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
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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.

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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。
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