybrid Intelligence (HI), a synergetic mixture of human and artificial intelligence. Due to the unique participant-centered set of values and the abundance of tasks drawing upon both human common sense and complex 21st century skills, we believe that the field of CS offers an invaluable testbed for the development of human-centered AI including HI, while also benefiting CS. In order to investigate this potential, we first relate CS to adjacent computational disciplines. Then, we demonstrate that CS projects can be grouped according to their potential for HI-enhancement by examining two key dimensions: the level of digitization and the amount of knowledge or experience required for participation. Finally, we propose a framework for types of human-AI interaction in CS based on established criteria of HI. This “HI lens” provides the CS community with an overview of ways to utilize the combination of AI and human intelligence in their projects. For AI researchers, this work highlights the opportunity CS presents to engage with real-world data sets and explore new AI methods and applications.","PeriodicalId":92785,"journal":{"name":"Human computation (Fairfax, Va.)","volume":"16 1","pages":"66-95"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Mapping Citizen Science through the Lens of Human-Centered AI\",\"authors\":\"J. Rafner, M. Gajdacz, Gitte Kragh, A. Hjorth, A. Gander, Blanka Palfi, Aleksandra Berditchevskiaia, F. Grey, Y. Gal, A. Segal, Mike Wamsley, J. Miller, Dominik Dellermann, M. Haklay, Pietro Michelucci, J. Sherson\",\"doi\":\"10.15346/hc.v9i1.133\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Artificial Intelligence (AI) can augment and sometimes even replace human cognition. Inspired by efforts to value human agency alongside productivity, we discuss and categorize the potential of solving Citizen Science (CS) tasks with Hybrid Intelligence (HI), a synergetic mixture of human and artificial intelligence. Due to the unique participant-centered set of values and the abundance of tasks drawing upon both human common sense and complex 21st century skills, we believe that the field of CS offers an invaluable testbed for the development of human-centered AI including HI, while also benefiting CS. In order to investigate this potential, we first relate CS to adjacent computational disciplines. Then, we demonstrate that CS projects can be grouped according to their potential for HI-enhancement by examining two key dimensions: the level of digitization and the amount of knowledge or experience required for participation. Finally, we propose a framework for types of human-AI interaction in CS based on established criteria of HI. This “HI lens” provides the CS community with an overview of ways to utilize the combination of AI and human intelligence in their projects. For AI researchers, this work highlights the opportunity CS presents to engage with real-world data sets and explore new AI methods and applications.\",\"PeriodicalId\":92785,\"journal\":{\"name\":\"Human computation (Fairfax, Va.)\",\"volume\":\"16 1\",\"pages\":\"66-95\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-11-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Human computation (Fairfax, Va.)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.15346/hc.v9i1.133\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Human computation (Fairfax, Va.)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15346/hc.v9i1.133","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

摘要

人工智能(AI)可以增强,有时甚至取代人类的认知。受重视人类代理和生产力的努力的启发,我们讨论并分类了用混合智能(HI)解决公民科学(CS)任务的潜力,混合智能是人类和人工智能的协同混合。由于独特的以参与者为中心的价值观,以及利用人类常识和21世纪复杂技能的大量任务,我们相信计算机科学领域为包括HI在内的以人为中心的人工智能的发展提供了宝贵的测试平台,同时也使计算机科学受益。为了研究这种潜力,我们首先将计算机科学与相邻的计算学科联系起来。然后,我们通过检查两个关键维度:数字化水平和参与所需的知识或经验的数量,证明了计算机科学项目可以根据其增强hi的潜力进行分组。最后,基于已建立的人机交互标准,我们提出了CS中人机交互类型的框架。这个“HI镜头”为CS社区提供了在他们的项目中利用人工智能和人类智能结合的方法的概述。对于人工智能研究人员来说,这项工作突出了CS提供的与现实世界数据集接触并探索新的人工智能方法和应用的机会。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mapping Citizen Science through the Lens of Human-Centered AI
Artificial Intelligence (AI) can augment and sometimes even replace human cognition. Inspired by efforts to value human agency alongside productivity, we discuss and categorize the potential of solving Citizen Science (CS) tasks with Hybrid Intelligence (HI), a synergetic mixture of human and artificial intelligence. Due to the unique participant-centered set of values and the abundance of tasks drawing upon both human common sense and complex 21st century skills, we believe that the field of CS offers an invaluable testbed for the development of human-centered AI including HI, while also benefiting CS. In order to investigate this potential, we first relate CS to adjacent computational disciplines. Then, we demonstrate that CS projects can be grouped according to their potential for HI-enhancement by examining two key dimensions: the level of digitization and the amount of knowledge or experience required for participation. Finally, we propose a framework for types of human-AI interaction in CS based on established criteria of HI. This “HI lens” provides the CS community with an overview of ways to utilize the combination of AI and human intelligence in their projects. For AI researchers, this work highlights the opportunity CS presents to engage with real-world data sets and explore new AI methods and applications.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信