Human-Centered Prompt Engineering: Techniques for Ethical and Inclusive LLM Outputs
DOI:
https://doi.org/10.32628/CSEIT25113357Keywords:
Prompt Engineering, Responsible AI, Bias Mitigation, Inclusive AI, Large Language Models, Human-Centered DesignAbstract
Large Language Models (LLMs) are being integrated into public-facing applications more and more despite their ethical and social outputs being of growing concern. They often generate biased recommendations, reflect exclusionary language, and amplify societal inequities. LLMs often reflect exclusionary language patterns in their responses. Our societal inequities writ large are their target. This paper positions the issue as fundamentally a human-centered design challenge—a prompt engineering problem—by critiquing the way prompts shape LLM behavior, rather than attributing the issue solely to societal inequities reflected in their outputs.
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