"Global is Good, Local is Bad?": Understanding Brand Bias in LLMs
This addresses brand bias in LLMs, a problem for applications like product recommendation and market analysis, and is incremental as it builds on prior social bias research.
The study tackled brand bias in LLMs, finding consistent biases such as disproportionately associating global brands with positive attributes and recommending luxury gifts for high-income countries, with country-of-origin effects boosting local brand preference in specific contexts.
Many recent studies have investigated social biases in LLMs but brand bias has received little attention. This research examines the biases exhibited by LLMs towards different brands, a significant concern given the widespread use of LLMs in affected use cases such as product recommendation and market analysis. Biased models may perpetuate societal inequalities, unfairly favoring established global brands while marginalizing local ones. Using a curated dataset across four brand categories, we probe the behavior of LLMs in this space. We find a consistent pattern of bias in this space -- both in terms of disproportionately associating global brands with positive attributes and disproportionately recommending luxury gifts for individuals in high-income countries. We also find LLMs are subject to country-of-origin effects which may boost local brand preference in LLM outputs in specific contexts.