WISDOM OF AI CROWDS: A PROPOSED THREE-PHASE POLICY SIMULATION FRAMEWORK

Gian Paul Gauci, Alexiei Dingli

Abstract


‘Wicked Problems’ are persistent societal issues characterised by complexity, divergent stakeholder perspectives, and resistance to traditional solutions. A key barrier to addressing them is the inability to experiment with potential policies safely, given their dynamic, high-stakes, and often 'one-shot' nature in the real world. This paper proposes the 'Wisdom of AI Crowds,' a novel conceptual framework designed to overcome this barrier. It employs artificial societies populated by agentic AI, whose personas are grounded in empirical data reflecting stakeholder norms, values, and beliefs, within a three-phase process: Input, Simulation, and Human-in-the-loop Feedback. The original contribution of this framework lies in its integration of agentic AI within a dynamic, iterative simulation environment. Unlike prior static mapping or high-risk incremental approaches, the 'Wisdom of AI Crowds' provides a risk-free virtual laboratory to test multiple policy scenarios, observe emergent behaviours over time, and incorporate expert validation before real-world implementation. This approach offers the potential to shift policymaking for wicked problems from reactive interventions to proactive, evidence-based experimentation, enabling the identification of more robust, well-vetted policy options. The framework explicitly incorporates considerations for ethical challenges, data representativeness, and simulation validation.

 

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Keywords


wicked problems; public policy; agentic AI; artificial societies; policy simulations; agent-based modelling; computational social science

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References


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DOI: http://dx.doi.org/10.46827/ejpss.v8i2.2096

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