LLMs as Writing Assistants: Exploring Perspectives on Sense of Ownership and Reasoning

arXiv:2404.00027v1 Announce Type: cross
Abstract: Sense of ownership in writing confines our investment of thoughts, time, and contribution, leading to attachment to the output. However, using writing assistants introduces a mental dilemma, as some content isn't directly our creation. For instance, we tend to credit Large Language Models (LLMs) more in creative tasks, even though all tasks are equal for them. Additionally, while we may not claim complete ownership of LLM-generated content, we freely claim authorship. We conduct a short …

abstract arxiv assistants credit cs.ai cs.cl cs.cy cs.hc cs.lg however instance investment isn language language models large language large language models llms ownership perspectives reasoning sense thoughts type writing