New perspectives for data-supported foresight: The hybrid AI-expert approach

Amber Geurts, Ralph Gutknecht, Philine Warnke, Arjen Goetheer, Elna Schirrmeister, Babette Bakker, Svetlana Meissner
{"title":"New perspectives for data-supported foresight: The hybrid AI-expert approach","authors":"Amber Geurts,&nbsp;Ralph Gutknecht,&nbsp;Philine Warnke,&nbsp;Arjen Goetheer,&nbsp;Elna Schirrmeister,&nbsp;Babette Bakker,&nbsp;Svetlana Meissner","doi":"10.1002/ffo2.99","DOIUrl":null,"url":null,"abstract":"<p>This paper outlines new perspectives for data-supported foresight by combining participatory expert-based futures dialogues with the power of artificial intelligence (AI) in what we call the hybrid AI-expert-based foresight approach. To this end, we present a framework of five typical steps in a fully fledged foresight process ranging from scoping to strategizing and show how AI can be integrated into each of the steps to enable the hybrid AI-expert foresight approach. Building on this, we present experiences gained from two recent research projects of TNO and Fraunhofer ISI that deal with aspects of the hybrid AI-expert foresight approach and give insights into the opportunities and challenges of the new perspectives for data-supported foresight that this approach enables. Finally, we summarize open questions and challenges for future research.</p>","PeriodicalId":100567,"journal":{"name":"FUTURES & FORESIGHT SCIENCE","volume":"4 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ffo2.99","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"FUTURES & FORESIGHT SCIENCE","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/ffo2.99","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9

Abstract

This paper outlines new perspectives for data-supported foresight by combining participatory expert-based futures dialogues with the power of artificial intelligence (AI) in what we call the hybrid AI-expert-based foresight approach. To this end, we present a framework of five typical steps in a fully fledged foresight process ranging from scoping to strategizing and show how AI can be integrated into each of the steps to enable the hybrid AI-expert foresight approach. Building on this, we present experiences gained from two recent research projects of TNO and Fraunhofer ISI that deal with aspects of the hybrid AI-expert foresight approach and give insights into the opportunities and challenges of the new perspectives for data-supported foresight that this approach enables. Finally, we summarize open questions and challenges for future research.

Abstract Image

数据支持预测的新视角:混合人工智能专家方法
本文通过将参与式基于专家的期货对话与人工智能(AI)的力量相结合,概述了数据支持的预测的新视角,即我们所说的基于人工智能专家的混合预测方法。为此,我们提出了一个框架,在一个成熟的预测过程中,包括从范围确定到战略制定的五个典型步骤,并展示了如何将人工智能集成到每个步骤中,以实现混合人工智能专家预测方法。在此基础上,我们介绍了从TNO和Fraunhofer ISI最近的两个研究项目中获得的经验,这些项目涉及混合人工智能专家预测方法的各个方面,并深入了解这种方法所带来的数据支持预测新视角的机遇和挑战。最后,我们总结了未来研究的开放性问题和挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
7.00
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