@inbook{25d695a1bed149dbaafc3d4bbd4be30d,
title = "Facilitating Human Feedback for GenAI Prompt Optimization",
abstract = "This study investigates the optimization of Generative AI (GenAI) systems through human feedback, focusing on how varying feedback mechanisms influence the quality of GenAI outputs. We devised a Human-AI training loop where 32 students, divided into two groups, evaluated AI-generated responses based on a single prompt. One group assessed a single output, while the other compared two outputs. Preliminary results from this small-scale experiment suggest that comparative feedback might encourage more nuanced evaluations, highlighting the potential for improved human-AI collaboration in prompt optimization. Future research with larger samples is recommended to validate these findings and further explore effective feedback strategies for GenAI systems.",
keywords = "education, Generative AI, human-machine learning, prompt engineering",
author = "Jacob Sherson and Florent Vinchon",
note = "Publisher Copyright: {\textcopyright} 2024 The Authors.; 3rd International Conference on Hybrid Human-Artificial Intelligence, HHAI 2024 ; Conference date: 10-06-2024 Through 14-06-2024",
year = "2024",
month = jun,
doi = "10.3233/FAIA240230",
language = "English",
series = "Frontiers in Artificial Intelligence and Applications",
publisher = "IOS Press BV",
pages = "478--480",
editor = "Fabian Lorig and Jason Tucker and Lindstrom, {Adam Dahlgren} and Frank Dignum and Pradeep Murukannaiah and Andreas Theodorou and Pinar Yolum",
booktitle = "HHAI 2024",
address = "Netherlands",
}