Attractiveness bias in Artificial Intelligence systems
DOI:
https://doi.org/10.23755/rm.v56i0.1745Keywords:
decision analysis, LLM, cognitive bias, attractiveness biasAbstract
Cognitive biases are thought patterns that can lead to incorrect decisions and judgments. Recently, Large Language Models (LLMs) have been shown to be capable of processing and understanding language well. However, because they learn from human data, they may also pick up human biases. While several scholars have analyzed social biases in LLMs, cognitive biases have not been studied as thoroughly. The goal of this research is to analyze how Artificial Intelligence (AI) may be susceptible to a particular cognitive bias, namely attractiveness bias, highlighting the consequences of using LLMs. This is a bias according to which people considered more attractive are viewed more positively than those considered less attractive. The use of AI in sensitive fields, such as the legal sector, where neutrality is essential, requires regulations that limit the risk of bias. However, the results show that AI technologies are susceptible to cognitive biases, highlighting a lack of clarity and robustness at key decision-making moments.References
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