What type of study is this?

This is a Systematic Review study (also classified as: Mixed-Methods Case Studies).

SOTA large language models’ contribution on the design of economic policies

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Systematic review reveals large language models can improve multiple policy areas, suggesting potential for efficiency in economic decisions.

LLM-assisted drafting accelerates preliminary policy formulation by approximately 50%, emphasizing the importance of expert oversight.
The analysis identifies key areas where artificial intelligence alters workflows in problem diagnosis, option generation, and impact assessment.
Contemporary LLMs face vulnerabilities like training-data bias and hallucination, which require effective mitigation strategies.
The synthesis of normative frameworks seeks to define balanced policy while accommodating ethical concerns and democratic accountability.

Zelin Zhao (2025) studied this question.

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Systematic review reveals large language models can improve multiple policy areas, suggesting potential for efficiency in economic decisions.