Left Leaning Models: AI Assumptions on Economic Policy
This addresses the problem of understanding AI biases in economic policy for researchers and policymakers, but it is incremental as it builds on existing work on LLM assumptions.
The paper investigated the factors influencing large language models' evaluations of economic policy, finding that LLMs are most sensitive to unemployment, inequality, financial stability, and environmental harm, with consistent results across scenarios and models.
How does AI think about economic policy? While the use of large language models (LLMs) in economics is growing exponentially, their assumptions on economic issues remain a black box. This paper uses a conjoint experiment to tease out the main factors influencing LLMs' evaluation of economic policy. It finds that LLMs are most sensitive to unemployment, inequality, financial stability, and environmental harm and less sensitive to traditional macroeconomic concerns such as economic growth, inflation, and government debt. The results are remarkably consistent across scenarios and across models.