Enhancing the Efficacy of Generative AI through User-Centric Prompt Optimization
My research proposal aims to address the gap between the vast potential of generative AI models in content creation and the challenges users face in harnessing this potential due to the complexity of prompt engineering. Generative AI, exemplified by models like GPT-3 and GPT-4, offers unprecedented opportunities for producing diverse, creative, and highly relevant content across a range of applications, from marketing and education to technical writing and beyond. However, the effectiveness of these AI models is significantly influenced by the quality of the prompts or queries they are given.
This research focuses on developing a comprehensive platform GenieWrite that simplifies and enhances the process of crafting these prompts. By doing so, it seeks to democratize the use of generative AI, making it accessible and effective for users regardless of their technical expertise. The platform aims to provide users with tools and methodologies for prompt optimization, incorporating principles from linguistics, psychology, and computer science to improve the interaction between humans and AI, thereby enhancing the quality and relevance of the AI-generated content.
The proposal outlines a mixed-methods research approach to design, test, and refine this platform. It includes a literature review to situate the project within current academic and practical knowledge on AI content generation and prompt engineering, a detailed research design and methodology section explaining how the project will be carried out, and a discussion of the expected implications of this work. By addressing both practical and theoretical aspects of AI-driven content creation, this research aspires to make significant contributions to the field, offering insights into effective human-AI collaboration in creative processes.