Location
https://www.kennesaw.edu/ccse/events/computing-showcase/fa24-cday-program.php
Document Type
Event
Start Date
19-11-2024 4:00 PM
Description
A. Background: Prompt engineering refers to the process of designing and refining input prompts for AI models (especially language models like GPT) to improve their outputs. It has become a critical tool in maximizing the performance and utility of AI models in diverse applications, from customer service to content creation. Beyond technical aspects, the interaction between humans and AI is increasingly shaped by the effectiveness of these prompts. B. Motivation: As AI becomes more integrated into daily life, the way humans interact with AI models is profoundly influenced by prompt engineering. Misaligned prompts can lead to misunderstanding, confusion, or unintended outcomes, affecting both the utility of AI systems and the trust people place in them. Our project seeks to understand how different prompt strategies impact not only AI performance but also human perceptions and relationships with AI systems. By exploring these dynamics, we aim to develop best practices in prompt engineering that foster both efficient AI performance and positive human-AI relationships. C. Expected Results: We expect to demonstrate that well-constructed prompts not only improve AI output quality but also lead to more transparent, trustworthy, and meaningful human-AI interactions. This will be quantified through various metrics such as response accuracy, user satisfaction, and interaction smoothness.
Included in
GMC-2162 Prompt Engineering and its Effects On AI and Human Relationships: A Contemporary Approach
https://www.kennesaw.edu/ccse/events/computing-showcase/fa24-cday-program.php
A. Background: Prompt engineering refers to the process of designing and refining input prompts for AI models (especially language models like GPT) to improve their outputs. It has become a critical tool in maximizing the performance and utility of AI models in diverse applications, from customer service to content creation. Beyond technical aspects, the interaction between humans and AI is increasingly shaped by the effectiveness of these prompts. B. Motivation: As AI becomes more integrated into daily life, the way humans interact with AI models is profoundly influenced by prompt engineering. Misaligned prompts can lead to misunderstanding, confusion, or unintended outcomes, affecting both the utility of AI systems and the trust people place in them. Our project seeks to understand how different prompt strategies impact not only AI performance but also human perceptions and relationships with AI systems. By exploring these dynamics, we aim to develop best practices in prompt engineering that foster both efficient AI performance and positive human-AI relationships. C. Expected Results: We expect to demonstrate that well-constructed prompts not only improve AI output quality but also lead to more transparent, trustworthy, and meaningful human-AI interactions. This will be quantified through various metrics such as response accuracy, user satisfaction, and interaction smoothness.