{"title":"New perspectives for data-supported foresight: The hybrid AI-expert approach","authors":"Amber Geurts, Ralph Gutknecht, Philine Warnke, Arjen Goetheer, Elna Schirrmeister, Babette Bakker, 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.