Open Access
Research Paper
Peer Reviewed

Paper Title

The Impact of Prompt Engineering and Ethics on the Evolution of Generative AI

Article Identifiers

Registration ID: IJNRD_310140

Published ID: IJNRD2510260

: https://doi.org/10.56975/ijnrd.v10i10.310140

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Keywords

Generative AI, Prompt Engineering, Ethical Implications, GPT, Content Creation

Abstract

Generative Artificial Intelligence (AI) has rapidly evolved as a ground-breaking technology, revolutionizing content creation across various domains, including text, images, music, and more. Central to this advancement is the concept of prompt engineering, a crucial technique that involves carefully crafting input prompts to effectively guide AI models, particularly those built on sophisticated architectures like GPT and DALL-E, in generating precise and high- quality outputs. As AI continues to integrate into creative and professional fields, understanding the intricacies of prompt engineering becomes increasingly important. This paper delves into the fundamental principles and recent advancements in generative AI, with a special emphasis on how prompt engineering optimizes model performance and adaptability. We explore various strategies for fine-tuning prompts to achieve targeted objectives, such as enhancing creativity, ensuring factual accuracy, and controlling the tone, style, and content of the generated material. By providing practical insights and examples, we highlight the pivotal role of prompt engineering in shaping the future of AI-driven content generation. Additionally, this study addresses the ethical considerations surrounding generative AI, including issues related to bias, intellectual property rights, and the risks of misuse. Through a comprehensive analysis, this research enriches the understanding of generative AI and prompt engineering, shedding light on their applications, challenges, and future potential.

How To Cite (APA)

Debajyoti Chakraborty & Yadika Prasad (October-2025). The Impact of Prompt Engineering and Ethics on the Evolution of Generative AI. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 10(10), c540-c548. https://doi.org/10.56975/ijnrd.v10i10.310140

Citation

Issue

Other Publication Details

Paper Reg. ID: IJNRD_310140

Published Paper Id: IJNRD2510260

Research Area: Other area not in list

Author Type: Indian Author

Country: Siliguri, West Bengal, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2510260.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2510260

Crossref DOI: https://doi.org/10.56975/ijnrd.v10i10.310140

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Publication Timeline

Paper Submission
20-10-2025
Peer Review
Through Scholar9.com Platform
Paper Acceptance
27-10-2025
Paper Publication
31-10-2025

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