Art or Artifice? Large Language Models and the False Promise of Creativity

Autor:	Chakrabarty, Tuhin, Laban, Philippe, Agarwal, Divyansh, Muresan, Smaranda, Wu, Chien-Sheng
Rok vydání:	2023
Předmět:	Computer Science - Computation and Language Computer Science - Artificial Intelligence Computer Science - Human-Computer Interaction
Druh dokumentu:	Working Paper
Popis:	Researchers have argued that large language models (LLMs) exhibit high-quality writing capabilities from blogs to stories. However, evaluating objectively the creativity of a piece of writing is challenging. Inspired by the Torrance Test of Creative Thinking (TTCT), which measures creativity as a process, we use the Consensual Assessment Technique [3] and propose the Torrance Test of Creative Writing (TTCW) to evaluate creativity as a product. TTCW consists of 14 binary tests organized into the original dimensions of Fluency, Flexibility, Originality, and Elaboration. We recruit 10 creative writers and implement a human assessment of 48 stories written either by professional authors or LLMs using TTCW. Our analysis shows that LLM-generated stories pass 3-10X less TTCW tests than stories written by professionals. In addition, we explore the use of LLMs as assessors to automate the TTCW evaluation, revealing that none of the LLMs positively correlate with the expert assessments. Comment: ACM CHI 2024
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2309.14556 Zobrazit plný text záznamu View this record from Arxiv