Dialectical AI in Foresight: Advancing Futures Literacy with the Futures’ Fingerprints+AI Method

This paper presents Futures’ Fingerprints+AI, an augmented foresight method integrating Dialectical AI (Artificial Intelligence) sparring into an interactive boundary object for collaborative scenario assessment. The study explores how personalized AI-driven feedback, shifting from the traditional human-in-the-loop to an AI-in-the-loop approach, can enhance structured group evaluation, foster multi-perspective thinking, and strengthen Futures Literacy. Empirical results from an international student cohort show that the AI-augmented process enabled rapid, well-founded evaluation of complex scenarios, accelerated convergence in scenario likelihood assessments, and supported individual and collective critical reflection. Further, the method contributed to measurable gains in Futures Literacy. The findings highlight scenario evaluation's normative and cultural layers, emphasizing the need for transparent, responsible AI integration in foresight. Future research should further examine how hybrid intelligence systems can leverage AI’s capacity to distribute information and reduce complexity while preserving human epistemic authority, especially in light of ethical challenges linked to the transition from AI to Artificial General Intelligence.

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Publication Details

Journal
ScholarSpace (University of Hawaii at Manoa)
Published
2025-12-23
Primary Topic
Sustainability and Climate Change Governance
Type
article
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article

Dialectical AI in Foresight: Advancing Futures Literacy with the Futures’ Fingerprints+AI Method

Caroline V. Rudzinska, Jonah L. Schierding, Hermann W. Klöckner, Roland M. Mueller
ScholarSpace (University of Hawaii at Manoa)
Sustainability and Climate Change Governance
article

Dialectical AI in Foresight: Advancing Futures Literacy with the Futures’ Fingerprints+AI Method

Caroline V. Rudzinska, Jonah L. Schierding, Hermann W. Klöckner, Roland M. Mueller
article en

Abstract

This paper presents Futures’ Fingerprints+AI, an augmented foresight method integrating Dialectical AI (Artificial Intelligence) sparring into an interactive boundary object for collaborative scenario assessment. The study explores how personalized AI-driven feedback, shifting from the traditional human-in-the-loop to an AI-in-the-loop approach, can enhance structured group evaluation, foster multi-perspective thinking, and strengthen Futures Literacy. Empirical results from an international student cohort show that the AI-augmented process enabled rapid, well-founded evaluation of complex scenarios, accelerated convergence in scenario likelihood assessments, and supported individual and collective critical reflection. Further, the method contributed to measurable gains in Futures Literacy. The findings highlight scenario evaluation's normative and cultural layers, emphasizing the need for transparent, responsible AI integration in foresight. Future research should further examine how hybrid intelligence systems can leverage AI’s capacity to distribute information and reduce complexity while preserving human epistemic authority, especially in light of ethical challenges linked to the transition from AI to Artificial General Intelligence.

ScholarSpace (University of Hawaii at Manoa)
Quality Education
Openalex Percentile: Top 36%
Sustainability and Climate Change Governance
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