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Human-Centered Prompt Engineering: Techniques for Ethical and Inclusive LLM Outputs

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  • Kapil Kumar Goyal

Abstract

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.

Suggested Citation

  • Kapil Kumar Goyal, 2025. "Human-Centered Prompt Engineering: Techniques for Ethical and Inclusive LLM Outputs," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 11(3), pages 897-903, June.
    • Handle: RePEc:jbh:ijsrcs:v11:y2025:i3:id:1542
    DOI: 10.32628/CSEIT25113357
    Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT25113357
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