The systematic review explores how people perceive bias and related concepts in large language models (LLMs). It analyzes the advantages, biases, and conflicting perceptions of LLMs across various applications. The study also delves into factors influencing perceptions and concerns about LLM applications.
The review highlights that while LLMs offer time-saving benefits and cross-cultural communication enhancements, they also face challenges with distribution bias leading to generic responses. Participants showed varying levels of awareness regarding inherent biases in LLM outputs. Conflicting views emerged on the coherence, impacts, appropriateness, efficiency, effectiveness, explainability, and anthropomorphism of LLMs.
Factors such as task dependencies, domain limitations, personal backgrounds, contextual needs, and expectations influence individuals' perceptions of LLM performances. The study underscores the importance of understanding diverse perspectives to enhance user experience and mitigate risks associated with biased outputs.
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arxiv.org
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by Lu Wang,Max ... at arxiv.org 03-05-2024
https://arxiv.org/pdf/2309.14504.pdfDeeper Inquiries