Related Experiment Video
Updated: May 1, 2026

High-definition Transcranial Direct Current Stimulation over Right Dorsolateral Prefrontal Cortex to Enhance Metacognitive Sensitivity
Published on: September 26, 2025
A reflexive artificial intelligence governance for transformative change in sustainability
Anna Hausmann1,2,3, Tuuli Toivonen4,5, Gonzalo Cortés-Capano6,7
1Department of Biological and Environmental Science, School of Resource Wisdom, University of Jyväskylä, Survontie 9c, 40500, Jyväskylä, Finland. anna.hausmann87@gmail.com.
Abstract:
Artificial intelligence (AI) is increasingly integrated in sustainability governance, yet most applications remain oriented towards optimisation and prediction, reducing complex social-ecological issues to technical problems. This narrow focus neglects plural values, lived experiences, and democratic judgement essential for transformative change. We advance a reflexive AI governance approach that treats AI as a socio-technical assemblage shaping problem framing, knowledge legitimisation, and authority distribution. Synthesising material, technical, epistemic, and ethico-political challenges, the paper draws on Aristotelian notions of techne, episteme, and phronesis to outline three reflexivity dimensions: design, epistemological, and engagement. Using a four-phase governance cycle and a protected area management scenario, we show how reflexivity can help align AI with plural, justice-oriented transformation pathways. Reflexive AI governance grounded in sustainability's visions fosters deliberation, inclusivity, and ecological sufficiency, enabling democratic capacities over whether and how AI should be used, including the legitimate possibility of non-use, restriction, or withdrawal.
Related Concept Videos
Sustainable Development
Global Regulatory Systems
Self-Regulation
Self-Awareness and Its Effects
The Sense of Self: Reflected Self-Appraisal and Social Comparison
Automatic Processing and Automatic Social Behavior