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2022
Journal Article
Titel

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

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.
Author(s)
Geurts, Amber
TNO, Strategic Analysis and Policy; Rathenau Institute
Gutknecht, Ralph
Fraunhofer-Institut für System- und Innovationsforschung ISI
Warnke, Philine
Fraunhofer-Institut für System- und Innovationsforschung ISI
Goetheer, Arjen
TNO, Strategic Analysis and Policy; VU Univ. Amsterdam
Schirrmeister, Elna
Fraunhofer-Institut für System- und Innovationsforschung ISI
Bakker, Babette
TNO, Strategic Analysis and Policy
Meissner, Svetlana
Fraunhofer-Institut für System- und Innovationsforschung ISI
Zeitschrift
Futures & foresight science
DOI
10.1002/ffo2.99
File(s)
N-638448.pdf (1.34 MB)
Language
English
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Fraunhofer-Institut für System- und Innovationsforschung ISI
Tags
  • AI

  • data supported foresi...

  • framework

  • hybrid AI‐exper...

  • innovation management...

  • strategic decision ma...

  • strategic foresight

  • technology management...

  • trend detection

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