Assessment Method for Generative AI Technology in Foresight and Policy Design in Public Management: Expanding AI Trustability for Anticipatory Governance
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Abstract
Objective: to develop and evaluate a generative AI system prototype and assessment method that supports anticipatory governance by integrating foresight and policy design, enabling stakeholders to anticipate and proactively address emerging challenges in public policy. Methods: the study uses a design science research approach, combining institutional and explainable AI frameworks. It designs and assesses a generative AI prototype through three case scenarios focusing on environmental, electoral, and labor regulations, and expands results to an assessment protocol. Results: the analysis demonstrates the strengths and limitations of generative AI in AG systems. The study produces a systemic framework and an assessment protocol for evaluating AI’s role in augmenting AG capabilities, focusing on enhancing trust and reliability. Conclusions: the article’s main contribution is the proposed assessment protocol that contributes to both theory and practice by providing a replicable method for enhancing trustability in AI-driven AG. The findings support researchers and policymakers in reflecting on and utilizing responsible AI to navigate complex geopolitical, environmental, and societal challenges.
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Panizzon, M., Janissek-Muniz, R., Borges, N. M., & Cainelli, A. (2025). Assessment Method for Generative AI Technology in Foresight and Policy Design in Public Management: Expanding AI Trustability for Anticipatory Governance. Brazilian Administration Review, 22(3), e240196. https://doi.org/10.1590/1807-7692bar2025240196
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Hassani, H., Silva, E. S., Unger, S., TajMazinani, M., & Mac Feely, S. (2020). Artificial Intelligence (AI) or Intelligence Augmentation (IA): What is the future? AI (Switzerland), 1(2), 143-155. https://doi.org/10.3390/ai1020008
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Laux, J., Wachter, S., & Mittelstadt, B. (2024). Trustworthy artificial intelligence and the European Union AI act: On the conflation of trustworthiness and acceptability of risk. Regulation & Governance, 18(1), 3-32. https://doi.org/10.1111/rego.12512
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