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This paper introduces a framework using AI-simulated expert panels to generate and evaluate socio-technical scenarios, addressing limitations in traditional scenario generation methods. The framework employs AI models to simulate domain experts, uses probabilistic Cross-Impact Balance analysis for pathway generation and stress-testing, and incorporates AI stakeholder panels for multi-criteria decision analysis. Applied to Germany's energy transition, the framework demonstrates its ability to create internally consistent pathways and offers a scalable alternative for scenario generation and policy stress-testing.
Forget resource-intensive workshops – AI can now simulate entire expert panels to generate and stress-test socio-technical scenarios, opening doors to rapid policy exploration.
Socio-technical scenarios for net-zero and other transformation pathways combine qualitative storylines with quantitative models, embedding them in plausible societal contexts for model assessment. Conventional scenario generation is resource-intensive, can be limited in internal consistency and diversity of expert and stakeholder perspectives, and is rarely stress-tested. This paper introduces a synthetic, AI-based expert panel to address these bottlenecks. An AI model first simulates domain experts who agree on descriptors, states, and their interactions. A probabilistic Cross-Impact Balance analysis then generates internally consistent pathways, using stochastic shocks to assess robustness and pathway diversity. An AI stakeholder panel uses multi-criteria decision analysis to select a preferred pathway; an AI expert panel translates it into model-ready quantitative inputs. Although scalable and applicable to any other country or region, the framework is applied to Germany's energy transition as a proof of concept, and offers an alternative and/or supplement to scenario generation. Furthermore, it enables Virtual AI-Led Decision Laboratories for exploratory policy stress-testing and provides an approach for rapid, structured expert elicitation and decision support in other domains.
