University Of Texas Dallas Papers

Browse 1 peer-reviewed paper from University Of Texas Dallas spanning Human-AI Interaction, Creative Work (2024). Research powered by Prolific's high-quality participant data.

This page lists 1 peer-reviewed paper from researchers at University Of Texas Dallas in the Prolific Citations Library, a curated collection of research powered by high-quality human data from Prolific.

Papers (1 of 1)

Large language model in creative work: The role of collaboration modality and user expertise

Authors: Z Chen, J Chan

Year: 2024

Published in: Management Science, 2024 - pubsonline.informs.org

Institution: University of Texas Dallas

Research Area: Human-AI Interaction, Creative Work, Behavioral Science

Discipline: Social Science

Using large language models (LLMs) as sounding boards improves ad content quality for nonexpert users, while using LLMs as ghostwriters can negatively impact expert users due to anchoring effects.

Methods: An experiment comparing ad copy creation with and without LLM assistance, focusing on two collaboration modalities: ghostwriting and sounding board approaches. Ad performance was measured via social media click rates, supported by textual analysis.

Key Findings: Effectiveness of LLM collaboration modalities (ghostwriting vs. sounding board) on ad quality and business outcomes for expert and nonexpert users.

DOI: https://doi.org/10.1287/mnsc.2023.03014

Citations: 180